The transpose of conv2d.

This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of conv2d rather than an actual deconvolution.

value A 4-D Tensor of type float and shape [batch, height, width, in_channels] for NHWC data format or [batch, in_channels, height, width] for NCHW data format.
filter A 4-D Tensor with the same type as value and shape [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 An int or list of ints that has length 1, 2 or 4. The stride of the sliding window for each dimension of input. If a single value is given it is replicated in the H and W dimension. 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 o