The transpose of atrous_conv2d.
tf.nn.atrous_conv2d_transpose(
value, filters, output_shape, rate, padding, name=None
)
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.
Args |
|---|
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 sample input values across
the height and width dimensions. Equivalently, the rate by which we
upsample the filter values by inserting zeros across the height and
width dimensions. In the literature, the same parameter is sometimes
called input stride or dilation.
|
padding
|
A string, either 'VALID' or 'SAME'. The padding algorithm.
|
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 filters' shape, or if
padding is other than 'VALID' or 'SAME', or if the rate is less
than one, or if the output_shape is not a tensor with 4 elements.
|
References:
Deconvolutional Networks:
Zeiler et al., 2010
(pdf)
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