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fix lab8 dropout+batchnormalization

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Aleksandra Jonas 2022-12-12 14:21:10 +01:00
parent f13785577d
commit e69318d649
1 changed files with 3 additions and 11 deletions
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14
sw_lab8.ipynb
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@ -3240,25 +3240,17 @@
"model_batch_drop = keras.models.Sequential([\n",
" keras.layers.Conv2D(filters=96, kernel_size=(11,11), strides=(4,4), activation='relu', input_shape=(227,227,3)),\n",
" keras.layers.BatchNormalization(),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.MaxPool2D(pool_size=(3,3), strides=(2,2)),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.Conv2D(filters=256, kernel_size=(5,5), strides=(1,1), activation='relu', padding=\"same\"),\n",
" keras.layers.BatchNormalization(),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.MaxPool2D(pool_size=(3,3), strides=(2,2)),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.Conv2D(filters=384, kernel_size=(3,3), strides=(1,1), activation='relu', padding=\"same\"),\n",
" keras.layers.BatchNormalization(),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.Conv2D(filters=384, kernel_size=(3,3), strides=(1,1), activation='relu', padding=\"same\"),\n",
" keras.layers.BatchNormalization(),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.Conv2D(filters=256, kernel_size=(3,3), strides=(1,1), activation='relu', padding=\"same\"),\n",
" keras.layers.BatchNormalization(),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.MaxPool2D(pool_size=(3,3), strides=(2,2)),\n",
" keras.layers.Dropout(.5),\n",
" keras.layers.Flatten(),\n",
" keras.layers.Dense(4096, activation='relu'),\n",
" keras.layers.Dropout(.5),\n",
@ -3623,7 +3615,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.4 64-bit",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
@ -3637,12 +3629,12 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.4"
"version": "3.10.7 (tags/v3.10.7:6cc6b13, Sep 5 2022, 14:08:36) [MSC v.1933 64 bit (AMD64)]"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "085c51388782ab7dcc7b32a500f9634129d1cddb82cd7a37058a5984251a0bc1"
"hash": "1b132c2ed43285dcf39f6d01712959169a14a721cf314fe69015adab49bb1fd1"
}
}
},