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Signed-off-by: Josh Soref <2119212+jsoref@users.noreply.github.com>
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Josh Soref 2024-01-01 22:44:33 -05:00
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python/mlx/nn/layers/normalization.py
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@ -198,7 +198,7 @@ class BatchNorm(Module):
batch, ``C`` is the number of features or channels, and ``L`` is the batch, ``C`` is the number of features or channels, and ``L`` is the
sequence length. The output has the same shape as the input. For sequence length. The output has the same shape as the input. For
four-dimensional arrays, the shape is ``NHWC``, where ``H`` and ``W`` are four-dimensional arrays, the shape is ``NHWC``, where ``H`` and ``W`` are
the height and width respecitvely. the height and width respectively.
For more information on Batch Normalization, see the original paper `Batch For more information on Batch Normalization, see the original paper `Batch
Normalization: Accelerating Deep Network Training by Reducing Internal Normalization: Accelerating Deep Network Training by Reducing Internal