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|
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from PIL import Image\n",
"import torch\n",
"from importlib.util import find_spec\n",
"if find_spec(\"text_recognizer\") is None:\n",
" import sys\n",
" sys.path.append('..')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from text_recognizer.networks.residual_network import IdentityBlock, ResidualBlock, BasicBlock, BottleNeckBlock, ResidualLayer, ResidualNetwork"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"IdentityBlock(\n",
" (blocks): Identity()\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): Identity()\n",
")"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"IdentityBlock(32, 64)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"ResidualBlock(\n",
" (blocks): Identity()\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): Sequential(\n",
" (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
")"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ResidualBlock(32, 64)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"BasicBlock(\n",
" (blocks): Sequential(\n",
" (0): Sequential(\n",
" (0): Conv2dAuto(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (1): ReLU(inplace=True)\n",
" (2): Sequential(\n",
" (0): Conv2dAuto(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): Sequential(\n",
" (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
")\n"
]
}
],
"source": [
"dummy = torch.ones((1, 32, 224, 224))\n",
"\n",
"block = BasicBlock(32, 64)\n",
"block(dummy).shape\n",
"print(block)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"BottleNeckBlock(\n",
" (blocks): Sequential(\n",
" (0): Sequential(\n",
" (0): Conv2dAuto(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (1): ReLU(inplace=True)\n",
" (2): Sequential(\n",
" (0): Conv2dAuto(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (3): ReLU(inplace=True)\n",
" (4): Sequential(\n",
" (0): Conv2dAuto(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): Sequential(\n",
" (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
" (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
")\n"
]
}
],
"source": [
"dummy = torch.ones((1, 32, 10, 10))\n",
"\n",
"block = BottleNeckBlock(32, 64)\n",
"block(dummy).shape\n",
"print(block)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dummy = torch.ones((1, 64, 48, 48))\n",
"\n",
"layer = ResidualLayer(64, 128, block=BasicBlock, num_blocks=3)\n",
"layer(dummy).shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"blocks_sizes=[64, 128, 256, 512]\n",
"list(zip(blocks_sizes, blocks_sizes[1:]))"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [],
"source": [
"e = Encoder(depths=[2, 1], block_sizes= [96, 128])"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Encoder(\n",
" (gate): Sequential(\n",
" (0): Conv2d(1, 96, kernel_size=(3, 3), stride=(2, 2), padding=(3, 3), bias=False)\n",
" (1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" (2): ReLU(inplace=True)\n",
" (3): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n",
" )\n",
" (blocks): Sequential(\n",
" (0): ResidualLayer(\n",
" (blocks): Sequential(\n",
" (0): BasicBlock(\n",
" (blocks): Sequential(\n",
" (0): Sequential(\n",
" (0): Conv2dAuto(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (1): ReLU(inplace=True)\n",
" (2): Sequential(\n",
" (0): Conv2dAuto(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): None\n",
" )\n",
" (1): BasicBlock(\n",
" (blocks): Sequential(\n",
" (0): Sequential(\n",
" (0): Conv2dAuto(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (1): ReLU(inplace=True)\n",
" (2): Sequential(\n",
" (0): Conv2dAuto(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): None\n",
" )\n",
" )\n",
" )\n",
" (1): ResidualLayer(\n",
" (blocks): Sequential(\n",
" (0): BasicBlock(\n",
" (blocks): Sequential(\n",
" (0): Sequential(\n",
" (0): Conv2dAuto(96, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" (1): ReLU(inplace=True)\n",
" (2): Sequential(\n",
" (0): Conv2dAuto(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
" (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" (activation_fn): ReLU(inplace=True)\n",
" (shortcut): Sequential(\n",
" (0): Conv2d(96, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
" (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
" )\n",
" )\n",
" )\n",
" )\n",
" )\n",
")"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Encoder(**{\"depths\": [2, 1], \"block_sizes\": [96, 128]})"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"from text_recognizer.networks import WideResidualNetwork"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"wr = WideResidualNetwork(\n",
" in_channels= 1,\n",
" num_classes= 80,\n",
" depth= 16,\n",
" num_layers= 4,\n",
" width_factor= 2,\n",
" dropout_rate= 0.2,\n",
" activation= \"SELU\",\n",
" use_decoder= False,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"from torchsummary import summary"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"===============================================================================================\n",
"Layer (type:depth-idx) Output Shape Param #\n",
"===============================================================================================\n",
"├─Sequential: 1-1 [-1, 256, 4, 2] --\n",
"| └─Conv2d: 2-1 [-1, 16, 28, 14] 144\n",
"| └─Sequential: 2-2 [-1, 32, 28, 14] --\n",
"| | └─WideBlock: 3-1 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4-1 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-1 [-1, 32, 28, 14] 512\n",
"| | | └─Sequential: 4-2 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-2 [-1, 16, 28, 14] 32\n",
"| | | └─SELU: 4-3 [-1, 16, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-3 [-1, 16, 28, 14] --\n",
"| | | | └─Conv2d: 5-4 [-1, 32, 28, 14] 4,608\n",
"| | | | └─Dropout: 5-5 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-6 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-4 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-7 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-8 [-1, 32, 28, 14] 9,216\n",
