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DepthwiseConv2dNativeBackpropInput

public final class DepthwiseConv2dNativeBackpropInput

Computes the gradients of depthwise convolution with respect to the input.

Nested Classes

class DepthwiseConv2dNativeBackpropInput.Options Optional attributes for DepthwiseConv2dNativeBackpropInput

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of the tensor.
static <T extends TNumber > DepthwiseConv2dNativeBackpropInput <T>
create ( Scope scope, Operand < TInt32 > inputSizes, Operand <T> filter, Operand <T> outBackprop, List<Long> strides, String padding, Options... options)
Factory method to create a class wrapping a new DepthwiseConv2dNativeBackpropInput operation.
static DepthwiseConv2dNativeBackpropInput.Options
dataFormat (String dataFormat)
static DepthwiseConv2dNativeBackpropInput.Options
dilations (List<Long> dilations)
static DepthwiseConv2dNativeBackpropInput.Options
explicitPaddings (List<Long> explicitPaddings)
Output <T>
output ()
4-D with shape according to `data_format`.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "DepthwiseConv2dNativeBackpropInput"

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static DepthwiseConv2dNativeBackpropInput <T> create ( Scope scope, Operand < TInt32 > inputSizes, Operand <T> filter, Operand <T> outBackprop, List<Long> strides, String padding, Options... options)

Factory method to create a class wrapping a new DepthwiseConv2dNativeBackpropInput operation.

Parameters
scope current scope
inputSizes 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 4-D with shape `[filter_height, filter_width, in_channels, depthwise_multiplier]`.
outBackprop 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 The stride of the sliding window for each dimension of the input of the convolution.
padding The type of padding algorithm to use.
options carries optional attributes values
Returns
  • a new instance of DepthwiseConv2dNativeBackpropInput

public static DepthwiseConv2dNativeBackpropInput.Options dataFormat (String dataFormat)

Parameters
dataFormat 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].

public static DepthwiseConv2dNativeBackpropInput.Options dilations (List<Long> dilations)

Parameters
dilations 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.

public static DepthwiseConv2dNativeBackpropInput.Options explicitPaddings (List<Long> explicitPaddings)

public Output <T> output ()

4-D with shape according to `data_format`. For example, if `data_format` is 'NHWC', output shape is `[batch, in_height, in_width, in_channels]`. Gradient w.r.t. the input of the convolution.