fix bug
This commit is contained in:
@ -183,7 +183,7 @@
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 2,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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@ -208,29 +208,29 @@
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 3,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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{
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"name": "stdout",
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"ename": "RuntimeError",
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"output_type": "stream",
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"evalue": "dot: Expected 1-D argument self, but got 2-D",
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"text": [
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"traceback": [
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"\n",
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"matrix multiplication (dot) \n",
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"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
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"numpy: [[ 7 10]\n",
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"\u001b[0;32m<ipython-input-3-a29f9258176b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m'\\nmatrix multiplication (dot)'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m'\\nnumpy: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# [[7, 10], [15, 22]]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;34m'\\ntorch: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 30.0. Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m )\n",
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" [15 22]] \n",
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"\u001b[0;31mRuntimeError\u001b[0m: dot: Expected 1-D argument self, but got 2-D"
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"torch: 30.0\n"
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],
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]
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"output_type": "error"
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}
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}
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],
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],
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"source": [
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"source": [
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"# incorrect method\n",
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"# incorrect method\n",
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"data = np.array(data)\n",
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"data = np.array(data)\n",
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"tensor = torch.Tensor([1,2,3,4]\n",
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"tensor = torch.Tensor(data)\n",
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"print(\n",
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"print(\n",
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" '\\nmatrix multiplication (dot)',\n",
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" '\\nmatrix multiplication (dot)',\n",
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" '\\nnumpy: ', data.dot(data), # [[7, 10], [15, 22]]\n",
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" '\\nnumpy: ', data.dot(data), # [[7, 10], [15, 22]]\n",
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" '\\ntorch: ', torch.dot(tensor.dot(tensor) # 30.0. Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\n",
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" '\\ntorch: ', torch.dot(tensor.dot(tensor)) # NOT WORKING! Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\n",
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")"
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")"
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]
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]
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},
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},
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