Computes the gradients of depthwise convolution with respect to the input.
tf.raw_ops.DepthwiseConv2dNativeBackpropInput( input_sizes, filter, out_backprop, strides, padding, explicit_paddings=[], data_format='NHWC', dilations=[1, 1, 1, 1], name=None )
Args | |
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input_sizes | A Tensor of type int32 . An integer vector representing the shape of input , based on data_format . For example, if data_format is 'NHWC' then input is a 4-D [batch, height, width, channels] tensor. |
filter | A Tensor . Must be one of the following types: half , bfloat16 , float32 , float64 . 4-D with shape [filter_height, filter_width, in_channels, depthwise_multiplier] . |
out_backprop | A Tensor . Must have the same type as filter . 4-D with shape based on data_format . For example, if data_format is 'NHWC' then out_backprop shape is [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. |
padding | A string from: "SAME", "VALID", "EXPLICIT" . The type of padding algorithm to use. |
explicit_paddings | An optional list of ints . Defaults to [] . |
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, height, width, channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, channels, height, 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 | |
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A Tensor . Has the same type as filter . |
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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/versions/r2.4/api_docs/python/tf/raw_ops/DepthwiseConv2dNativeBackpropInput