experiments/STT-tensorflow
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Fixes: GitHub #40103

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PiperOrigin-RevId: 315215042
Change-Id: Ib7f0e33b4844a2a5607300a6b7b22e9c85167ecb
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A. Unique TensorFlower 2020-06-07 22:34:42 -07:00 committed by TensorFlower Gardener
parent 7a239d4952
commit cef0c8cf71
1 changed files with 6 additions and 6 deletions
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12
tensorflow/python/ops/nn_ops.py
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@ -1962,9 +1962,9 @@ def conv1d_transpose(
input: A 3-D `Tensor` of type `float` and shape input: A 3-D `Tensor` of type `float` and shape
`[batch, in_width, in_channels]` for `NWC` data format or `[batch, in_width, in_channels]` for `NWC` data format or
`[batch, in_channels, in_width]` for `NCW` data format. `[batch, in_channels, in_width]` for `NCW` data format.
filters: A 3-D `Tensor` with the same type as `value` and shape filters: A 3-D `Tensor` with the same type as `input` and shape
`[filter_width, output_channels, in_channels]`. `filter`'s `[filter_width, output_channels, in_channels]`. `filter`'s
`in_channels` dimension must match that of `value`. `in_channels` dimension must match that of `input`.
output_shape: A 1-D `Tensor`, containing three elements, representing the output_shape: A 1-D `Tensor`, containing three elements, representing the
output shape of the deconvolution op. output shape of the deconvolution op.
strides: An int or list of `ints` that has length `1` or `3`. The number of strides: An int or list of `ints` that has length `1` or `3`. The number of
@ -1979,7 +1979,7 @@ def conv1d_transpose(
name: Optional name for the returned tensor. name: Optional name for the returned tensor.
Returns: Returns:
A `Tensor` with the same type as `value`. A `Tensor` with the same type as `input`.
Raises: Raises:
ValueError: If input/output depth does not match `filter`'s shape, if ValueError: If input/output depth does not match `filter`'s shape, if
@ -3118,9 +3118,9 @@ def conv3d_transpose_v2(input, # pylint: disable=redefined-builtin
input: A 5-D `Tensor` of type `float` and shape `[batch, depth, height, input: A 5-D `Tensor` of type `float` and shape `[batch, depth, height,
width, in_channels]` for `NDHWC` data format or `[batch, in_channels, width, in_channels]` for `NDHWC` data format or `[batch, in_channels,
depth, height, width]` for `NCDHW` data format. depth, height, width]` for `NCDHW` data format.
filters: A 5-D `Tensor` with the same type as `value` and shape `[depth, filters: A 5-D `Tensor` with the same type as `input` and shape `[depth,
height, width, output_channels, in_channels]`. `filter`'s `in_channels` height, width, output_channels, in_channels]`. `filter`'s `in_channels`
dimension must match that of `value`. dimension must match that of `input`.
output_shape: A 1-D `Tensor` representing the output shape of the output_shape: A 1-D `Tensor` representing the output shape of the
deconvolution op. deconvolution op.
strides: An int or list of `ints` that has length `1`, `3` or `5`. The strides: An int or list of `ints` that has length `1`, `3` or `5`. The
@ -3142,7 +3142,7 @@ def conv3d_transpose_v2(input, # pylint: disable=redefined-builtin
name: Optional name for the returned tensor. name: Optional name for the returned tensor.
Returns: Returns:
A `Tensor` with the same type as `value`. A `Tensor` with the same type as `input`.
References: References:
Deconvolutional Networks: Deconvolutional Networks: