W3cubDocs

/TensorFlow 2.4

tf.nn.conv1d_transpose

The transpose of conv1d.

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)

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/nn/conv1d_transpose