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TensorFlow 1 version
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View source on GitHub
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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
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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.
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filters
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An N+2 dimensional Tensor with the same type as input and
shape spatial_filter_shape + [in_channels, out_channels].
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output_shape
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A 1-D Tensor representing the output shape of the
deconvolution op.
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strides
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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.
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padding
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A string, either 'VALID' or 'SAME'. The padding algorithm. See
the "returns" section of tf.nn.convolution for details.
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data_format
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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".
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dilations
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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.
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name
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A name for the operation (optional). If not specified "conv_transpose" is used. |
Returns | |
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A Tensor with the same type as value.
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References:
Deconvolutional Networks: Zeiler et al., 2010 (pdf)