"| | └─WideBlock: 3-2 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4-5 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-9 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-6 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-10 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-11 [-1, 32, 28, 14] 9,216\n",
"| | | | └─Dropout: 5-12 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-13 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-7 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-14 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-15 [-1, 32, 28, 14] 9,216\n",
"| └─Sequential: 2-3 [-1, 64, 14, 7] --\n",
"| | └─WideBlock: 3-3 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4-8 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-16 [-1, 64, 14, 7] 2,048\n",
"| | | └─Sequential: 4-9 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-17 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-10 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-18 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-19 [-1, 64, 28, 14] 18,432\n",
"| | | | └─Dropout: 5-20 [-1, 64, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-21 [-1, 64, 28, 14] 128\n",
"| | | └─SELU: 4-11 [-1, 64, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-22 [-1, 64, 28, 14] --\n",
"| | | | └─Conv2d: 5-23 [-1, 64, 14, 7] 36,864\n",
"| | └─WideBlock: 3-4 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4-12 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-24 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-13 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-25 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-26 [-1, 64, 14, 7] 36,864\n",
"| | | | └─Dropout: 5-27 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-28 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-14 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-29 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-30 [-1, 64, 14, 7] 36,864\n",
"| └─Sequential: 2-4 [-1, 128, 7, 4] --\n",
"| | └─WideBlock: 3-5 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4-15 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-31 [-1, 128, 7, 4] 8,192\n",
"| | | └─Sequential: 4-16 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-32 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-17 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-33 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-34 [-1, 128, 14, 7] 73,728\n",
"| | | | └─Dropout: 5-35 [-1, 128, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-36 [-1, 128, 14, 7] 256\n",
"| | | └─SELU: 4-18 [-1, 128, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-37 [-1, 128, 14, 7] --\n",
"| | | | └─Conv2d: 5-38 [-1, 128, 7, 4] 147,456\n",
"| | └─WideBlock: 3-6 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4-19 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-39 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-20 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-40 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-41 [-1, 128, 7, 4] 147,456\n",
"| | | | └─Dropout: 5-42 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-43 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-21 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-44 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-45 [-1, 128, 7, 4] 147,456\n",
"| └─Sequential: 2-5 [-1, 256, 4, 2] --\n",
"| | └─WideBlock: 3-7 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4-22 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-46 [-1, 256, 4, 2] 32,768\n",
"| | | └─Sequential: 4-23 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-47 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-24 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-48 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-49 [-1, 256, 7, 4] 294,912\n",
"| | | | └─Dropout: 5-50 [-1, 256, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-51 [-1, 256, 7, 4] 512\n",
"| | | └─SELU: 4-25 [-1, 256, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-52 [-1, 256, 7, 4] --\n",
"| | | | └─Conv2d: 5-53 [-1, 256, 4, 2] 589,824\n",
"| | └─WideBlock: 3-8 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4-26 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-54 [-1, 256, 4, 2] 512\n",
"| | | └─SELU: 4-27 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-55 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-56 [-1, 256, 4, 2] 589,824\n",
"| | | | └─Dropout: 5-57 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-58 [-1, 256, 4, 2] 512\n",
"| | | └─SELU: 4-28 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-59 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-60 [-1, 256, 4, 2] 589,824\n",
"===============================================================================================\n",
"Total params: 2,788,784\n",
"Trainable params: 2,788,784\n",
"Non-trainable params: 0\n",
"Total mult-adds (M): 84.83\n",
"===============================================================================================\n",
"Input size (MB): 0.00\n",
"Forward/backward pass size (MB): 2.26\n",
"Params size (MB): 10.64\n",
"Estimated Total Size (MB): 12.90\n",
"===============================================================================================\n"
]
},
{
"data": {
"text/plain": [
"===============================================================================================\n",
"Layer (type:depth-idx) Output Shape Param #\n",
"===============================================================================================\n",
"├─Sequential: 1-1 [-1, 256, 4, 2] --\n",
"| └─Conv2d: 2-1 [-1, 16, 28, 14] 144\n",
"| └─Sequential: 2-2 [-1, 32, 28, 14] --\n",
"| | └─WideBlock: 3-1 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4-1 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-1 [-1, 32, 28, 14] 512\n",
