{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Transfer Learning approach with the Tensorflow EfficientNet model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Import des librairies" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024-09-30 11:38:22.779561: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-09-30 11:38:22.783091: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-09-30 11:38:22.794062: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", "2024-09-30 11:38:22.813315: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", "2024-09-30 11:38:22.819202: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", "2024-09-30 11:38:22.834455: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2024-09-30 11:38:23.921894: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "tensorflow version 2.17.0\n", "Num GPUs Available: 0\n" ] } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "import os\n", "import cv2\n", "import pathlib\n", "import itertools\n", "import random\n", "import time\n", "import setuptools\n", "import datetime\n", "\n", "from PIL import Image\n", "\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "from matplotlib import cm\n", "\n", "from sklearn import metrics\n", "from sklearn.metrics import confusion_matrix\n", "\n", "import tensorflow as tf\n", "from tensorflow.keras.models import Sequential, Model\n", "from tensorflow.keras.utils import to_categorical\n", "from tensorflow.keras.applications import EfficientNetB1\n", "from tensorflow.keras import layers\n", "from tensorflow.keras.layers import Dense, Activation, Input\n", "from tensorflow.keras.layers import Dropout\n", "from tensorflow.keras.layers import Flatten\n", "from tensorflow.keras.layers import Conv2D\n", "from tensorflow.keras.layers import MaxPooling2D\n", "from tensorflow.keras.layers import GlobalAveragePooling2D\n", "from tensorflow.keras.callbacks import ReduceLROnPlateau\n", "from tensorflow.keras.callbacks import EarlyStopping\n", "from tensorflow.keras.callbacks import TensorBoard\n", "\n", "print(\"tensorflow version\",tf.__version__)\n", "print(\"Num GPUs Available: \", len(tf.config.list_physical_devices('GPU')))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Récupération des datas" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "16 classes\n" ] }, { "data": { "text/html": [ "
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name
id
42Trametes versicolor
53Stropharia ambigua
267Fuligo septica
330Cantharellus cinnabarinus
344Boletus edulis
362Amanita velosa
373Amanita muscaria
382Amanita bisporigera
401Agaricus augustus
1174Ceratiomyxa fruticulosa
1540Boletinellus merulioides
15162Bolbitius titubans
4920Craterellus fallax
939Mycena haematopus
407Ganoderma oregonense
271Flammulina velutipes
\n", "
" ], "text/plain": [ " name\n", "id \n", "42 Trametes versicolor\n", "53 Stropharia ambigua\n", "267 Fuligo septica\n", "330 Cantharellus cinnabarinus\n", "344 Boletus edulis\n", "362 Amanita velosa\n", "373 Amanita muscaria\n", "382 Amanita bisporigera\n", "401 Agaricus augustus\n", "1174 Ceratiomyxa fruticulosa\n", "1540 Boletinellus merulioides\n", "15162 Bolbitius titubans\n", "4920 Craterellus fallax\n", "939 Mycena haematopus\n", "407 Ganoderma oregonense\n", "271 Flammulina velutipes" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mo_db_path=\"../../data/LAYER2/MO/train/\"\n", "names_csv_path=\"../../data/LAYER2/names.csv\"\n", "data_dir = pathlib.Path(mo_db_path)\n", "\n", "def get_champi_name(mo_db_path, names_csv_path):\n", " \"\"\"\n", " Retourne le nom de la classe du champignon depuis le fichier names.csv de Mushroom Observer.\n", " Requiere numpy, pandas et os.\n", "\n", " Args:\n", " mo_db_path : Chemin vers le dossier contenant les classes\n", " names_csv_path : Chemin vers le fichier names.csv\n", "\n", " Returns:\n", " Dataframe Pandas avec IDs et noms\n", " \"\"\"\n", " # Imports des sources\n", " data_files = os.listdir(mo_db_path)\n", " names = pd.read_csv(names_csv_path, delimiter='\\t', index_col=0)\n", "\n", " # Recupération des ID des classes\n", " champi_classes = []\n", " for item in data_files:\n", " champi_classes.append(int(item))\n", " \n", " # Creation du DataFrame\n", " df = names[[\"text_name\"]].rename(columns={'text_name': 'name'})\n", " df = df.loc[champi_classes]\n", "\n", " # Resultat\n", " return df\n", " \n", "df = get_champi_name(mo_db_path, names_csv_path)\n", "\n", "print(len(df), 'classes')\n", "display(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Chargement des datas" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Créer les ensembles de données" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 112000 files belonging to 16 classes.\n", "Found 48000 files belonging to 16 classes.\n", "Found 1360 files belonging to 16 classes.\n", "Classes sauvegardées : ['1174', '15162', '1540', '267', '271', '330', '344', '362', '373', '382', '401', '407', '42', '4920', '53', '939']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2024-09-30 11:38:41.368217: I tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data_dir = '../../data/LAYER2/MO/'\n", "batch_size = 32\n", "img_height = 224\n", "img_width = 224\n", "\n", "train_ds = tf.keras.utils.image_dataset_from_directory(\n", " data_dir + '/train',\n", " validation_split=None,\n", " subset=None,\n", " shuffle=True,\n", " seed=random.randint(1,9999),\n", " image_size=(img_height, img_width),\n", " batch_size=batch_size\n", ")\n", "\n", "val_ds = tf.keras.utils.image_dataset_from_directory(\n", " data_dir + '/validation',\n", " validation_split=None,\n", " subset=None,\n", " shuffle=True,\n", " seed=random.randint(1,9999),\n", " image_size=(img_height, img_width),\n", " batch_size=batch_size\n", ")\n", "\n", "test_ds = tf.keras.utils.image_dataset_from_directory(\n", " data_dir + '/test',\n", " validation_split=None,\n", " subset=None,\n", " shuffle=False,\n", " seed=random.randint(1,9999),\n", " image_size=(img_height, img_width),\n", " batch_size=batch_size\n", ")\n", "\n", "# Sauvegarder les classes\n", "class_names = train_ds.class_names\n", "np.save('class_names.npy', class_names)\n", "print(\"Classes sauvegardées : \", class_names)\n", "\n", "# Visualiser un échantillon\n", "for images, labels in val_ds.take(1):\n", " for i in range(9):\n", " ax = plt.subplot(3, 3, i + 1)\n", " plt.imshow(images[i].numpy().astype(\"uint8\"))\n", " plt.title(class_names[labels[i]])\n", " plt.axis(\"off\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Création du CNN" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Model: \"functional\"\n",
       "
\n" ], "text/plain": [ "\u001b[1mModel: \"functional\"\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n",
       "┃ Layer (type)         Output Shape          Param #  Connected to      ┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n",
       "│ input_layer         │ (None, 224, 224,  │          0 │ -                 │\n",
       "│ (InputLayer)        │ 3)                │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ rescaling           │ (None, 224, 224,  │          0 │ input_layer[0][0] │\n",
       "│ (Rescaling)         │ 3)                │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ normalization       │ (None, 224, 224,  │          7 │ rescaling[0][0]   │\n",
       "│ (Normalization)     │ 3)                │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ rescaling_1         │ (None, 224, 224,  │          0 │ normalization[0]… │\n",
       "│ (Rescaling)         │ 3)                │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ stem_conv_pad       │ (None, 225, 225,  │          0 │ rescaling_1[0][0] │\n",
       "│ (ZeroPadding2D)     │ 3)                │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ stem_conv (Conv2D)  │ (None, 112, 112,  │        864 │ stem_conv_pad[0]… │\n",
       "│                     │ 32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ stem_bn             │ (None, 112, 112,  │        128 │ stem_conv[0][0]   │\n",
       "│ (BatchNormalizatio…32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ stem_activation     │ (None, 112, 112,  │          0 │ stem_bn[0][0]     │\n",
       "│ (Activation)        │ 32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_dwconv      │ (None, 112, 112,  │        288 │ stem_activation[ │\n",
       "│ (DepthwiseConv2D)   │ 32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_bn          │ (None, 112, 112,  │        128 │ block1a_dwconv[0… │\n",
       "│ (BatchNormalizatio…32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_activation  │ (None, 112, 112,  │          0 │ block1a_bn[0][0]  │\n",
       "│ (Activation)        │ 32)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_se_squeeze  │ (None, 32)        │          0 │ block1a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_se_reshape  │ (None, 1, 1, 32)  │          0 │ block1a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_se_reduce   │ (None, 1, 1, 8)   │        264 │ block1a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_se_expand   │ (None, 1, 1, 32)  │        288 │ block1a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_se_excite   │ (None, 112, 112,  │          0 │ block1a_activati… │\n",
       "│ (Multiply)          │ 32)               │            │ block1a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_project_co… │ (None, 112, 112,  │        512 │ block1a_se_excit… │\n",
       "│ (Conv2D)            │ 16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1a_project_bn  │ (None, 112, 112,  │         64 │ block1a_project_… │\n",
       "│ (BatchNormalizatio…16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_dwconv      │ (None, 112, 112,  │        144 │ block1a_project_… │\n",
       "│ (DepthwiseConv2D)   │ 16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_bn          │ (None, 112, 112,  │         64 │ block1b_dwconv[0… │\n",
       "│ (BatchNormalizatio…16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_activation  │ (None, 112, 112,  │          0 │ block1b_bn[0][0]  │\n",
       "│ (Activation)        │ 16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_se_squeeze  │ (None, 16)        │          0 │ block1b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_se_reshape  │ (None, 1, 1, 16)  │          0 │ block1b_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_se_reduce   │ (None, 1, 1, 4)   │         68 │ block1b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_se_expand   │ (None, 1, 1, 16)  │         80 │ block1b_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_se_excite   │ (None, 112, 112,  │          0 │ block1b_activati… │\n",
       "│ (Multiply)          │ 16)               │            │ block1b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_project_co… │ (None, 112, 112,  │        256 │ block1b_se_excit… │\n",
       "│ (Conv2D)            │ 16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_project_bn  │ (None, 112, 112,  │         64 │ block1b_project_… │\n",
       "│ (BatchNormalizatio…16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_drop        │ (None, 112, 112,  │          0 │ block1b_project_… │\n",
       "│ (Dropout)           │ 16)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block1b_add (Add)   │ (None, 112, 112,  │          0 │ block1b_drop[0][ │\n",
       "│                     │ 16)               │            │ block1a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_expand_conv │ (None, 112, 112,  │      1,536 │ block1b_add[0][0] │\n",
       "│ (Conv2D)            │ 96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_expand_bn   │ (None, 112, 112,  │        384 │ block2a_expand_c… │\n",
