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Add missing BN layer in ResNet-34 and remove bias in Conv2D

main
Aurélien Geron 2019-03-25 12:19:27 +08:00
parent 3313c21723
commit f0b432eb59
1 changed files with 4 additions and 2 deletions
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6
14_convolutional_neural_networks.ipynb
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@ -588,8 +588,8 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"DefaultConv2D = partial(keras.layers.Conv2D,\n", "DefaultConv2D = partial(keras.layers.Conv2D, kernel_size=3, strides=1,\n",
" kernel_size=3, strides=1, padding=\"SAME\")\n", " padding=\"SAME\", use_bias=False)\n",
"\n", "\n",
"class ResidualUnit(keras.layers.Layer):\n", "class ResidualUnit(keras.layers.Layer):\n",
" def __init__(self, filters, strides=1, activation=\"relu\", **kwargs):\n", " def __init__(self, filters, strides=1, activation=\"relu\", **kwargs):\n",
@ -626,6 +626,8 @@
"model = keras.models.Sequential()\n", "model = keras.models.Sequential()\n",
"model.add(DefaultConv2D(64, kernel_size=7, strides=2,\n", "model.add(DefaultConv2D(64, kernel_size=7, strides=2,\n",
" input_shape=[224, 224, 3]))\n", " input_shape=[224, 224, 3]))\n",
"model.add(keras.layers.BatchNormalization())\n",
"model.add(keras.layers.Activation(\"relu\"))\n",
"model.add(keras.layers.MaxPool2D(pool_size=3, strides=2, padding=\"SAME\"))\n", "model.add(keras.layers.MaxPool2D(pool_size=3, strides=2, padding=\"SAME\"))\n",
"prev_filters = 64\n", "prev_filters = 64\n",
"for filters in [64] * 3 + [128] * 4 + [256] * 6 + [512] * 3:\n", "for filters in [64] * 3 + [128] * 4 + [256] * 6 + [512] * 3:\n",