tf.nn.conv3d_transpose

tf.nn.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-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 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 match filter's shape, or if padding is other than 'VALID' or 'SAME'.