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@@ -280,6 +280,17 @@ class BatchNorm2d(_BatchNorm): |
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statistics on `(N, H, W)` slices, it's common terminology to call this |
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Spatial Batch Normalization. |
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.. note:: |
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The update formula for ``running_mean`` and ``running_var`` (taking ``running_mean`` as an example) is |
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.. math:: |
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\textrm{running_mean} = \textrm{momentum} \times \textrm{running_mean} + (1 - \textrm{momentum}) \times \textrm{batch_mean} |
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which could be defined differently in other frameworks. Most notably, ``momentum`` of 0.1 in PyTorch |
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is equivalent to ``mementum`` of 0.9 here. |
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Args: |
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num_features: usually :math:`C` from an input of shape |
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:math:`(N, C, H, W)` or the highest ranked dimension of an input |
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