tf.nn.conv2d_backprop_filter(input, filter_sizes, out_backprop, strides, padding, use_cudnn_on_gpu=None, data_format=None, name=None)
See the guide: Neural Network > Convolution
Computes the gradients of convolution with respect to the filter.
input
: A Tensor
. Must be one of the following types: half
, 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"
. The type of padding algorithm to use.use_cudnn_on_gpu
: An optional bool
. Defaults to True
.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].name
: A name for the operation (optional).A Tensor
. Has the same type as input
. 4-D with shape [filter_height, filter_width, in_channels, out_channels]
. Gradient w.r.t. the filter
input of the convolution.
Defined in tensorflow/python/ops/gen_nn_ops.py
.
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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/conv2d_backprop_filter