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Update README.md

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@@ -8,14 +8,16 @@ If you want to use them, do
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  ```
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  import torch
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- csr_kwargs = torch.load('FEAT_IDX.pt')
 
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- # The matrices are stored in space-efficient formats that're incompatible with torch's sparse csr tensor.
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- # Convert them back before constructing the matrix.
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- csr_kwargs['crow_indices'] = csr_kwargs['crow_indices'].int()
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- csr_kwargs['col_indices'] = csr_kwargs['crow_indices'].int()
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- csr_kwargs['values'] = csr_kwargs['values'].float()/255
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-
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- feat_acts = torch.sparse_csr_tensor(**csr_kwargs)
 
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  ```
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  ```
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  import torch
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+ def load_feat_acts(fname):
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+ csr_kwargs = torch.load(fname)
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+ # The matrices are stored in space-efficient formats that're incompatible with torch's sparse csr tensor.
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+ # Convert them back before constructing the matrix.
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+ csr_kwargs['crow_indices'] = csr_kwargs['crow_indices'].int()
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+ csr_kwargs['col_indices'] = csr_kwargs['crow_indices'].int()
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+ csr_kwargs['values'] = csr_kwargs['values'].float()/255
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+
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+ feat_acts = torch.sparse_csr_tensor(**csr_kwargs)
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+ return feat_acts
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  ```
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