Update CM20315_Convolution_II.ipynb
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@@ -105,7 +105,7 @@
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"cell_type": "code",
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"cell_type": "code",
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"source": [
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"source": [
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"\n",
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"\n",
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"# TODO Create a model with the folowing layers\n",
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"# TODO Create a model with the following layers\n",
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"# 1. Convolutional layer, (input=length 40 and 1 channel, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels ) \n",
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"# 1. Convolutional layer, (input=length 40 and 1 channel, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels ) \n",
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"# 2. ReLU\n",
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"# 2. ReLU\n",
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"# 3. Convolutional layer, (input=length 19 and 15 channels, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels )\n",
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"# 3. Convolutional layer, (input=length 19 and 15 channels, kernel size 3x3, stride 2, padding=\"valid\", 15 output channels )\n",
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@@ -120,7 +120,7 @@
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"# https://pytorch.org/docs/1.13/generated/torch.nn.Linear.html?highlight=linear#torch.nn.Linear\n",
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"# https://pytorch.org/docs/1.13/generated/torch.nn.Linear.html?highlight=linear#torch.nn.Linear\n",
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"\n",
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"\n",
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"# Replace the following function which just runs a standard fully connected network\n",
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"# Replace the following function which just runs a standard fully connected network\n",
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"# The flatten at the beginning is becuase we are passing in the data in a slightly different format.\n",
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"# The flatten at the beginning is because we are passing in the data in a slightly different format.\n",
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"model = nn.Sequential(\n",
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"model = nn.Sequential(\n",
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"nn.Flatten(),\n",
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"nn.Flatten(),\n",
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"nn.Linear(40, 100),\n",
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"nn.Linear(40, 100),\n",
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