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udlbook
2023-11-06 13:11:13 +00:00
parent 0c5aacbd8b
commit 34235a319c
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Notebooks/Chap10/10_2_Convolution_for_MNIST_1D.ipynb
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@@ -4,7 +4,7 @@
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyOgDisWDe/zHpfTGCH8AZ3i",
"authorship_tag": "ABX9TyN1v/yg9PtdSVOWlYJ7bgkz",
"include_colab_link": true
},
"kernelspec": {
@@ -128,11 +128,11 @@
"\n",
"\n",
"# TODO Create a model with the following layers\n",
"# 1. Convolutional layer, (input=length 40 and 1 channel, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels )\n",
"# 1. Convolutional layer, (input=length 40 and 1 channel, kernel size 3, stride 2, padding=\"valid\", 15 output channels )\n",
"# 2. ReLU\n",
"# 3. Convolutional layer, (input=length 19 and 15 channels, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels )\n",
"# 3. Convolutional layer, (input=length 19 and 15 channels, kernel size 3, stride 2, padding=\"valid\", 15 output channels )\n",
"# 4. ReLU\n",
"# 5. Convolutional layer, (input=length 9 and 15 channels, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels)\n",
"# 5. Convolutional layer, (input=length 9 and 15 channels, kernel size 3, stride 2, padding=\"valid\", 15 output channels)\n",
"# 6. ReLU\n",
"# 7. Flatten (converts 4x15) to length 60\n",
"# 8. Linear layer (input size = 60, output size = 10)\n",