fix comment

ssnl · ssnl · commit cd8f5624b1b2 · 2020-05-06T11:30:42.000-04:00
diff --git a/torch/nn/modules/conv.py b/torch/nn/modules/conv.py
@@ -41,6 +41,10 @@ def __init__(self, in_channels, out_channels, kernel_size, stride,
         self.output_padding = output_padding
         self.groups = groups
         self.padding_mode = padding_mode
+        # `_reversed_padding_repeated_twice` is the padding to be passed to
+        # `F.pad` if needed (e.g., for non-zero padding types that are
+        # implemented as two ops: padding + conv). `F.pad` accepts paddings in
+        # reverse order than the dimension.
         self._reversed_padding_repeated_twice = _reverse_repeat_tuple(self.padding, 2)
         if transposed:
             self.weight = Parameter(torch.Tensor(
diff --git a/torch/testing/_internal/common_nn.py b/torch/testing/_internal/common_nn.py
@@ -3252,7 +3252,7 @@ def fractional_max_pool3d_test(test_case):
         padding = tuple(range(1, d + 1))
         cpp_padding = '{' + ', '.join(map(str, padding)) + '}'
         input_size = (2, 2) + (4,) * d
-        output_size = (2, 3) + tuple(p + 1 for p in padding)  # simplified from `(3 + 2 * p - 3) // 2`
+        output_size = (2, 3) + tuple(p + 1 for p in padding)  # simplified from `(4 + 2 * p - 3) // 2 + 1`
         new_module_tests.append(
             dict(
                 module_name='Conv{}d'.format(d),
