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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from torchinfo import summary\n",
"\n",
"from wearsed.models.baseline_conv.BaselineConv import BaselineConv"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"model = BaselineConv(in_channels=6)\n",
"batch_size = 64"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"summary(model, input_size=(batch_size, 6, 600))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\n==========================================================================================\\nLayer (type:depth-idx) Output Shape Param #\\n==========================================================================================\\nBaselineConv [64, 600] --\\n├─Sequential: 1-1 [64, 64, 600] --\\n│ └─Conv1d: 2-1 [64, 64, 600] 1,216\\n│ └─ReLU: 2-2 [64, 64, 600] --\\n│ └─Conv1d: 2-3 [64, 64, 600] 12,352\\n│ └─ReLU: 2-4 [64, 64, 600] --\\n├─MaxPool1d: 1-2 [64, 64, 300] --\\n├─Sequential: 1-3 [64, 128, 300] --\\n│ └─Conv1d: 2-5 [64, 128, 300] 24,704\\n│ └─ReLU: 2-6 [64, 128, 300] --\\n│ └─Conv1d: 2-7 [64, 128, 300] 49,280\\n│ └─ReLU: 2-8 [64, 128, 300] --\\n├─MaxPool1d: 1-4 [64, 128, 150] --\\n├─Sequential: 1-5 [64, 256, 150] --\\n│ └─Conv1d: 2-9 [64, 256, 150] 98,560\\n│ └─ReLU: 2-10 [64, 256, 150] --\\n│ └─Conv1d: 2-11 [64, 256, 150] 196,864\\n│ └─ReLU: 2-12 [64, 256, 150] --\\n├─MaxPool1d: 1-6 [64, 256, 75] --\\n├─Sequential: 1-7 [64, 512, 75] --\\n│ └─Conv1d: 2-13 [64, 512, 75] 393,728\\n│ └─ReLU: 2-14 [64, 512, 75] --\\n│ └─Conv1d: 2-15 [64, 512, 75] 786,944\\n│ └─ReLU: 2-16 [64, 512, 75] --\\n├─MaxPool1d: 1-8 [64, 512, 37] --\\n├─Sequential: 1-9 [64, 1024, 37] --\\n│ └─Conv1d: 2-17 [64, 1024, 37] 1,573,888\\n│ └─ReLU: 2-18 [64, 1024, 37] --\\n│ └─Conv1d: 2-19 [64, 1024, 37] 3,146,752\\n│ └─ReLU: 2-20 [64, 1024, 37] --\\n├─ConvTranspose1d: 1-10 [64, 512, 75] 1,049,088\\n├─Sequential: 1-11 [64, 512, 75] --\\n│ └─Conv1d: 2-21 [64, 512, 75] 1,573,376\\n│ └─ReLU: 2-22 [64, 512, 75] --\\n│ └─Conv1d: 2-23 [64, 512, 75] 786,944\\n│ └─ReLU: 2-24 [64, 512, 75] --\\n├─ConvTranspose1d: 1-12 [64, 256, 150] 262,400\\n├─Sequential: 1-13 [64, 256, 150] --\\n│ └─Conv1d: 2-25 [64, 256, 150] 393,472\\n│ └─ReLU: 2-26 [64, 256, 150] --\\n│ └─Conv1d: 2-27 [64, 256, 150] 196,864\\n│ └─ReLU: 2-28 [64, 256, 150] --\\n├─ConvTranspose1d: 1-14 [64, 128, 300] 65,664\\n├─Sequential: 1-15 [64, 128, 300] --\\n│ └─Conv1d: 2-29 [64, 128, 300] 98,432\\n│ └─ReLU: 2-30 [64, 128, 300] --\\n│ └─Conv1d: 2-31 [64, 128, 300] 49,280\\n│ └─ReLU: 2-32 [64, 128, 300] --\\n├─ConvTranspose1d: 1-16 [64, 64, 600] 16,448\\n├─Sequential: 1-17 [64, 64, 600] --\\n│ └─Conv1d: 2-33 [64, 64, 600] 24,640\\n│ └─ReLU: 2-34 [64, 64, 600] --\\n│ └─Conv1d: 2-35 [64, 64, 600] 12,352\\n│ └─ReLU: 2-36 [64, 64, 600] --\\n├─Conv1d: 1-18 [64, 1, 600] 65\\n==========================================================================================\\nTotal params: 10,813,313\\nTrainable params: 10,813,313\\nNon-trainable params: 0\\nTotal mult-adds (Units.GIGABYTES): 52.33\\n==========================================================================================\\nInput size (MB): 0.92\\nForward/backward pass size (MB): 432.32\\nParams size (MB): 43.25\\nEstimated Total Size (MB): 476.50\\n==========================================================================================\\n'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'''\n",