"| | | └─Sequential: 4-2 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-2 [-1, 16, 28, 14] 32\n",
"| | | └─SELU: 4-3 [-1, 16, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-3 [-1, 16, 28, 14] --\n",
"| | | | └─Conv2d: 5-4 [-1, 32, 28, 14] 4,608\n",
"| | | | └─Dropout: 5-5 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-6 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-4 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-7 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-8 [-1, 32, 28, 14] 9,216\n",
"| | └─WideBlock: 3-2 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4-5 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-9 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-6 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-10 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-11 [-1, 32, 28, 14] 9,216\n",
"| | | | └─Dropout: 5-12 [-1, 32, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-13 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-7 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-14 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-15 [-1, 32, 28, 14] 9,216\n",
"| └─Sequential: 2-3 [-1, 64, 14, 7] --\n",
"| | └─WideBlock: 3-3 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4-8 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-16 [-1, 64, 14, 7] 2,048\n",
"| | | └─Sequential: 4-9 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-17 [-1, 32, 28, 14] 64\n",
"| | | └─SELU: 4-10 [-1, 32, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-18 [-1, 32, 28, 14] --\n",
"| | | | └─Conv2d: 5-19 [-1, 64, 28, 14] 18,432\n",
"| | | | └─Dropout: 5-20 [-1, 64, 28, 14] --\n",
"| | | | └─BatchNorm2d: 5-21 [-1, 64, 28, 14] 128\n",
"| | | └─SELU: 4-11 [-1, 64, 28, 14] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-22 [-1, 64, 28, 14] --\n",
"| | | | └─Conv2d: 5-23 [-1, 64, 14, 7] 36,864\n",
"| | └─WideBlock: 3-4 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4-12 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-24 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-13 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-25 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-26 [-1, 64, 14, 7] 36,864\n",
"| | | | └─Dropout: 5-27 [-1, 64, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-28 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-14 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-29 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-30 [-1, 64, 14, 7] 36,864\n",
"| └─Sequential: 2-4 [-1, 128, 7, 4] --\n",
"| | └─WideBlock: 3-5 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4-15 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-31 [-1, 128, 7, 4] 8,192\n",
"| | | └─Sequential: 4-16 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-32 [-1, 64, 14, 7] 128\n",
"| | | └─SELU: 4-17 [-1, 64, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-33 [-1, 64, 14, 7] --\n",
"| | | | └─Conv2d: 5-34 [-1, 128, 14, 7] 73,728\n",
"| | | | └─Dropout: 5-35 [-1, 128, 14, 7] --\n",
"| | | | └─BatchNorm2d: 5-36 [-1, 128, 14, 7] 256\n",
"| | | └─SELU: 4-18 [-1, 128, 14, 7] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-37 [-1, 128, 14, 7] --\n",
"| | | | └─Conv2d: 5-38 [-1, 128, 7, 4] 147,456\n",
"| | └─WideBlock: 3-6 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4-19 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-39 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-20 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-40 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-41 [-1, 128, 7, 4] 147,456\n",
"| | | | └─Dropout: 5-42 [-1, 128, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-43 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-21 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-44 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-45 [-1, 128, 7, 4] 147,456\n",
"| └─Sequential: 2-5 [-1, 256, 4, 2] --\n",
"| | └─WideBlock: 3-7 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4-22 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-46 [-1, 256, 4, 2] 32,768\n",
"| | | └─Sequential: 4-23 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-47 [-1, 128, 7, 4] 256\n",
"| | | └─SELU: 4-24 [-1, 128, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-48 [-1, 128, 7, 4] --\n",
"| | | | └─Conv2d: 5-49 [-1, 256, 7, 4] 294,912\n",
"| | | | └─Dropout: 5-50 [-1, 256, 7, 4] --\n",
"| | | | └─BatchNorm2d: 5-51 [-1, 256, 7, 4] 512\n",
"| | | └─SELU: 4-25 [-1, 256, 7, 4] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-52 [-1, 256, 7, 4] --\n",
"| | | | └─Conv2d: 5-53 [-1, 256, 4, 2] 589,824\n",
"| | └─WideBlock: 3-8 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4-26 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-54 [-1, 256, 4, 2] 512\n",
"| | | └─SELU: 4-27 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-55 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-56 [-1, 256, 4, 2] 589,824\n",
"| | | | └─Dropout: 5-57 [-1, 256, 4, 2] --\n",
"| | | | └─BatchNorm2d: 5-58 [-1, 256, 4, 2] 512\n",
"| | | └─SELU: 4-28 [-1, 256, 4, 2] --\n",
"| | | └─Sequential: 4 [] --\n",
"| | | | └─SELU: 5-59 [-1, 256, 4, 2] --\n",
"| | | | └─Conv2d: 5-60 [-1, 256, 4, 2] 589,824\n",
"===============================================================================================\n",
"Total params: 2,788,784\n",
"Trainable params: 2,788,784\n",
"Non-trainable params: 0\n",
"Total mult-adds (M): 84.83\n",
"===============================================================================================\n",
"Input size (MB): 0.00\n",
"Forward/backward pass size (MB): 2.26\n",
"Params size (MB): 10.64\n",
"Estimated Total Size (MB): 12.90\n",
"==============================================================================================="
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"summary(wr, (1, 28, 14), device=\"cpu\", depth=10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"name": "python3"
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