The transpose of conv1d.
tf.nn.conv1d_transpose(
input, filters, output_shape, strides, padding='SAME',
data_format='NWC', dilations=None, name=None
)
This operation is sometimes called "deconvolution" after
(Zeiler et al., 2010), but is actually the transpose (gradient) of conv1d
rather than an actual deconvolution.
Args |
|---|
input
|
A 3-D Tensor of type float and shape
[batch, in_width, in_channels] for NWC data format or
[batch, in_channels, in_width] for NCW data format.
|
filters
|
A 3-D Tensor with the same type as input and shape
[filter_width, output_channels, in_channels]. filter's
in_channels dimension must match that of input.
|
output_shape
|
A 1-D Tensor, containing three elements, representing the
output shape of the deconvolution op.
|
strides
|
An int or list of ints that has length 1 or 3. The number of
entries by which the filter is moved right at each step.
|
padding
|
A string, either 'VALID' or 'SAME'. The padding algorithm.
See the "returns" section of tf.nn.convolution for details.
|
data_format
|
A string. 'NWC' and 'NCW' are supported.
|
dilations
|
An int or list of ints that has length 1 or 3 which
defaults to 1. The dilation factor for each dimension of input. If set to
k > 1, there will be k-1 skipped cells between each filter element on that
dimension. Dilations in the batch and depth dimensions must be 1.
|
name
|
Optional name for the returned tensor.
|
Returns |
|---|
A Tensor with the same type as input.
|
Raises |
|---|
ValueError
|
If input/output depth does not match filter's shape, if
output_shape is not at 3-element vector, if padding is other than
'VALID' or 'SAME', or if data_format is invalid.
|
References:
Deconvolutional Networks:
Zeiler et al., 2010
(pdf)
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