tf.compat.v1.nn.conv3d_transpose

The transpose of conv3d.

tf.compat.v1.nn.conv3d_transpose(
    value,
    filter=None,
    output_shape=None,
    strides=None,
    padding='SAME',
    data_format='NDHWC',
    name=None,
    input=None,
    filters=None,
    dilations=None
)

This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of conv3d rather than an actual deconvolution.

Args
`value`	A 5-D `Tensor` of type `float` and shape `[batch, depth, height, width, in_channels]`.
`filter`	A 5-D `Tensor` with the same type as `value` and shape `[depth, height, width, output_channels, in_channels]`. `filter`'s `in_channels` dimension must match that of `value`.
`output_shape`	A 1-D `Tensor` 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 "returns" section of `tf.nn.convolution` for details.
`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.
`input`	Alias of value.
`filters`	Alias of filter.
`dilations`	An int or list of `ints` that has length `1`, `3` or `5`, defaults to 1. The dilation factor for each dimension of`input`. If a single value is given it is replicated in the `D`, `H` and `W` dimension. By default the `N` and `C` dimensions are set to 1. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions if a 5-d tensor must be 1.

Returns
A `Tensor` with the same type as `value`.

Raises
`ValueError`	If input/output depth does not match `filter`'s shape, or if padding is other than `'VALID'` or `'SAME'`.

References
Deconvolutional Networks: Zeiler et al., 2010 (pdf)

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/compat/v1/nn/conv3d_transpose