tf.nn.conv3d_backprop_filter_v2( input, filter_sizes, out_backprop, strides, padding, data_format='NDHWC', dilations=[1, 1, 1, 1, 1], name=None )
Defined in tensorflow/python/ops/gen_nn_ops.py
.
See the guide: Neural Network > Convolution
Computes the gradients of 3-D convolution with respect to the filter.
input
: A Tensor
. Must be one of the following types: half
, bfloat16
, float32
, float64
. Shape [batch, depth, rows, cols, in_channels]
.filter_sizes
: A Tensor
of type int32
. An integer vector representing the tensor shape of filter
, where filter
is a 5-D [filter_depth, filter_height, filter_width, in_channels, out_channels]
tensor.out_backprop
: A Tensor
. Must have the same type as input
. Backprop signal of shape [batch, out_depth, out_rows, out_cols, out_channels]
.strides
: A list of ints
that has length >= 5
. 1-D tensor of length 5. The stride of the sliding window for each dimension of input
. Must have strides[0] = strides[4] = 1
.padding
: A string
from: "SAME", "VALID"
. The type of padding algorithm to use.data_format
: An optional string
from: "NDHWC", "NCDHW"
. Defaults to "NDHWC"
. The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].dilations
: An optional list of ints
. Defaults to [1, 1, 1, 1, 1]
. 1-D tensor of length 5. 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).A Tensor
. Has the same type as input
.
© 2018 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/api_docs/python/tf/nn/conv3d_backprop_filter_v2