tf.nn.conv_transpose
The transpose of convolution.
tf.nn.conv_transpose(
input, filters, output_shape, strides, padding='SAME', data_format=None,
dilations=None, name=None
)
This operation is sometimes called "deconvolution" after (Zeiler et al., 2010), but is really the transpose (gradient) of conv3d rather than an actual deconvolution.
| Args | |
|---|---|
input |
An N+2 dimensional Tensor of shape [batch_size] + input_spatial_shape + [in_channels] if data_format does not start with "NC" (default), or [batch_size, in_channels] + input_spatial_shape if data_format starts with "NC". It must be one of the following types: half, bfloat16, float32, float64. |
filters |
An N+2 dimensional Tensor with the same type as input and shape spatial_filter_shape + [in_channels, out_channels]. |
output_shape |
A 1-D Tensor representing the output shape of the deconvolution op. |
strides |
An int or list of ints that has length 1, N or N+2. The stride of the sliding window for each dimension of input. If a single value is given it is replicated in the spatial dimensions. By default the N and C dimensions are set to 0. The dimension order is determined by the value of data_format, see below for details. |
padding |
A string, either 'VALID' or 'SAME'. The padding algorithm. See the "returns" section of tf.nn.convolution for details. |
data_format |
A string or None. Specifies whether the channel dimension of the input and output is the last dimension (default, or if data_format does not start with "NC"), or the second dimension (if data_format starts with "NC"). For N=1, the valid values are "NWC" (default) and "NCW". For N=2, the valid values are "NHWC" (default) and "NCHW". For N=3, the valid values are "NDHWC" (default) and "NCDHW". |
dilations |
An int or list of ints that has length 1, N or N+2, defaults to 1. The dilation factor for each dimension ofinput. If a single value is given it is replicated in the spatial dimensions. By default the N and C dimensions are set to 1. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format, see above for details. |
name |
A name for the operation (optional). If not specified "conv_transpose" is used. |
| Returns | |
|---|---|
A Tensor with the same type as value. |
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/conv_transpose