tf.nn.depthwise_conv2d_native
tf.nn.depthwise_conv2d_native
tf.nn.depthwise_conv2d_native
depthwise_conv2d_native( input, filter, strides, padding, data_format=None, name=None )
Defined in tensorflow/python/ops/gen_nn_ops.py
.
See the guide: Neural Network > Convolution
Computes a 2-D depthwise convolution given 4-D input
and filter
tensors.
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]
.
Args:
-
input
: ATensor
. Must be one of the following types:float32
,float64
. -
filter
: ATensor
. Must have the same type asinput
. -
strides
: A list ofints
. 1-D of length 4. The stride of the sliding window for each dimension ofinput
. -
padding
: Astring
from:"SAME", "VALID"
. The type of padding algorithm to use. -
data_format
: An optionalstring
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]. -
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/depthwise_conv2d_native