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https://github.com/rasbt/LLMs-from-scratch.git
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add print statements for illustration purposes
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commit
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@ -538,7 +538,7 @@
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"id": "11190e7d-8c29-4115-824a-e03702f9dd54",
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"metadata": {},
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"source": [
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"## 4.3 Implementing a feed forward network and GELU activations"
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"## 4.3 Implementing a feed forward network with GELU activations"
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]
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},
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{
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@ -741,19 +741,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 38,
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"id": "05473938-799c-49fd-86d4-8ed65f94fee6",
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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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"tensor([[0.2427]], grad_fn=<AddmmBackward0>)"
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Before shortcut: tensor([[0.0950, 0.0634, 0.3361]], grad_fn=<MulBackward0>)\n",
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"After shortcut: tensor([[-0.9050, 1.0634, 2.3361]], grad_fn=<AddBackward0>)\n",
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"Final network output: tensor([[0.2427]], grad_fn=<AddmmBackward0>)\n"
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]
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}
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],
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"source": [
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@ -768,14 +767,17 @@
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" def forward(self, x):\n",
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" shortcut = x\n",
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" x = self.gelu(self.fc1(x))\n",
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" x = self.gelu(self.fc2(x)) + shortcut\n",
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" x = self.gelu(self.fc2(x))\n",
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" print(\"Before shortcut:\", x)\n",
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" x = x + shortcut\n",
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" print(\"After shortcut:\", x)\n",
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" x = self.fc3(x)\n",
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" return x\n",
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"\n",
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"torch.manual_seed(123)\n",
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"ex_short = ExampleWithShortcut()\n",
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"inputs = torch.tensor([[-1., 1., 2.]])\n",
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"print(ex_short(inputs))"
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"print(\"Final network output:\", ex_short(inputs))"
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]
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},
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{
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