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Update 17_foundations.ipynb

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2020-06-03 22:06:17 +02:00
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@@ -1137,7 +1137,7 @@
"torch.einsum('bi,ij,bj->b', a, b, c)\n",
"```\n",
"\n",
"will return a vector of size `b` where the `k`-th coordinate is the sum of `a[k,i] b[i,j] c[k,j]`. This notation is particularly convenient when you have more dimensions because of batches. For example, if you have two batches of matrices and want compute the matrix product per batch, you would could this: \n",
"will return a vector of size `b` where the `k`-th coordinate is the sum of `a[k,i] b[i,j] c[k,j]`. This notation is particularly convenient when you have more dimensions because of batches. For example, if you have two batches of matrices and want to compute the matrix product per batch, you would could this: \n",
"\n",
"```python\n",
"torch.einsum('bik,bkj->bij', a, b)\n",