tf.raw_ops.Conv2DBackpropFilter
Computes the gradients of convolution with respect to the filter.
tf.raw_ops.Conv2DBackpropFilter(
input, filter_sizes, out_backprop, strides, padding, use_cudnn_on_gpu=True,
explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1], name=None
)
| Args | |
|---|---|
input |
A Tensor. Must be one of the following types: half, bfloat16, float32, float64. 4-D with shape [batch, in_height, in_width, in_channels]. |
filter_sizes |
A Tensor of type int32. An integer vector representing the tensor shape of filter, where filter is a 4-D [filter_height, filter_width, in_channels, out_channels] tensor. |
out_backprop |
A Tensor. Must have the same type as input. 4-D with shape [batch, out_height, out_width, out_channels]. Gradients w.r.t. the output of the convolution. |
strides |
A list of ints. The stride of the sliding window for each dimension of the input of the convolution. Must be in the same order as the dimension specified with format. |
padding |
A string from: "SAME", "VALID", "EXPLICIT". The type of padding algorithm to use. |
use_cudnn_on_gpu |
An optional bool. Defaults to True. |
explicit_paddings |
An optional list of ints. Defaults to []. If padding is "EXPLICIT", the list of explicit padding amounts. For the ith dimension, the amount of padding inserted before and after the dimension is explicit_paddings[2 * i] and explicit_paddings[2 * i + 1], respectively. If padding is not "EXPLICIT", explicit_paddings must be empty. |
data_format |
An optional string from: "NHWC", "NCHW". Defaults to "NHWC". Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: [batch, in_height, in_width, in_channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, in_channels, in_height, in_width]. |
dilations |
An optional list of ints. Defaults to [1, 1, 1, 1]. 1-D tensor of length 4. 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. The dimension order is determined by the value of data_format, see above for details. Dilations in the batch and depth dimensions must be 1. |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as input. |
© 2020 The TensorFlow Authors. All rights reserved.
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/raw_ops/Conv2DBackpropFilter