"==========================================================================================\n",
"Layer (type:depth-idx) Output Shape Param #\n",
"==========================================================================================\n",
"BaselineConv [64, 600] --\n",
"├─Sequential: 1-1 [64, 64, 600] --\n",
"│ └─Conv1d: 2-1 [64, 64, 600] 1,216\n",
"│ └─ReLU: 2-2 [64, 64, 600] --\n",
"│ └─Conv1d: 2-3 [64, 64, 600] 12,352\n",
"│ └─ReLU: 2-4 [64, 64, 600] --\n",
"├─MaxPool1d: 1-2 [64, 64, 300] --\n",
"├─Sequential: 1-3 [64, 128, 300] --\n",
"│ └─Conv1d: 2-5 [64, 128, 300] 24,704\n",
"│ └─ReLU: 2-6 [64, 128, 300] --\n",
"│ └─Conv1d: 2-7 [64, 128, 300] 49,280\n",
"│ └─ReLU: 2-8 [64, 128, 300] --\n",
"├─MaxPool1d: 1-4 [64, 128, 150] --\n",
"├─Sequential: 1-5 [64, 256, 150] --\n",
"│ └─Conv1d: 2-9 [64, 256, 150] 98,560\n",
"│ └─ReLU: 2-10 [64, 256, 150] --\n",
"│ └─Conv1d: 2-11 [64, 256, 150] 196,864\n",
"│ └─ReLU: 2-12 [64, 256, 150] --\n",
"├─MaxPool1d: 1-6 [64, 256, 75] --\n",
"├─Sequential: 1-7 [64, 512, 75] --\n",
"│ └─Conv1d: 2-13 [64, 512, 75] 393,728\n",
"│ └─ReLU: 2-14 [64, 512, 75] --\n",
"│ └─Conv1d: 2-15 [64, 512, 75] 786,944\n",
"│ └─ReLU: 2-16 [64, 512, 75] --\n",
"├─MaxPool1d: 1-8 [64, 512, 37] --\n",
"├─Sequential: 1-9 [64, 1024, 37] --\n",
"│ └─Conv1d: 2-17 [64, 1024, 37] 1,573,888\n",
"│ └─ReLU: 2-18 [64, 1024, 37] --\n",
"│ └─Conv1d: 2-19 [64, 1024, 37] 3,146,752\n",
"│ └─ReLU: 2-20 [64, 1024, 37] --\n",
"├─ConvTranspose1d: 1-10 [64, 512, 75] 1,049,088\n",
"├─Sequential: 1-11 [64, 512, 75] --\n",
"│ └─Conv1d: 2-21 [64, 512, 75] 1,573,376\n",
"│ └─ReLU: 2-22 [64, 512, 75] --\n",
"│ └─Conv1d: 2-23 [64, 512, 75] 786,944\n",
"│ └─ReLU: 2-24 [64, 512, 75] --\n",
"├─ConvTranspose1d: 1-12 [64, 256, 150] 262,400\n",
"├─Sequential: 1-13 [64, 256, 150] --\n",
"│ └─Conv1d: 2-25 [64, 256, 150] 393,472\n",
"│ └─ReLU: 2-26 [64, 256, 150] --\n",
"│ └─Conv1d: 2-27 [64, 256, 150] 196,864\n",
"│ └─ReLU: 2-28 [64, 256, 150] --\n",
"├─ConvTranspose1d: 1-14 [64, 128, 300] 65,664\n",
"├─Sequential: 1-15 [64, 128, 300] --\n",
"│ └─Conv1d: 2-29 [64, 128, 300] 98,432\n",
"│ └─ReLU: 2-30 [64, 128, 300] --\n",
"│ └─Conv1d: 2-31 [64, 128, 300] 49,280\n",
"│ └─ReLU: 2-32 [64, 128, 300] --\n",
"├─ConvTranspose1d: 1-16 [64, 64, 600] 16,448\n",
"├─Sequential: 1-17 [64, 64, 600] --\n",
"│ └─Conv1d: 2-33 [64, 64, 600] 24,640\n",
"│ └─ReLU: 2-34 [64, 64, 600] --\n",
"│ └─Conv1d: 2-35 [64, 64, 600] 12,352\n",
"│ └─ReLU: 2-36 [64, 64, 600] --\n",
"├─Conv1d: 1-18 [64, 1, 600] 65\n",
"==========================================================================================\n",
"Total params: 10,813,313\n",
"Trainable params: 10,813,313\n",
"Non-trainable params: 0\n",
"Total mult-adds (Units.GIGABYTES): 52.33\n",
"==========================================================================================\n",
"Input size (MB): 0.92\n",
"Forward/backward pass size (MB): 432.32\n",
"Params size (MB): 43.25\n",
"Estimated Total Size (MB): 476.50\n",
"==========================================================================================\n",
"'''"
]
}
],
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