tf.nn.conv1d_transpose
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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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/nn/conv1d_transpose