       "│ (BatchNormalizatio…96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_expand_act… │ (None, 112, 112,  │          0 │ block2a_expand_b… │\n",
       "│ (Activation)        │ 96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_dwconv_pad  │ (None, 113, 113,  │          0 │ block2a_expand_a… │\n",
       "│ (ZeroPadding2D)     │ 96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_dwconv      │ (None, 56, 56,    │        864 │ block2a_dwconv_p… │\n",
       "│ (DepthwiseConv2D)   │ 96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_bn          │ (None, 56, 56,    │        384 │ block2a_dwconv[0… │\n",
       "│ (BatchNormalizatio…96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_activation  │ (None, 56, 56,    │          0 │ block2a_bn[0][0]  │\n",
       "│ (Activation)        │ 96)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_se_squeeze  │ (None, 96)        │          0 │ block2a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_se_reshape  │ (None, 1, 1, 96)  │          0 │ block2a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_se_reduce   │ (None, 1, 1, 4)   │        388 │ block2a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_se_expand   │ (None, 1, 1, 96)  │        480 │ block2a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_se_excite   │ (None, 56, 56,    │          0 │ block2a_activati… │\n",
       "│ (Multiply)          │ 96)               │            │ block2a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_project_co… │ (None, 56, 56,    │      2,304 │ block2a_se_excit… │\n",
       "│ (Conv2D)            │ 24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2a_project_bn  │ (None, 56, 56,    │         96 │ block2a_project_… │\n",
       "│ (BatchNormalizatio…24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_expand_conv │ (None, 56, 56,    │      3,456 │ block2a_project_… │\n",
       "│ (Conv2D)            │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_expand_bn   │ (None, 56, 56,    │        576 │ block2b_expand_c… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_expand_act… │ (None, 56, 56,    │          0 │ block2b_expand_b… │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_dwconv      │ (None, 56, 56,    │      1,296 │ block2b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_bn          │ (None, 56, 56,    │        576 │ block2b_dwconv[0… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_activation  │ (None, 56, 56,    │          0 │ block2b_bn[0][0]  │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_se_squeeze  │ (None, 144)       │          0 │ block2b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_se_reshape  │ (None, 1, 1, 144) │          0 │ block2b_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_se_reduce   │ (None, 1, 1, 6)   │        870 │ block2b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_se_expand   │ (None, 1, 1, 144) │      1,008 │ block2b_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_se_excite   │ (None, 56, 56,    │          0 │ block2b_activati… │\n",
       "│ (Multiply)          │ 144)              │            │ block2b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_project_co… │ (None, 56, 56,    │      3,456 │ block2b_se_excit… │\n",
       "│ (Conv2D)            │ 24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_project_bn  │ (None, 56, 56,    │         96 │ block2b_project_… │\n",
       "│ (BatchNormalizatio…24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_drop        │ (None, 56, 56,    │          0 │ block2b_project_… │\n",
       "│ (Dropout)           │ 24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2b_add (Add)   │ (None, 56, 56,    │          0 │ block2b_drop[0][ │\n",
       "│                     │ 24)               │            │ block2a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_expand_conv │ (None, 56, 56,    │      3,456 │ block2b_add[0][0] │\n",
       "│ (Conv2D)            │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_expand_bn   │ (None, 56, 56,    │        576 │ block2c_expand_c… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_expand_act… │ (None, 56, 56,    │          0 │ block2c_expand_b… │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_dwconv      │ (None, 56, 56,    │      1,296 │ block2c_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_bn          │ (None, 56, 56,    │        576 │ block2c_dwconv[0… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_activation  │ (None, 56, 56,    │          0 │ block2c_bn[0][0]  │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_se_squeeze  │ (None, 144)       │          0 │ block2c_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_se_reshape  │ (None, 1, 1, 144) │          0 │ block2c_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_se_reduce   │ (None, 1, 1, 6)   │        870 │ block2c_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_se_expand   │ (None, 1, 1, 144) │      1,008 │ block2c_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_se_excite   │ (None, 56, 56,    │          0 │ block2c_activati… │\n",
       "│ (Multiply)          │ 144)              │            │ block2c_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_project_co… │ (None, 56, 56,    │      3,456 │ block2c_se_excit… │\n",
       "│ (Conv2D)            │ 24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_project_bn  │ (None, 56, 56,    │         96 │ block2c_project_… │\n",
       "│ (BatchNormalizatio…24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_drop        │ (None, 56, 56,    │          0 │ block2c_project_… │\n",
       "│ (Dropout)           │ 24)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block2c_add (Add)   │ (None, 56, 56,    │          0 │ block2c_drop[0][ │\n",
       "│                     │ 24)               │            │ block2b_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_expand_conv │ (None, 56, 56,    │      3,456 │ block2c_add[0][0] │\n",
       "│ (Conv2D)            │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_expand_bn   │ (None, 56, 56,    │        576 │ block3a_expand_c… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_expand_act… │ (None, 56, 56,    │          0 │ block3a_expand_b… │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_dwconv_pad  │ (None, 59, 59,    │          0 │ block3a_expand_a… │\n",
       "│ (ZeroPadding2D)     │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_dwconv      │ (None, 28, 28,    │      3,600 │ block3a_dwconv_p… │\n",
       "│ (DepthwiseConv2D)   │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_bn          │ (None, 28, 28,    │        576 │ block3a_dwconv[0… │\n",
       "│ (BatchNormalizatio…144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_activation  │ (None, 28, 28,    │          0 │ block3a_bn[0][0]  │\n",
       "│ (Activation)        │ 144)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_se_squeeze  │ (None, 144)       │          0 │ block3a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_se_reshape  │ (None, 1, 1, 144) │          0 │ block3a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_se_reduce   │ (None, 1, 1, 6)   │        870 │ block3a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_se_expand   │ (None, 1, 1, 144) │      1,008 │ block3a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_se_excite   │ (None, 28, 28,    │          0 │ block3a_activati… │\n",
       "│ (Multiply)          │ 144)              │            │ block3a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_project_co… │ (None, 28, 28,    │      5,760 │ block3a_se_excit… │\n",
       "│ (Conv2D)            │ 40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3a_project_bn  │ (None, 28, 28,    │        160 │ block3a_project_… │\n",
       "│ (BatchNormalizatio…40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_expand_conv │ (None, 28, 28,    │      9,600 │ block3a_project_… │\n",
       "│ (Conv2D)            │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_expand_bn   │ (None, 28, 28,    │        960 │ block3b_expand_c… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_expand_act… │ (None, 28, 28,    │          0 │ block3b_expand_b… │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_dwconv      │ (None, 28, 28,    │      6,000 │ block3b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_bn          │ (None, 28, 28,    │        960 │ block3b_dwconv[0… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_activation  │ (None, 28, 28,    │          0 │ block3b_bn[0][0]  │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_se_squeeze  │ (None, 240)       │          0 │ block3b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_se_reshape  │ (None, 1, 1, 240) │          0 │ block3b_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_se_reduce   │ (None, 1, 1, 10)  │      2,410 │ block3b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_se_expand   │ (None, 1, 1, 240) │      2,640 │ block3b_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_se_excite   │ (None, 28, 28,    │          0 │ block3b_activati… │\n",
       "│ (Multiply)          │ 240)              │            │ block3b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_project_co… │ (None, 28, 28,    │      9,600 │ block3b_se_excit… │\n",
       "│ (Conv2D)            │ 40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_project_bn  │ (None, 28, 28,    │        160 │ block3b_project_… │\n",
       "│ (BatchNormalizatio…40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_drop        │ (None, 28, 28,    │          0 │ block3b_project_… │\n",
       "│ (Dropout)           │ 40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3b_add (Add)   │ (None, 28, 28,    │          0 │ block3b_drop[0][ │\n",
       "│                     │ 40)               │            │ block3a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_expand_conv │ (None, 28, 28,    │      9,600 │ block3b_add[0][0] │\n",
       "│ (Conv2D)            │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_expand_bn   │ (None, 28, 28,    │        960 │ block3c_expand_c… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_expand_act… │ (None, 28, 28,    │          0 │ block3c_expand_b… │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_dwconv      │ (None, 28, 28,    │      6,000 │ block3c_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_bn          │ (None, 28, 28,    │        960 │ block3c_dwconv[0… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_activation  │ (None, 28, 28,    │          0 │ block3c_bn[0][0]  │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_se_squeeze  │ (None, 240)       │          0 │ block3c_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_se_reshape  │ (None, 1, 1, 240) │          0 │ block3c_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_se_reduce   │ (None, 1, 1, 10)  │      2,410 │ block3c_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_se_expand   │ (None, 1, 1, 240) │      2,640 │ block3c_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_se_excite   │ (None, 28, 28,    │          0 │ block3c_activati… │\n",
       "│ (Multiply)          │ 240)              │            │ block3c_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_project_co… │ (None, 28, 28,    │      9,600 │ block3c_se_excit… │\n",
       "│ (Conv2D)            │ 40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_project_bn  │ (None, 28, 28,    │        160 │ block3c_project_… │\n",
       "│ (BatchNormalizatio…40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_drop        │ (None, 28, 28,    │          0 │ block3c_project_… │\n",
