[GitHub] piiswrong commented on a change in pull request #7938: instance norm and reflection padding

[GitBox <gi...@apache.org>]

piiswrong commented on a change in pull request #7938: instance norm and reflection padding
URL: https://github.com/apache/incubator-mxnet/pull/7938#discussion_r165162581
 
 

 ##########
 File path: python/mxnet/gluon/nn/conv_layers.py
 ##########
 @@ -1007,3 +1008,32 @@ def __init__(self, layout='NCDHW', **kwargs):
         assert layout == 'NCDHW', "Only supports NCDHW layout for now"
         super(GlobalAvgPool3D, self).__init__(
             (1, 1, 1), None, 0, True, True, 'avg', **kwargs)
+
+
+class ReflectionPad2D(HybridBlock):
+    """Pads the input tensor using the reflection of the input boundary.
+
+    Parameters
+    ----------
+        `padding` is a tuple of integer padding widths for each axis of the format
+``(before_1, after_1, ... , before_N, after_N)``. The `padding` should be of length ``2*N``
+where ``N`` is the number of dimensions of the array.
+
+    Shape:
+        - Input: :math:`(N, C, H_{in}, W_{in})`
+        - Output: :math:`(N, C, H_{out}, W_{out})` where
+          :math:`H_{out} = H_{in} + paddingTop + paddingBottom`
+          :math:`W_{out} = W_{in} + paddingLeft + paddingRight`
+
+    Examples
+    --------
+    >>> m = nn.ReflectionPad2D(3)
+    >>> input = mx.nd.random.normal(shape=(16, 3, 224, 224))
+    >>> output = m(input)
+    """
+    def __init__(self, padding=0, **kwargs):
+        super(ReflectionPad2D, self).__init__(**kwargs)
+        self._padding = padding
+
+    def hybrid_forward(self, F, x):
+        return F.pad(x, mode='reflect', padding=self._padding)
 
 Review comment:
   I think we should have this.

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