tensorflow::ops::DepthwiseConv2dNative

#include <nn_ops.h>

Computes a 2-D depthwise convolution given 4-D input and filter tensors.

Summary

Given an input tensor of shape [batch, in_height, in_width, in_channels] and a filter / kernel tensor of shape [filter_height, filter_width, in_channels, channel_multiplier], containing in_channels convolutional filters of depth 1, depthwise_conv2d applies a different filter to each input channel (expanding from 1 channel to channel_multiplier channels for each), then concatenates the results together. Thus, the output has in_channels * channel_multiplier channels.

for k in 0..in_channels-1 for q in 0..channel_multiplier-1 output[b, i, j, k * channel_multiplier + q] = sum_{di, dj} input[b, strides[1] * i + di, strides[2] * j + dj, k] * filter[di, dj, k, q]

Must have strides[0] = strides[3] = 1. For the most common case of the same horizontal and vertices strides, strides = [1, stride, stride, 1].

Arguments:

• scope: A Scope object
• strides: 1-D of length 4. The stride of the sliding window for each dimension of input.
• padding: The type of padding algorithm to use.

Returns:

• Output: The output tensor.

Public attributes

::tensorflow::Output output

Public functions

 DepthwiseConv2dNative(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input filter,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const