The transpose of conv2d
.
tf.nn.conv2d_transpose(
input, filters, output_shape, strides, padding='SAME',
data_format='NHWC', dilations=None, name=None
)
This operation is sometimes called "deconvolution" after
(Zeiler et al., 2010), but is really the transpose (gradient) of
atrous_conv2d
rather than an actual deconvolution.
Args |
input
|
A 4-D Tensor of type float and shape [batch, height, width,
in_channels] for NHWC data format or [batch, in_channels, height,
width] for NCHW data format.
|
filters
|
A 4-D Tensor with the same type as input and shape [height,
width, output_channels, in_channels] . filter 's in_channels dimension
must match that of input .
|
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 , 2 or 4 . The
stride of the sliding window for each dimension of input . If a single
value is given it is replicated in the H and W dimension. 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
|
Either the string "SAME"or "VALID"indicating the type of
padding algorithm to use, or a list indicating the explicit paddings at
the start and end of each dimension. When explicit padding is used and
data_format is "NHWC", this should be in the form [[0, 0], [pad_top,
pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used
and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],
[pad_top, pad_bottom], [pad_left, pad_right]].
</td>
</tr><tr>
<td> data_format</td>
<td>
A string. 'NHWC' and 'NCHW' are supported.
</td>
</tr><tr>
<td> dilations</td>
<td>
An int or list of intsthat has length 1, 2or 4,
defaults to 1. The dilation factor for each dimension of input. If a
single value is given it is replicated in the Hand Wdimension. By
default the Nand Cdimensions 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. Dilations in the batch and depth dimensions if a 4-d tensor
must be 1.
</td>
</tr><tr>
<td> 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, or if
padding is other than 'VALID' or 'SAME' .
|
References:
Deconvolutional Networks:
Zeiler et al., 2010
(pdf)