tf.nn.conv3d_backprop_filter_v2
tf.nn.conv3d_backprop_filter_v2
tf.nn.conv3d_backprop_filter_v2
conv3d_backprop_filter_v2( input, filter_sizes, out_backprop, strides, padding, data_format=None, 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.
Args:
-
input
: ATensor
. Must be one of the following types:float32
,float64
. Shape[batch, depth, rows, cols, in_channels]
. -
filter_sizes
: ATensor
of typeint32
. An integer vector representing the tensor shape offilter
, wherefilter
is a 5-D[filter_depth, filter_height, filter_width, in_channels, out_channels]
tensor. -
out_backprop
: ATensor
. Must have the same type asinput
. Backprop signal of shape[batch, out_depth, out_rows, out_cols, out_channels]
. -
strides
: A list ofints
that has length>= 5
. 1-D tensor of length 5. The stride of the sliding window for each dimension ofinput
. Must havestrides[0] = strides[4] = 1
. -
padding
: Astring
from:"SAME", "VALID"
. The type of padding algorithm to use. -
data_format
: An optionalstring
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]. -
name
: A name for the operation (optional).
Returns:
A Tensor
. Has the same type as input
.
© 2017 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