tf.nn.depthwise_conv2d_native(
input,
filter,
strides,
padding,
data_format='NHWC',
dilations=[1, 1, 1, 1],
name=None
)
Defined in generated file: tensorflow/python/ops/gen_nn_ops.py
.
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:half
,bfloat16
,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].dilations
: An optional list ofints
. Defaults to[1, 1, 1, 1]
. 1-D tensor of length 4. The dilation factor for each dimension ofinput
. 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 ofdata_format
, see above for details. Dilations in the batch and depth dimensions must be 1.name
: A name for the operation (optional).
Returns:
A Tensor
. Has the same type as input
.