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'` . |

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

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/nn/conv3d_transpose