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 Deconvolutional Networks, but is really 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 value and shape [filter_width, output_channels, in_channels]. filter's in_channels dimension must match that of value. |
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 value. |
| 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. |