tf.nn.conv3d_transpose
tf.nn.conv3d_transpose
tf.nn.conv3d_transpose
conv3d_transpose( value, filter, output_shape, strides, padding='SAME', data_format='NDHWC', name=None )
Defined in tensorflow/python/ops/nn_ops.py
.
See the guide: Neural Network > Convolution
The transpose of conv3d
.
This operation is sometimes called "deconvolution" after Deconvolutional Networks, but is actually the transpose (gradient) of conv3d
rather than an actual deconvolution.
Args:
-
value
: A 5-DTensor
of typefloat
and shape[batch, depth, height, width, in_channels]
. -
filter
: A 5-DTensor
with the same type asvalue
and shape[depth, height, width, output_channels, in_channels]
.filter
'sin_channels
dimension must match that ofvalue
. -
output_shape
: A 1-DTensor
representing the output shape of the deconvolution op. -
strides
: A list of ints. The stride of the sliding window for each dimension of the input tensor. -
padding
: A string, either'VALID'
or'SAME'
. The padding algorithm. See the comment here -
data_format
: A string, either'NDHWC'
or'NCDHW
' specifying the layout of the input and output tensors. Defaults to'NDHWC'
. -
name
: Optional name for the returned tensor.
Returns:
A Tensor
with the same type as value
.
Raises:
-
ValueError
: If input/output depth does not matchfilter
's shape, or if padding is other than'VALID'
or'SAME'
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/nn/conv3d_transpose