       "│ (Dropout)           │ 40)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block3c_add (Add)   │ (None, 28, 28,    │          0 │ block3c_drop[0][ │\n",
       "│                     │ 40)               │            │ block3b_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_expand_conv │ (None, 28, 28,    │      9,600 │ block3c_add[0][0] │\n",
       "│ (Conv2D)            │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_expand_bn   │ (None, 28, 28,    │        960 │ block4a_expand_c… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_expand_act… │ (None, 28, 28,    │          0 │ block4a_expand_b… │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_dwconv_pad  │ (None, 29, 29,    │          0 │ block4a_expand_a… │\n",
       "│ (ZeroPadding2D)     │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_dwconv      │ (None, 14, 14,    │      2,160 │ block4a_dwconv_p… │\n",
       "│ (DepthwiseConv2D)   │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_bn          │ (None, 14, 14,    │        960 │ block4a_dwconv[0… │\n",
       "│ (BatchNormalizatio…240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_activation  │ (None, 14, 14,    │          0 │ block4a_bn[0][0]  │\n",
       "│ (Activation)        │ 240)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_se_squeeze  │ (None, 240)       │          0 │ block4a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_se_reshape  │ (None, 1, 1, 240) │          0 │ block4a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_se_reduce   │ (None, 1, 1, 10)  │      2,410 │ block4a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_se_expand   │ (None, 1, 1, 240) │      2,640 │ block4a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_se_excite   │ (None, 14, 14,    │          0 │ block4a_activati… │\n",
       "│ (Multiply)          │ 240)              │            │ block4a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_project_co… │ (None, 14, 14,    │     19,200 │ block4a_se_excit… │\n",
       "│ (Conv2D)            │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4a_project_bn  │ (None, 14, 14,    │        320 │ block4a_project_… │\n",
       "│ (BatchNormalizatio…80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_expand_conv │ (None, 14, 14,    │     38,400 │ block4a_project_… │\n",
       "│ (Conv2D)            │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_expand_bn   │ (None, 14, 14,    │      1,920 │ block4b_expand_c… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_expand_act… │ (None, 14, 14,    │          0 │ block4b_expand_b… │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_dwconv      │ (None, 14, 14,    │      4,320 │ block4b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_bn          │ (None, 14, 14,    │      1,920 │ block4b_dwconv[0… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_activation  │ (None, 14, 14,    │          0 │ block4b_bn[0][0]  │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_se_squeeze  │ (None, 480)       │          0 │ block4b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_se_reshape  │ (None, 1, 1, 480) │          0 │ block4b_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_se_reduce   │ (None, 1, 1, 20)  │      9,620 │ block4b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_se_expand   │ (None, 1, 1, 480) │     10,080 │ block4b_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_se_excite   │ (None, 14, 14,    │          0 │ block4b_activati… │\n",
       "│ (Multiply)          │ 480)              │            │ block4b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_project_co… │ (None, 14, 14,    │     38,400 │ block4b_se_excit… │\n",
       "│ (Conv2D)            │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_project_bn  │ (None, 14, 14,    │        320 │ block4b_project_… │\n",
       "│ (BatchNormalizatio…80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_drop        │ (None, 14, 14,    │          0 │ block4b_project_… │\n",
       "│ (Dropout)           │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4b_add (Add)   │ (None, 14, 14,    │          0 │ block4b_drop[0][ │\n",
       "│                     │ 80)               │            │ block4a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_expand_conv │ (None, 14, 14,    │     38,400 │ block4b_add[0][0] │\n",
       "│ (Conv2D)            │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_expand_bn   │ (None, 14, 14,    │      1,920 │ block4c_expand_c… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_expand_act… │ (None, 14, 14,    │          0 │ block4c_expand_b… │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_dwconv      │ (None, 14, 14,    │      4,320 │ block4c_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_bn          │ (None, 14, 14,    │      1,920 │ block4c_dwconv[0… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_activation  │ (None, 14, 14,    │          0 │ block4c_bn[0][0]  │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_se_squeeze  │ (None, 480)       │          0 │ block4c_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_se_reshape  │ (None, 1, 1, 480) │          0 │ block4c_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_se_reduce   │ (None, 1, 1, 20)  │      9,620 │ block4c_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_se_expand   │ (None, 1, 1, 480) │     10,080 │ block4c_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_se_excite   │ (None, 14, 14,    │          0 │ block4c_activati… │\n",
       "│ (Multiply)          │ 480)              │            │ block4c_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_project_co… │ (None, 14, 14,    │     38,400 │ block4c_se_excit… │\n",
       "│ (Conv2D)            │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_project_bn  │ (None, 14, 14,    │        320 │ block4c_project_… │\n",
       "│ (BatchNormalizatio…80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_drop        │ (None, 14, 14,    │          0 │ block4c_project_… │\n",
       "│ (Dropout)           │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4c_add (Add)   │ (None, 14, 14,    │          0 │ block4c_drop[0][ │\n",
       "│                     │ 80)               │            │ block4b_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_expand_conv │ (None, 14, 14,    │     38,400 │ block4c_add[0][0] │\n",
       "│ (Conv2D)            │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_expand_bn   │ (None, 14, 14,    │      1,920 │ block4d_expand_c… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_expand_act… │ (None, 14, 14,    │          0 │ block4d_expand_b… │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_dwconv      │ (None, 14, 14,    │      4,320 │ block4d_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_bn          │ (None, 14, 14,    │      1,920 │ block4d_dwconv[0… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_activation  │ (None, 14, 14,    │          0 │ block4d_bn[0][0]  │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_se_squeeze  │ (None, 480)       │          0 │ block4d_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_se_reshape  │ (None, 1, 1, 480) │          0 │ block4d_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_se_reduce   │ (None, 1, 1, 20)  │      9,620 │ block4d_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_se_expand   │ (None, 1, 1, 480) │     10,080 │ block4d_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_se_excite   │ (None, 14, 14,    │          0 │ block4d_activati… │\n",
       "│ (Multiply)          │ 480)              │            │ block4d_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_project_co… │ (None, 14, 14,    │     38,400 │ block4d_se_excit… │\n",
       "│ (Conv2D)            │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_project_bn  │ (None, 14, 14,    │        320 │ block4d_project_… │\n",
       "│ (BatchNormalizatio…80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_drop        │ (None, 14, 14,    │          0 │ block4d_project_… │\n",
       "│ (Dropout)           │ 80)               │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block4d_add (Add)   │ (None, 14, 14,    │          0 │ block4d_drop[0][ │\n",
       "│                     │ 80)               │            │ block4c_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_expand_conv │ (None, 14, 14,    │     38,400 │ block4d_add[0][0] │\n",
       "│ (Conv2D)            │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_expand_bn   │ (None, 14, 14,    │      1,920 │ block5a_expand_c… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_expand_act… │ (None, 14, 14,    │          0 │ block5a_expand_b… │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_dwconv      │ (None, 14, 14,    │     12,000 │ block5a_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_bn          │ (None, 14, 14,    │      1,920 │ block5a_dwconv[0… │\n",
       "│ (BatchNormalizatio…480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_activation  │ (None, 14, 14,    │          0 │ block5a_bn[0][0]  │\n",
       "│ (Activation)        │ 480)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_se_squeeze  │ (None, 480)       │          0 │ block5a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_se_reshape  │ (None, 1, 1, 480) │          0 │ block5a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_se_reduce   │ (None, 1, 1, 20)  │      9,620 │ block5a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_se_expand   │ (None, 1, 1, 480) │     10,080 │ block5a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_se_excite   │ (None, 14, 14,    │          0 │ block5a_activati… │\n",
       "│ (Multiply)          │ 480)              │            │ block5a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_project_co… │ (None, 14, 14,    │     53,760 │ block5a_se_excit… │\n",
       "│ (Conv2D)            │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5a_project_bn  │ (None, 14, 14,    │        448 │ block5a_project_… │\n",
       "│ (BatchNormalizatio…112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_expand_conv │ (None, 14, 14,    │     75,264 │ block5a_project_… │\n",
       "│ (Conv2D)            │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_expand_bn   │ (None, 14, 14,    │      2,688 │ block5b_expand_c… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_expand_act… │ (None, 14, 14,    │          0 │ block5b_expand_b… │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_dwconv      │ (None, 14, 14,    │     16,800 │ block5b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_bn          │ (None, 14, 14,    │      2,688 │ block5b_dwconv[0… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_activation  │ (None, 14, 14,    │          0 │ block5b_bn[0][0]  │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_se_squeeze  │ (None, 672)       │          0 │ block5b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_se_reshape  │ (None, 1, 1, 672) │          0 │ block5b_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_se_reduce   │ (None, 1, 1, 28)  │     18,844 │ block5b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_se_expand   │ (None, 1, 1, 672) │     19,488 │ block5b_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_se_excite   │ (None, 14, 14,    │          0 │ block5b_activati… │\n",
       "│ (Multiply)          │ 672)              │            │ block5b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_project_co… │ (None, 14, 14,    │     75,264 │ block5b_se_excit… │\n",
       "│ (Conv2D)            │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_project_bn  │ (None, 14, 14,    │        448 │ block5b_project_… │\n",
       "│ (BatchNormalizatio…112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_drop        │ (None, 14, 14,    │          0 │ block5b_project_… │\n",
       "│ (Dropout)           │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5b_add (Add)   │ (None, 14, 14,    │          0 │ block5b_drop[0][ │\n",
       "│                     │ 112)              │            │ block5a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_expand_conv │ (None, 14, 14,    │     75,264 │ block5b_add[0][0] │\n",
       "│ (Conv2D)            │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_expand_bn   │ (None, 14, 14,    │      2,688 │ block5c_expand_c… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_expand_act… │ (None, 14, 14,    │          0 │ block5c_expand_b… │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_dwconv      │ (None, 14, 14,    │     16,800 │ block5c_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_bn          │ (None, 14, 14,    │      2,688 │ block5c_dwconv[0… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_activation  │ (None, 14, 14,    │          0 │ block5c_bn[0][0]  │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_se_squeeze  │ (None, 672)       │          0 │ block5c_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_se_reshape  │ (None, 1, 1, 672) │          0 │ block5c_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_se_reduce   │ (None, 1, 1, 28)  │     18,844 │ block5c_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_se_expand   │ (None, 1, 1, 672) │     19,488 │ block5c_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_se_excite   │ (None, 14, 14,    │          0 │ block5c_activati… │\n",
       "│ (Multiply)          │ 672)              │            │ block5c_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_project_co… │ (None, 14, 14,    │     75,264 │ block5c_se_excit… │\n",
       "│ (Conv2D)            │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_project_bn  │ (None, 14, 14,    │        448 │ block5c_project_… │\n",
       "│ (BatchNormalizatio…112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_drop        │ (None, 14, 14,    │          0 │ block5c_project_… │\n",
       "│ (Dropout)           │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5c_add (Add)   │ (None, 14, 14,    │          0 │ block5c_drop[0][ │\n",
       "│                     │ 112)              │            │ block5b_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_expand_conv │ (None, 14, 14,    │     75,264 │ block5c_add[0][0] │\n",
       "│ (Conv2D)            │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_expand_bn   │ (None, 14, 14,    │      2,688 │ block5d_expand_c… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_expand_act… │ (None, 14, 14,    │          0 │ block5d_expand_b… │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_dwconv      │ (None, 14, 14,    │     16,800 │ block5d_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_bn          │ (None, 14, 14,    │      2,688 │ block5d_dwconv[0… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_activation  │ (None, 14, 14,    │          0 │ block5d_bn[0][0]  │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_se_squeeze  │ (None, 672)       │          0 │ block5d_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_se_reshape  │ (None, 1, 1, 672) │          0 │ block5d_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_se_reduce   │ (None, 1, 1, 28)  │     18,844 │ block5d_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_se_expand   │ (None, 1, 1, 672) │     19,488 │ block5d_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_se_excite   │ (None, 14, 14,    │          0 │ block5d_activati… │\n",
       "│ (Multiply)          │ 672)              │            │ block5d_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_project_co… │ (None, 14, 14,    │     75,264 │ block5d_se_excit… │\n",
       "│ (Conv2D)            │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_project_bn  │ (None, 14, 14,    │        448 │ block5d_project_… │\n",
       "│ (BatchNormalizatio…112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_drop        │ (None, 14, 14,    │          0 │ block5d_project_… │\n",
       "│ (Dropout)           │ 112)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block5d_add (Add)   │ (None, 14, 14,    │          0 │ block5d_drop[0][ │\n",
       "│                     │ 112)              │            │ block5c_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_expand_conv │ (None, 14, 14,    │     75,264 │ block5d_add[0][0] │\n",
       "│ (Conv2D)            │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_expand_bn   │ (None, 14, 14,    │      2,688 │ block6a_expand_c… │\n",
       "│ (BatchNormalizatio…672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_expand_act… │ (None, 14, 14,    │          0 │ block6a_expand_b… │\n",
       "│ (Activation)        │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_dwconv_pad  │ (None, 17, 17,    │          0 │ block6a_expand_a… │\n",
       "│ (ZeroPadding2D)     │ 672)              │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_dwconv      │ (None, 7, 7, 672) │     16,800 │ block6a_dwconv_p… │\n",
       "│ (DepthwiseConv2D)   │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_bn          │ (None, 7, 7, 672) │      2,688 │ block6a_dwconv[0… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_activation  │ (None, 7, 7, 672) │          0 │ block6a_bn[0][0]  │\n",
       "│ (Activation)        │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_se_squeeze  │ (None, 672)       │          0 │ block6a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_se_reshape  │ (None, 1, 1, 672) │          0 │ block6a_se_squee… │\n",
       "│ (Reshape)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_se_reduce   │ (None, 1, 1, 28)  │     18,844 │ block6a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_se_expand   │ (None, 1, 1, 672) │     19,488 │ block6a_se_reduc… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_se_excite   │ (None, 7, 7, 672) │          0 │ block6a_activati… │\n",
       "│ (Multiply)          │                   │            │ block6a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_project_co… │ (None, 7, 7, 192) │    129,024 │ block6a_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6a_project_bn  │ (None, 7, 7, 192) │        768 │ block6a_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_expand_conv │ (None, 7, 7,      │    221,184 │ block6a_project_… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_expand_bn   │ (None, 7, 7,      │      4,608 │ block6b_expand_c… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_expand_act… │ (None, 7, 7,      │          0 │ block6b_expand_b… │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_dwconv      │ (None, 7, 7,      │     28,800 │ block6b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_bn          │ (None, 7, 7,      │      4,608 │ block6b_dwconv[0… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_activation  │ (None, 7, 7,      │          0 │ block6b_bn[0][0]  │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_se_squeeze  │ (None, 1152)      │          0 │ block6b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_se_reshape  │ (None, 1, 1,      │          0 │ block6b_se_squee… │\n",
       "│ (Reshape)           │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_se_reduce   │ (None, 1, 1, 48)  │     55,344 │ block6b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_se_expand   │ (None, 1, 1,      │     56,448 │ block6b_se_reduc… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_se_excite   │ (None, 7, 7,      │          0 │ block6b_activati… │\n",
       "│ (Multiply)          │ 1152)             │            │ block6b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_project_co… │ (None, 7, 7, 192) │    221,184 │ block6b_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_project_bn  │ (None, 7, 7, 192) │        768 │ block6b_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_drop        │ (None, 7, 7, 192) │          0 │ block6b_project_… │\n",
       "│ (Dropout)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6b_add (Add)   │ (None, 7, 7, 192) │          0 │ block6b_drop[0][ │\n",
       "│                     │                   │            │ block6a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_expand_conv │ (None, 7, 7,      │    221,184 │ block6b_add[0][0] │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_expand_bn   │ (None, 7, 7,      │      4,608 │ block6c_expand_c… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_expand_act… │ (None, 7, 7,      │          0 │ block6c_expand_b… │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_dwconv      │ (None, 7, 7,      │     28,800 │ block6c_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_bn          │ (None, 7, 7,      │      4,608 │ block6c_dwconv[0… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_activation  │ (None, 7, 7,      │          0 │ block6c_bn[0][0]  │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_se_squeeze  │ (None, 1152)      │          0 │ block6c_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_se_reshape  │ (None, 1, 1,      │          0 │ block6c_se_squee… │\n",
       "│ (Reshape)           │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_se_reduce   │ (None, 1, 1, 48)  │     55,344 │ block6c_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_se_expand   │ (None, 1, 1,      │     56,448 │ block6c_se_reduc… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_se_excite   │ (None, 7, 7,      │          0 │ block6c_activati… │\n",
       "│ (Multiply)          │ 1152)             │            │ block6c_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_project_co… │ (None, 7, 7, 192) │    221,184 │ block6c_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_project_bn  │ (None, 7, 7, 192) │        768 │ block6c_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_drop        │ (None, 7, 7, 192) │          0 │ block6c_project_… │\n",
       "│ (Dropout)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6c_add (Add)   │ (None, 7, 7, 192) │          0 │ block6c_drop[0][ │\n",
       "│                     │                   │            │ block6b_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_expand_conv │ (None, 7, 7,      │    221,184 │ block6c_add[0][0] │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_expand_bn   │ (None, 7, 7,      │      4,608 │ block6d_expand_c… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_expand_act… │ (None, 7, 7,      │          0 │ block6d_expand_b… │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_dwconv      │ (None, 7, 7,      │     28,800 │ block6d_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_bn          │ (None, 7, 7,      │      4,608 │ block6d_dwconv[0… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_activation  │ (None, 7, 7,      │          0 │ block6d_bn[0][0]  │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_se_squeeze  │ (None, 1152)      │          0 │ block6d_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_se_reshape  │ (None, 1, 1,      │          0 │ block6d_se_squee… │\n",
       "│ (Reshape)           │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_se_reduce   │ (None, 1, 1, 48)  │     55,344 │ block6d_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_se_expand   │ (None, 1, 1,      │     56,448 │ block6d_se_reduc… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_se_excite   │ (None, 7, 7,      │          0 │ block6d_activati… │\n",
