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Merge pull request #109 from ayasyrev/make_body
Make body
2 parents 6c8a6e9 + b3792cf commit e077402

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3 files changed

+353
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‎Nbs/00_ModelConstructor.ipynb

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@@ -311,7 +311,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`make_layer` need `layer_num` argument - number of layer."
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"`make_layer` need `layer_num` argument - number of layer. \n",
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"`make_layer` separated with `make_body` - it can be one piece."
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]
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},
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{
@@ -372,24 +373,174 @@
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"### Body"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`make_body` needs `cfg.make_layer` initialized. As default - `make_layer`. It can be changed."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Sequential(\n",
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" (l_0): Sequential(\n",
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" (bl_0): YaBasicBlock(\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" (bl_1): YaBasicBlock(\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" )\n",
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" (l_1): Sequential(\n",
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" (bl_0): YaBasicBlock(\n",
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" (reduce): ConvBnAct(\n",
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" (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
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" (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): ReLU(inplace=True)\n",
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" )\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (id_conv): ConvBnAct(\n",
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" (conv): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" (bl_1): YaBasicBlock(\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" )\n",
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" (l_2): Sequential(\n",
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" (bl_0): YaBasicBlock(\n",
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" (reduce): ConvBnAct(\n",
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" (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
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" (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): ReLU(inplace=True)\n",
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" )\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (id_conv): ConvBnAct(\n",
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" (conv): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" (bl_1): YaBasicBlock(\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" )\n",
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" (l_3): Sequential(\n",
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" (bl_0): YaBasicBlock(\n",
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" (reduce): ConvBnAct(\n",
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" (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
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" (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): ReLU(inplace=True)\n",
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" )\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (id_conv): ConvBnAct(\n",
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" (conv): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" (bl_1): YaBasicBlock(\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_1): ConvBnAct(\n",
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" (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
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" (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
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" )\n",
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" )\n",
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" (merge): Mish(inplace=True)\n",
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" )\n",
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" )\n",
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")"
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]
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},
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"execution_count": null,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# collapse_output\n",
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"# cfg.make_layer = make_layer\n",
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"# body = make_body(cfg)\n",
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"# body"
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"body = make_body(cfg)\n",
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"body"
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]
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},
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{
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"mc.body.l_0"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},

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