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Merge pull request #85 from ayasyrev/ayasyrev/issue78
docs yaresnet
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‎Nbs/04_YaResNet.ipynb

+35-2
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@@ -13,7 +13,16 @@
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The autoreload extension is already loaded. To reload it, use:\n",
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" %reload_ext autoreload\n"
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]
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}
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],
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"source": [
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"#hide\n",
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"%load_ext autoreload\n",
@@ -1001,13 +1010,27 @@
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"# YaResnet34, YaResnet50"
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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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"We has `Resnet34` and `Resnet50` like models predefined, we can impoer it as: \n",
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"`from model_constructor.yaresnet import YaResNet34, YaResNet50` \n",
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"But lets create it."
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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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"source": [
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"from model_constructor.yaresnet import YaResNet34, YaResNet50"
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"class YaResNet34(ModelConstructor):\n",
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" block: type[nn.Module] = YaResBlock\n",
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" expansion: int = 1\n",
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" layers: list[int] = [3, 4, 6, 3]\n",
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" act_fn: type[nn.Module] = nn.Mish"
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]
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},
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{
@@ -1037,6 +1060,16 @@
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"yaresnet34"
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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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"source": [
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"class YaResNet50(YaResNet34):\n",
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" expansion: int = 4"
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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,

‎Nbs/index.ipynb ‎Nbs/README.ipynb

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@@ -18,7 +18,8 @@
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"outputs": [],
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"source": [
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"#hide\n",
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"import torch"
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"import torch\n",
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"from torch import nn"
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]
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},
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{
@@ -1326,9 +1327,27 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"mc = ModelConstructor(name=\"YaResNet\")\n",
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"mc.block = YaResBlock"
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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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"Or in one line:"
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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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"source": [
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"mc = ModelConstructor(name=\"YaResNet\", block=YaResBlock)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
@@ -1352,15 +1371,15 @@
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" block='YaResBlock'\n",
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" conv_layer='ConvBnAct'\n",
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" block_sizes=[64, 128, 256, 512]\n",
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" layers=[3, 4, 6, 3]\n",
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" layers=[2, 2, 2, 2]\n",
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" norm='BatchNorm2d'\n",
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" act_fn='Mish'\n",
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" act_fn='ReLU'\n",
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" pool=\"AvgPool2d {'kernel_size': 2, 'ceil_mode': True}\"\n",
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" expansion=4\n",
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" expansion=1\n",
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" groups=1\n",
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" bn_1st=True\n",
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" zero_bn=True\n",
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" stem_sizes=[32, 64, 64]\n",
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" stem_sizes=[32, 32, 64]\n",
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" stem_pool=\"MaxPool2d {'kernel_size': 3, 'stride': 2, 'padding': 1}\"\n",
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" init_cnn='init_cnn'\n",
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" make_stem='make_stem'\n",
@@ -1372,7 +1391,6 @@
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],
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"source": [
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"#collapse_output\n",
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"mc.name = 'YaResNet'\n",
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"mc.print_cfg()"
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]
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},
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" (reduce): AvgPool2d(kernel_size=2, stride=2, padding=0)\n",
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" (convs): Sequential(\n",
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" (conv_0): ConvBnAct(\n",
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" (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\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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" (act_fn): ReLU(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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" (act_fn): Mish(inplace=True)\n",
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" )\n",
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" (conv_2): ConvBnAct(\n",
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" (conv): Conv2d(128, 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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" )\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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" (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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" (merge): ReLU(inplace=True)\n",
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")"
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]
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},
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"#collapse_output\n",
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"mc.body.l_1.bl_0"
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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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"Lets create `Resnet34` like model constructor:"
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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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"source": [
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"class YaResnet34(ModelConstructor):\n",
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" block: type[nn.Module] = YaResBlock\n",
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" layers: list[int] = [3, 4, 6, 3]"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"YaResnet34(\n",
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" in_chans=3\n",
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" num_classes=1000\n",
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" block='YaResBlock'\n",
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" conv_layer='ConvBnAct'\n",
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" block_sizes=[64, 128, 256, 512]\n",
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" layers=[3, 4, 6, 3]\n",
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" norm='BatchNorm2d'\n",
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" act_fn='ReLU'\n",
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" pool=\"AvgPool2d {'kernel_size': 2, 'ceil_mode': True}\"\n",
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" expansion=1\n",
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" groups=1\n",
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" bn_1st=True\n",
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" zero_bn=True\n",
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" stem_sizes=[32, 32, 64]\n",
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" stem_pool=\"MaxPool2d {'kernel_size': 3, 'stride': 2, 'padding': 1}\"\n",
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" init_cnn='init_cnn'\n",
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" make_stem='make_stem'\n",
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" make_layer='make_layer'\n",
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" make_body='make_body'\n",
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" make_head='make_head')\n"
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]
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}
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],
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"source": [
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"mc = YaResnet34()\n",
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"mc.print_cfg()"
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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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"And `Resnet50` like model can be inherited from `YaResnet34`:"
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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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"source": [
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"class YaResnet50(YaResnet34):\n",
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" expansion = 4"
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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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{
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"data": {
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"text/plain": [
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"YaResnet50\n",
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" in_chans: 3, num_classes: 1000\n",
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" expansion: 4, groups: 1, dw: False, div_groups: None\n",
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" act_fn: ReLU, sa: False, se: False\n",
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" stem sizes: [32, 32, 64], stride on 0\n",
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" body sizes [64, 128, 256, 512]\n",
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" layers: [3, 4, 6, 3]"
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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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"mc = YaResnet50()\n",
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"mc"
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]
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}
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],
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"metadata": {

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