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### `tf.nn.conv2d_transpose(value, filter, output_shape, strides, padding='SAME', name=None)` {#conv2d_transpose}
The transpose of `conv2d`.
This operation is sometimes called "deconvolution" after [Deconvolutional
Networks](http://www.matthewzeiler.com/pubs/cvpr2010/cvpr2010.pdf), but is
actually the transpose (gradient) of `conv2d` rather than an actual
deconvolution.
##### Args:
* <b>`value`</b>: A 4-D `Tensor` of type `float` and shape
`[batch, in_height, in_width, in_channels]`.
* <b>`filter`</b>: A 4-D `Tensor` with the same type as `value` and shape
`[filter_height, filter_width, output_channels, in_channels]`. `filter`'s
`in_channels` dimension must match that of `value`.
* <b>`output_shape`</b>: A 1-D `Tensor` representing the output shape of the
deconvolution op.
* <b>`strides`</b>: A list of ints. The stride of the sliding window for each
dimension of the input tensor.
* <b>`padding`</b>: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
See the [comment here](https://www.tensorflow.org/api_docs/python/nn.html#convolution)
* <b>`name`</b>: Optional name for the returned tensor.
##### Returns:
A `Tensor` with the same type as `value`.
##### Raises:
* <b>`ValueError`</b>: If input/output depth does not match `filter`'s shape, or if
padding is other than `'VALID'` or `'SAME'`.
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