       "│ (Multiply)          │ 1152)             │            │ block6d_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_project_co… │ (None, 7, 7, 192) │    221,184 │ block6d_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_project_bn  │ (None, 7, 7, 192) │        768 │ block6d_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_drop        │ (None, 7, 7, 192) │          0 │ block6d_project_… │\n",
       "│ (Dropout)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6d_add (Add)   │ (None, 7, 7, 192) │          0 │ block6d_drop[0][ │\n",
       "│                     │                   │            │ block6c_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_expand_conv │ (None, 7, 7,      │    221,184 │ block6d_add[0][0] │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_expand_bn   │ (None, 7, 7,      │      4,608 │ block6e_expand_c… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_expand_act… │ (None, 7, 7,      │          0 │ block6e_expand_b… │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_dwconv      │ (None, 7, 7,      │     28,800 │ block6e_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_bn          │ (None, 7, 7,      │      4,608 │ block6e_dwconv[0… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_activation  │ (None, 7, 7,      │          0 │ block6e_bn[0][0]  │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_se_squeeze  │ (None, 1152)      │          0 │ block6e_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_se_reshape  │ (None, 1, 1,      │          0 │ block6e_se_squee… │\n",
       "│ (Reshape)           │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_se_reduce   │ (None, 1, 1, 48)  │     55,344 │ block6e_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_se_expand   │ (None, 1, 1,      │     56,448 │ block6e_se_reduc… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_se_excite   │ (None, 7, 7,      │          0 │ block6e_activati… │\n",
       "│ (Multiply)          │ 1152)             │            │ block6e_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_project_co… │ (None, 7, 7, 192) │    221,184 │ block6e_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_project_bn  │ (None, 7, 7, 192) │        768 │ block6e_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_drop        │ (None, 7, 7, 192) │          0 │ block6e_project_… │\n",
       "│ (Dropout)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block6e_add (Add)   │ (None, 7, 7, 192) │          0 │ block6e_drop[0][ │\n",
       "│                     │                   │            │ block6d_add[0][0] │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_expand_conv │ (None, 7, 7,      │    221,184 │ block6e_add[0][0] │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_expand_bn   │ (None, 7, 7,      │      4,608 │ block7a_expand_c… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_expand_act… │ (None, 7, 7,      │          0 │ block7a_expand_b… │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_dwconv      │ (None, 7, 7,      │     10,368 │ block7a_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_bn          │ (None, 7, 7,      │      4,608 │ block7a_dwconv[0… │\n",
       "│ (BatchNormalizatio…1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_activation  │ (None, 7, 7,      │          0 │ block7a_bn[0][0]  │\n",
       "│ (Activation)        │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_se_squeeze  │ (None, 1152)      │          0 │ block7a_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_se_reshape  │ (None, 1, 1,      │          0 │ block7a_se_squee… │\n",
       "│ (Reshape)           │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_se_reduce   │ (None, 1, 1, 48)  │     55,344 │ block7a_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_se_expand   │ (None, 1, 1,      │     56,448 │ block7a_se_reduc… │\n",
       "│ (Conv2D)            │ 1152)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_se_excite   │ (None, 7, 7,      │          0 │ block7a_activati… │\n",
       "│ (Multiply)          │ 1152)             │            │ block7a_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_project_co… │ (None, 7, 7, 320) │    368,640 │ block7a_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7a_project_bn  │ (None, 7, 7, 320) │      1,280 │ block7a_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_expand_conv │ (None, 7, 7,      │    614,400 │ block7a_project_… │\n",
       "│ (Conv2D)            │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_expand_bn   │ (None, 7, 7,      │      7,680 │ block7b_expand_c… │\n",
       "│ (BatchNormalizatio…1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_expand_act… │ (None, 7, 7,      │          0 │ block7b_expand_b… │\n",
       "│ (Activation)        │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_dwconv      │ (None, 7, 7,      │     17,280 │ block7b_expand_a… │\n",
       "│ (DepthwiseConv2D)   │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_bn          │ (None, 7, 7,      │      7,680 │ block7b_dwconv[0… │\n",
       "│ (BatchNormalizatio…1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_activation  │ (None, 7, 7,      │          0 │ block7b_bn[0][0]  │\n",
       "│ (Activation)        │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_se_squeeze  │ (None, 1920)      │          0 │ block7b_activati… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_se_reshape  │ (None, 1, 1,      │          0 │ block7b_se_squee… │\n",
       "│ (Reshape)           │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_se_reduce   │ (None, 1, 1, 80)  │    153,680 │ block7b_se_resha… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_se_expand   │ (None, 1, 1,      │    155,520 │ block7b_se_reduc… │\n",
       "│ (Conv2D)            │ 1920)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_se_excite   │ (None, 7, 7,      │          0 │ block7b_activati… │\n",
       "│ (Multiply)          │ 1920)             │            │ block7b_se_expan… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_project_co… │ (None, 7, 7, 320) │    614,400 │ block7b_se_excit… │\n",
       "│ (Conv2D)            │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_project_bn  │ (None, 7, 7, 320) │      1,280 │ block7b_project_… │\n",
       "│ (BatchNormalizatio… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_drop        │ (None, 7, 7, 320) │          0 │ block7b_project_… │\n",
       "│ (Dropout)           │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ block7b_add (Add)   │ (None, 7, 7, 320) │          0 │ block7b_drop[0][ │\n",
       "│                     │                   │            │ block7a_project_… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ top_conv (Conv2D)   │ (None, 7, 7,      │    409,600 │ block7b_add[0][0] │\n",
       "│                     │ 1280)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ top_bn              │ (None, 7, 7,      │      5,120 │ top_conv[0][0]    │\n",
       "│ (BatchNormalizatio…1280)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ top_activation      │ (None, 7, 7,      │          0 │ top_bn[0][0]      │\n",
       "│ (Activation)        │ 1280)             │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ global_average_poo… │ (None, 1280)      │          0 │ top_activation[0… │\n",
       "│ (GlobalAveragePool… │                   │            │                   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dense (Dense)       │ (None, 512)       │    655,872 │ global_average_p… │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dropout (Dropout)   │ (None, 512)       │          0 │ dense[0][0]       │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dense_1 (Dense)     │ (None, 128)       │     65,664 │ dropout[0][0]     │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dropout_1 (Dropout) │ (None, 128)       │          0 │ dense_1[0][0]     │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dense_2 (Dense)     │ (None, 64)        │      8,256 │ dropout_1[0][0]   │\n",
       "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
       "│ dense_3 (Dense)     │ (None, 16)        │      1,040 │ dense_2[0][0]     │\n",
       "└─────────────────────┴───────────────────┴────────────┴───────────────────┘\n",
       "
\n" ], "text/plain": [ "┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n", "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mConnected to \u001b[0m\u001b[1m \u001b[0m┃\n", "┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n", "│ input_layer │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ - │\n", "│ (\u001b[38;5;33mInputLayer\u001b[0m) │ \u001b[38;5;34m3\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ rescaling │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ input_layer[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mRescaling\u001b[0m) │ \u001b[38;5;34m3\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ normalization │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\u001b[0m, │ \u001b[38;5;34m7\u001b[0m │ rescaling[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mNormalization\u001b[0m) │ \u001b[38;5;34m3\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ rescaling_1 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ normalization[\u001b[38;5;34m0\u001b[0m]… │\n", "│ (\u001b[38;5;33mRescaling\u001b[0m) │ \u001b[38;5;34m3\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ stem_conv_pad │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m225\u001b[0m, \u001b[38;5;34m225\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ rescaling_1[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m) │ \u001b[38;5;34m3\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ stem_conv (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m864\u001b[0m │ stem_conv_pad[\u001b[38;5;34m0\u001b[0m]… │\n", "│ │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ stem_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m128\u001b[0m │ stem_conv[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ stem_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ stem_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m288\u001b[0m │ stem_activation[\u001b[38;5;34m…\u001b[0m │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m128\u001b[0m │ block1a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m32\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block1a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block1a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m8\u001b[0m) │ \u001b[38;5;34m264\u001b[0m │ block1a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m288\u001b[0m │ block1a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m32\u001b[0m) │ │ block1a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m512\u001b[0m │ block1a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m64\u001b[0m │ block1a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m144\u001b[0m │ block1a_project_… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m64\u001b[0m │ block1b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block1b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block1b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m4\u001b[0m) │ \u001b[38;5;34m68\u001b[0m │ block1b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m80\u001b[0m │ block1b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ block1b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m256\u001b[0m │ block1b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m64\u001b[0m │ block1b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m16\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block1b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block1b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m16\u001b[0m) │ │ block1a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m1,536\u001b[0m │ block1b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m384\u001b[0m │ block2a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_dwconv_pad │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m113\u001b[0m, \u001b[38;5;34m113\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2a_expand_a… │\n", "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m864\u001b[0m │ block2a_dwconv_p… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m384\u001b[0m │ block2a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m96\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m96\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m4\u001b[0m) │ \u001b[38;5;34m388\u001b[0m │ block2a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m96\u001b[0m) │ \u001b[38;5;34m480\u001b[0m │ block2a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m96\u001b[0m) │ │ block2a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m2,304\u001b[0m │ block2a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m96\u001b[0m │ block2a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m3,456\u001b[0m │ block2a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block2b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m1,296\u001b[0m │ block2b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block2b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m6\u001b[0m) │ \u001b[38;5;34m870\u001b[0m │ block2b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m1,008\u001b[0m │ block2b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ block2b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m3,456\u001b[0m │ block2b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m96\u001b[0m │ block2b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m24\u001b[0m) │ │ block2a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m3,456\u001b[0m │ block2b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block2c_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2c_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m1,296\u001b[0m │ block2c_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block2c_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2c_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2c_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block2c_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m6\u001b[0m) │ \u001b[38;5;34m870\u001b[0m │ block2c_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m1,008\u001b[0m │ block2c_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2c_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ block2c_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m3,456\u001b[0m │ block2c_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m96\u001b[0m │ block2c_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2c_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m24\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block2c_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block2c_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m24\u001b[0m) │ │ block2b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m3,456\u001b[0m │ block2c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block3a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_dwconv_pad │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m59\u001b[0m, \u001b[38;5;34m59\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3a_expand_a… │\n", "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m3,600\u001b[0m │ block3a_dwconv_p… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m576\u001b[0m │ block3a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m6\u001b[0m) │ \u001b[38;5;34m870\u001b[0m │ block3a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m144\u001b[0m) │ \u001b[38;5;34m1,008\u001b[0m │ block3a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m144\u001b[0m) │ │ block3a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m5,760\u001b[0m │ block3a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m160\u001b[0m │ block3a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m9,600\u001b[0m │ block3a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block3b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m6,000\u001b[0m │ block3b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block3b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m10\u001b[0m) │ \u001b[38;5;34m2,410\u001b[0m │ block3b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m2,640\u001b[0m │ block3b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ block3b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m9,600\u001b[0m │ block3b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m160\u001b[0m │ block3b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m40\u001b[0m) │ │ block3a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m9,600\u001b[0m │ block3b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block3c_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3c_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m6,000\u001b[0m │ block3c_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block3c_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3c_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3c_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block3c_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m10\u001b[0m) │ \u001b[38;5;34m2,410\u001b[0m │ block3c_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m2,640\u001b[0m │ block3c_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3c_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ block3c_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m9,600\u001b[0m │ block3c_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m160\u001b[0m │ block3c_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3c_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m40\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block3c_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block3c_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m40\u001b[0m) │ │ block3b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m9,600\u001b[0m │ block3c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block4a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_dwconv_pad │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m29\u001b[0m, \u001b[38;5;34m29\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4a_expand_a… │\n", "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,160\u001b[0m │ block4a_dwconv_p… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m960\u001b[0m │ block4a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m10\u001b[0m) │ \u001b[38;5;34m2,410\u001b[0m │ block4a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m240\u001b[0m) │ \u001b[38;5;34m2,640\u001b[0m │ block4a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m240\u001b[0m) │ │ block4a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m19,200\u001b[0m │ block4a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m320\u001b[0m │ block4a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m4,320\u001b[0m │ block4b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m20\u001b[0m) │ \u001b[38;5;34m9,620\u001b[0m │ block4b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m10,080\u001b[0m │ block4b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ block4b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m320\u001b[0m │ block4b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m80\u001b[0m) │ │ block4a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4c_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4c_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m4,320\u001b[0m │ block4c_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4c_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4c_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4c_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4c_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m20\u001b[0m) │ \u001b[38;5;34m9,620\u001b[0m │ block4c_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m10,080\u001b[0m │ block4c_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4c_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ block4c_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4c_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m320\u001b[0m │ block4c_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4c_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4c_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4c_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m80\u001b[0m) │ │ block4b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4d_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4d_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m4,320\u001b[0m │ block4d_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block4d_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4d_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4d_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block4d_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m20\u001b[0m) │ \u001b[38;5;34m9,620\u001b[0m │ block4d_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m10,080\u001b[0m │ block4d_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4d_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ block4d_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4d_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m320\u001b[0m │ block4d_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4d_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m80\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block4d_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block4d_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m80\u001b[0m) │ │ block4c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m38,400\u001b[0m │ block4d_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block5a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m12,000\u001b[0m │ block5a_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m1,920\u001b[0m │ block5a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m20\u001b[0m) │ \u001b[38;5;34m9,620\u001b[0m │ block5a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m480\u001b[0m) │ \u001b[38;5;34m10,080\u001b[0m │ block5a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m480\u001b[0m) │ │ block5a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m53,760\u001b[0m │ block5a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m448\u001b[0m │ block5a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m16,800\u001b[0m │ block5b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m28\u001b[0m) │ \u001b[38;5;34m18,844\u001b[0m │ block5b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m19,488\u001b[0m │ block5b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ block5b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m448\u001b[0m │ block5b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m112\u001b[0m) │ │ block5a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5c_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5c_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m16,800\u001b[0m │ block5c_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5c_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5c_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5c_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5c_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m28\u001b[0m) │ \u001b[38;5;34m18,844\u001b[0m │ block5c_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m19,488\u001b[0m │ block5c_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5c_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ block5c_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5c_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m448\u001b[0m │ block5c_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5c_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5c_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5c_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m112\u001b[0m) │ │ block5b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5d_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5d_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m16,800\u001b[0m │ block5d_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block5d_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5d_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5d_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block5d_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m28\u001b[0m) │ \u001b[38;5;34m18,844\u001b[0m │ block5d_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m19,488\u001b[0m │ block5d_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5d_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ block5d_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5d_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m448\u001b[0m │ block5d_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5d_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ \u001b[38;5;34m112\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block5d_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block5d_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ \u001b[38;5;34m112\u001b[0m) │ │ block5c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m75,264\u001b[0m │ block5d_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m2,688\u001b[0m │ block6a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_dwconv_pad │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m17\u001b[0m, \u001b[38;5;34m17\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6a_expand_a… │\n", "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m) │ \u001b[38;5;34m672\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m16,800\u001b[0m │ block6a_dwconv_p… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m2,688\u001b[0m │ block6a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m28\u001b[0m) │ \u001b[38;5;34m18,844\u001b[0m │ block6a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m19,488\u001b[0m │ block6a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m672\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ │ │ block6a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m129,024\u001b[0m │ block6a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m768\u001b[0m │ block6a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m221,184\u001b[0m │ block6a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m28,800\u001b[0m │ block6b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1152\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m48\u001b[0m) │ \u001b[38;5;34m55,344\u001b[0m │ block6b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m56,448\u001b[0m │ block6b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ block6b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m221,184\u001b[0m │ block6b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m768\u001b[0m │ block6b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ │ │ block6a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m221,184\u001b[0m │ block6b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6c_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6c_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m28,800\u001b[0m │ block6c_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6c_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6c_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1152\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6c_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6c_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m48\u001b[0m) │ \u001b[38;5;34m55,344\u001b[0m │ block6c_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m56,448\u001b[0m │ block6c_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6c_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ block6c_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m221,184\u001b[0m │ block6c_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m768\u001b[0m │ block6c_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6c_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6c_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6c_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ │ │ block6b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m221,184\u001b[0m │ block6c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6d_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6d_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m28,800\u001b[0m │ block6d_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6d_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6d_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1152\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6d_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6d_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m48\u001b[0m) │ \u001b[38;5;34m55,344\u001b[0m │ block6d_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m56,448\u001b[0m │ block6d_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6d_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ block6d_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m221,184\u001b[0m │ block6d_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m768\u001b[0m │ block6d_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6d_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6d_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6d_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ │ │ block6c_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m221,184\u001b[0m │ block6d_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6e_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6e_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m28,800\u001b[0m │ block6e_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block6e_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6e_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1152\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6e_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6e_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m48\u001b[0m) │ \u001b[38;5;34m55,344\u001b[0m │ block6e_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m56,448\u001b[0m │ block6e_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block6e_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ block6e_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m221,184\u001b[0m │ block6e_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m768\u001b[0m │ block6e_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6e_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block6e_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m192\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block6e_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ │ │ block6d_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m221,184\u001b[0m │ block6e_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block7a_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7a_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m10,368\u001b[0m │ block7a_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m4,608\u001b[0m │ block7a_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7a_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1152\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block7a_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7a_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m48\u001b[0m) │ \u001b[38;5;34m55,344\u001b[0m │ block7a_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m56,448\u001b[0m │ block7a_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7a_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1152\u001b[0m) │ │ block7a_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m368,640\u001b[0m │ block7a_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7a_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m1,280\u001b[0m │ block7a_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_expand_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m614,400\u001b[0m │ block7a_project_… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_expand_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m7,680\u001b[0m │ block7b_expand_c… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_expand_act… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7b_expand_b… │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_dwconv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m17,280\u001b[0m │ block7b_expand_a… │\n", "│ (\u001b[38;5;33mDepthwiseConv2D\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m7,680\u001b[0m │ block7b_dwconv[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7b_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_se_squeeze │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1920\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block7b_activati… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_se_reshape │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7b_se_squee… │\n", "│ (\u001b[38;5;33mReshape\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_se_reduce │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m80\u001b[0m) │ \u001b[38;5;34m153,680\u001b[0m │ block7b_se_resha… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_se_expand │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m, \u001b[38;5;34m1\u001b[0m, │ \u001b[38;5;34m155,520\u001b[0m │ block7b_se_reduc… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_se_excite │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ block7b_activati… │\n", "│ (\u001b[38;5;33mMultiply\u001b[0m) │ \u001b[38;5;34m1920\u001b[0m) │ │ block7b_se_expan… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_project_co… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m614,400\u001b[0m │ block7b_se_excit… │\n", "│ (\u001b[38;5;33mConv2D\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_project_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m1,280\u001b[0m │ block7b_project_… │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_drop │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block7b_project_… │\n", "│ (\u001b[38;5;33mDropout\u001b[0m) │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ block7b_add (\u001b[38;5;33mAdd\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m320\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ block7b_drop[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m…\u001b[0m │\n", "│ │ │ │ block7a_project_… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ top_conv (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m409,600\u001b[0m │ block7b_add[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ │ \u001b[38;5;34m1280\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ top_bn │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m5,120\u001b[0m │ top_conv[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1280\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ top_activation │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, │ \u001b[38;5;34m0\u001b[0m │ top_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "│ (\u001b[38;5;33mActivation\u001b[0m) │ \u001b[38;5;34m1280\u001b[0m) │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ global_average_poo… │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1280\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ top_activation[\u001b[38;5;34m0\u001b[0m… │\n", "│ (\u001b[38;5;33mGlobalAveragePool…\u001b[0m │ │ │ │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dense (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m655,872\u001b[0m │ global_average_p… │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dropout (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ dense[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dense_1 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m65,664\u001b[0m │ dropout[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dropout_1 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │ dense_1[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dense_2 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m8,256\u001b[0m │ dropout_1[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n", "│ dense_3 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m1,040\u001b[0m │ dense_2[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m] │\n", "└─────────────────────┴───────────────────┴────────────┴───────────────────┘\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Total params: 7,306,071 (27.87 MB)\n",
