tf.nn.conv_transpose

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The transpose of convolution.

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tf.compat.v1.nn.conv_transpose

tf.nn.conv_transpose(
    input, filters, output_shape, strides, padding='SAME',
    data_format=None, dilations=None, name=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
input	An N+2 dimensional Tensor of shape [batch_size] + input_spatial_shape + [in_channels] if data_format does not start with "NC" (default), or [batch_size, in_channels] + input_spatial_shape if data_format starts with "NC". It must be one of the following types: half, bfloat16, float32, float64.
filters	An N+2 dimensional Tensor with the same type as input and shape spatial_filter_shape + [in_channels, out_channels].
output_shape	A 1-D Tensor representing the output shape of the deconvolution op.
strides	An int or list of ints that has length 1, N or N+2. The stride of the sliding window for each dimension of input. If a single value is given it is replicated in the spatial dimensions. By default the N and C dimensions are set to 0. The dimension order is determined by the value of data_format, see below for details.
padding	A string, either 'VALID' or 'SAME'. The padding algorithm. See the "returns" section of tf.nn.convolution for details.
data_format	A string or None. Specifies whether the channel dimension of the input and output is the last dimension (default, or if data_format does not start with "NC"), or the second dimension (if data_format starts with "NC"). For N=1, the valid values are "NWC" (default) and "NCW". For N=2, the valid values are "NHWC" (default) and "NCHW". For N=3, the valid values are "NDHWC" (default) and "NCDHW".
dilations	An int or list of ints that has length 1, N or N+2, defaults to 1. The dilation factor for each dimension ofinput. If a single value is given it is replicated in the spatial dimensions. 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.
name	A name for the operation (optional). If not specified "conv_transpose" is used.

Returns
A Tensor with the same type as value.

References:

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