The transpose of atrous_conv2d.

This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of atrous_conv2d rather than an actual deconvolution.

value A 4-D Tensor of type float. It needs to be in the default NHWC format. Its shape is [batch, in_height, in_width, in_channels].
filters A 4-D Tensor with the same type as value and shape [filter_height, filter_width, out_channels, in_channels]. filters' in_channels dimension must match that of value. Atrous convolution is equivalent to standard convolution with upsampled filters with effective height filter_height + (filter_height - 1) * (rate - 1) and effective width filter_width + (filter_width - 1) * (rate - 1), produced by inserting rate - 1 zeros along consecutive elements across the filters' spatial dimensions.
output_shape A 1-D Tensor of shape representing the output shape of the deconvolution op.
rate A positive int32. The stride with which we sam