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 Trainable params: 730,832 (2.79 MB)\n",
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\n" ], "text/plain": [ "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m730,832\u001b[0m (2.79 MB)\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Non-trainable params: 6,575,239 (25.08 MB)\n",
       "
\n" ], "text/plain": [ "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m6,575,239\u001b[0m (25.08 MB)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Charger le modèle pré-entraîné sur ImageNet\n", "base_model = EfficientNetB1(weights='imagenet', include_top=False, input_shape=(224, 224, 3))\n", "\n", "# Congeler les couches de base\n", "for layer in base_model.layers:\n", " layer.trainable = False\n", "\n", "# Couches de sorie\n", "x = base_model.output\n", "x = GlobalAveragePooling2D()(x)\n", "x = Dense(512, activation='relu')(x)\n", "x = Dropout(0.5)(x)\n", "x = Dense(128, activation='relu')(x)\n", "x = Dropout(0.5)(x)\n", "x = Dense(64, activation='relu')(x)\n", "x = Dense(len(class_names), activation='softmax')(x)\n", "\n", "model = Model(inputs=base_model.input, outputs=x)\n", "\n", "model.compile(optimizer='adam',\n", " loss='sparse_categorical_crossentropy',\n", " metrics=['accuracy'])\n", "\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Entrainement" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Configuration pour les performances afin d'éviter une saturation de la RAM\n", "options = tf.data.Options()\n", "\n", "# Stop magic stuff that eats up RAM:\n", "options.autotune.enabled = False\n", "options.experimental_distribute.auto_shard_policy = (\n", " tf.data.experimental.AutoShardPolicy.OFF)\n", "options.experimental_optimization.inject_prefetch = False\n", "\n", "train_ds = train_ds.with_options(options)\n", "val_ds = val_ds.with_options(options)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Mise en place de Tensorboard\n", "log_dir = \"logs/\" + datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n", "tensorboard_callback = TensorBoard(log_dir=log_dir, histogram_freq=1)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/9\n", "\u001b[1m3500/3500\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4666s\u001b[0m 1s/step - accuracy: 0.7257 - loss: 0.8521 - val_accuracy: 0.8565 - val_loss: 0.5012 - learning_rate: 0.0010\n", "Epoch 2/9\n", "\u001b[1m3500/3500\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4777s\u001b[0m 1s/step - accuracy: 0.9306 - loss: 0.2337 - val_accuracy: 0.8615 - val_loss: 0.5271 - learning_rate: 0.0010\n", "Epoch 3/9\n", "\u001b[1m3500/3500\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4799s\u001b[0m 1s/step - accuracy: 0.9503 - loss: 0.1681 - val_accuracy: 0.8585 - val_loss: 0.5629 - learning_rate: 0.0010\n", "Epoch 4/9\n", "\u001b[1m3500/3500\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4786s\u001b[0m 1s/step - accuracy: 0.9589 - loss: 0.1402 - val_accuracy: 0.8645 - val_loss: 0.5321 - learning_rate: 0.0010\n" ] } ], "source": [ "epochs=9\n", "\n", "history = model.fit(\n", " train_ds,\n", " validation_data=val_ds,\n", " epochs=epochs,\n", " callbacks=[ReduceLROnPlateau(monitor='val_loss', factor=0.4, patience=3, min_lr=0.001), EarlyStopping(monitor='val_loss', patience=3), tensorboard_callback] # Reduction du LR + EarlyStop + Tensorboard\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Évaluation finale" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m43/43\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m44s\u001b[0m 978ms/step\n", "Classes prédites : ['1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '271', '4920', '1174', '1174', '271', '1174', '362', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', '1174', 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'53', '53', '344', '53', '53', '53', '53', '53', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '939', '15162']\n" ] } ], "source": [ "# Charger les noms de classes\n", "class_names = np.load('class_names.npy')\n", "\n", "# Effectuer les prédictions\n", "predictions = model.predict(test_ds)\n", "\n", "# Trouver les classes prédites\n", "predicted_classes = np.argmax(predictions, axis=1)\n", "\n", "# Associer les indices aux noms de classes\n", "predicted_classes_names = [class_names[i] for i in predicted_classes]\n", "\n", "# Afficher les résultats\n", "print(\"Classes prédites :\", predicted_classes_names)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m43/43\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m39s\u001b[0m 916ms/step\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2024-09-30 19:27:17.615592: I tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Matrice de confusion\n", "y_pred_probs = model.predict(test_ds)\n", "y_pred_classes = np.argmax(y_pred_probs, axis=1)\n", "\n", "true_labels = []\n", "for images, labels in test_ds:\n", " true_labels.extend(labels.numpy())\n", "true_labels = np.array(true_labels)\n", "\n", "conf_matrix = confusion_matrix(true_labels, y_pred_classes)\n", "\n", "sns.heatmap(conf_matrix, annot=True, fmt='g', cmap='Blues')\n", "plt.xlabel('Prédictions')\n", "plt.ylabel('Vraies valeurs')\n", "plt.title('Matrice de confusion')\n", "plt.show();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Envoi des informations sur le serveur de tracking" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Le serveur de tracking MLflow est disponible : https://champi.heuzef.com\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Imports et paramétrage de MLflow\n", "import mlflow\n", "from mlflow.keras import MlflowCallback\n", "from mlflow import MlflowClient\n", "import setuptools\n", "import requests\n", "\n", "# Initialisation de l'URL\n", "mlflow_server_uri = \"https://champi.heuzef.com\"\n", "mlflow.set_tracking_uri(mlflow_server_uri)\n", "\n", "def is_mlflow_tracking_server_available(mlflow_server_uri):\n", " try:\n", " response = requests.get(mlflow_server_uri)\n", " if response.status_code == 200:\n", " return True\n", " else:\n", " return False\n", " except requests.exceptions.RequestException:\n", " return False\n", "\n", "if is_mlflow_tracking_server_available(mlflow_server_uri):\n", " print(\"Le serveur de tracking MLflow est disponible :\", mlflow_server_uri)\n", "else:\n", " print(\"Le serveur de tracking MLflow n'est pas disponible.\")\n", "\n", "requests.get(mlflow_server_uri)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2024/09/30 21:50:55 WARNING mlflow.keras.save: You are saving a Keras model without specifying model signature.\n", "/home/heuzef/GIT/jan24_cds_mushrooms/.venv/lib/python3.11/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils.\n", " warnings.warn(\"Setuptools is replacing distutils.\")\n" ] } ], "source": [ "mlflow.end_run()\n", "epochs = 4\n", "mlflow.set_experiment(\"champi\") # Le nom du projet\n", "run_name = \"heuzef_efficientnetb1_010\" # Le nom de la run\n", "\n", "mlflow.start_run(run_name=run_name)\n", "mlflow.log_param(\"epochs\", epochs)\n", "for epoch in range(epochs):\n", " mlflow.log_metric(\"accuracy\", acc[epoch], step=epoch)\n", " mlflow.log_metric(\"val_accuracy\", val_acc[epoch], step=epoch)\n", " mlflow.log_metric(\"loss\", loss[epoch], step=epoch)\n", " mlflow.log_metric(\"val_loss\", val_loss[epoch], step=epoch)\n", "mlflow.keras.log_model(model, artifact_path=run_name+\"_artifacts\")\n", "mlflow.end_run()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acc : [0.8457232117652893, 0.9367767572402954, 0.9521250128746033, 0.9607678651809692]\n", "val_acc : [0.856458306312561, 0.8615416884422302, 0.8584583401679993, 0.8645208477973938]\n", "loss : [0.4897499084472656, 0.2151074856519699, 0.1635088473558426, 0.1356484740972519]\n", "val_loss : [0.5011836886405945, 0.5270619988441467, 0.5628567934036255, 0.5321077108383179]\n", "epochs_range : range(0, 9)\n" ] } ], "source": [ "print(\"acc :\", acc)\n", "print(\"val_acc :\", val_acc)\n", "print(\"loss :\", loss)\n", "print(\"val_loss :\", val_loss)\n", "print(\"epochs_range :\", epochs_range)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.9286764705882353\n", "Precision: 0.9336224871829758\n", "Recall: 0.9286764705882353\n", "F1-score: 0.9290201971718653\n" ] } ], "source": [ "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n", "\n", "# Calcul des autres métriques sur le jeu de test\n", "accuracy = accuracy_score(true_labels, y_pred_classes)\n", "precision = precision_score(true_labels, y_pred_classes, average='weighted')\n", "recall = recall_score(true_labels, y_pred_classes, average='weighted')\n", "f1 = f1_score(true_labels, y_pred_classes, average='weighted')\n", "\n", "print(\"Accuracy:\", accuracy)\n", "print(\"Precision:\", precision)\n", "print(\"Recall:\", recall)\n", "print(\"F1-score:\", f1)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2024-09-30 21:42:12.968771: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-09-30 21:42:12.971925: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n", "2024-09-30 21:42:12.983989: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", "2024-09-30 21:42:13.003770: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", "2024-09-30 21:42:13.009367: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", "2024-09-30 21:42:13.023139: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2024-09-30 21:42:14.014947: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", "I0000 00:00:1727725335.634998 3390 config.cc:230] gRPC experiments enabled: call_status_override_on_cancellation, event_engine_dns, event_engine_listener, http2_stats_fix, monitoring_experiment, pick_first_new, trace_record_callops, work_serializer_clears_time_cache\n", "\n", "NOTE: Using experimental fast data loading logic. To disable, pass\n", " \"--load_fast=false\" and report issues on GitHub. More details:\n", " https://github.com/tensorflow/tensorboard/issues/4784\n", "\n", "Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all\n", "TensorBoard 2.17.0 at http://localhost:6006/ (Press CTRL+C to quit)\n", "^C\n" ] } ], "source": [ "!tensorboard --logdir logs/" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 2 }