Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

UniformQuantizedConvolution.Options

public static class UniformQuantizedConvolution.Options

Optional attributes for UniformQuantizedConvolution

Public Methods

UniformQuantizedConvolution.Options	batchGroupCount(Long batchGroupCount)
UniformQuantizedConvolution.Options	dimensionNumbers(String dimensionNumbers)
UniformQuantizedConvolution.Options	explicitPadding(List<Long> explicitPadding)
UniformQuantizedConvolution.Options	featureGroupCount(Long featureGroupCount)
UniformQuantizedConvolution.Options	lhsDilation(List<Long> lhsDilation)
UniformQuantizedConvolution.Options	lhsQuantizationAxis(Long lhsQuantizationAxis)
UniformQuantizedConvolution.Options	outputQuantizationAxis(Long outputQuantizationAxis)
UniformQuantizedConvolution.Options	rhsDilation(List<Long> rhsDilation)
UniformQuantizedConvolution.Options	rhsQuantizationAxis(Long rhsQuantizationAxis)
UniformQuantizedConvolution.Options	windowStrides(List<Long> windowStrides)

Inherited Methods

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

Public Methods

public UniformQuantizedConvolution.Options batchGroupCount (Long batchGroupCount)

Parameters

batchGroupCount	The number of batch groups. Used for grouped filters. Must be a divisor of `output_feature`.

public UniformQuantizedConvolution.Options dimensionNumbers (String dimensionNumbers)

Parameters

dimensionNumbers	Structure of dimension information for the convolution op. Must be an empty string (default) or a serialized string of `tensorflow.UniformQuantizedConvolutionDimensionNumbersAttr` proto. If empty string, the default is `("NCHW", "OIHW", "NCHW")` (for a 2D convolution).

public UniformQuantizedConvolution.Options explicitPadding (List<Long> explicitPadding)

Parameters

explicitPadding	If `padding` is `"EXPLICIT"`, must be set as a list indicating the explicit paddings at the start and end of each `lhs` spatial dimension. Otherwise, this must be empty. (If used,) Must be a list of size `2 * (number of lhs spatial dimensions)`, where `(explicit_padding[2 * i], explicit_padding[2 * i + 1])` indicates `(start_padding, end_padding)` of `spatial_dimensions[i]`.

public UniformQuantizedConvolution.Options featureGroupCount (Long featureGroupCount)

Parameters

featureGroupCount	The number of feature groups. Used for grouped convolutions. Must be a divisor of both `lhs_feature` and `output_feature`.

public UniformQuantizedConvolution.Options lhsDilation (List<Long> lhsDilation)

Parameters

lhsDilation	The dilation factor to apply in each spatial dimension of `lhs`. Must be an empty list (default) or a list of size (number of `lhs` spatial dimensions). If empty list, the dilation for each `lhs` spatial dimension is set to 1.

public UniformQuantizedConvolution.Options lhsQuantizationAxis (Long lhsQuantizationAxis)

Parameters

lhsQuantizationAxis	Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For the `lhs`, only per-tensor quantization is supported. Thus, this must be set to -1. Other values will raise error at OpKernel construction.

public UniformQuantizedConvolution.Options outputQuantizationAxis (Long outputQuantizationAxis)

Parameters

outputQuantizationAxis	Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For the `output`, only per-tensor quantization or per-channel quantization along `output_feature_dimension` is supported. Thus, this must be set to -1 or `dimension_numbers.output_feature_dimension`. Other values will raise error at OpKernel construction.

outputQuantizationAxis

Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For the `output`, only per-tensor quantization or per-channel quantization along `output_feature_dimension` is supported. Thus, this must be set to -1 or `dimension_numbers.output_feature_dimension`. Other values will raise error at OpKernel construction.

public UniformQuantizedConvolution.Options rhsDilation (List<Long> rhsDilation)

Parameters

rhsDilation	The dilation factor to apply in each spatial dimension of `rhs`. Must be an empty list (default) or a list of size (number of `rhs` spatial dimensions). If empty list, the dilation for each `rhs` spatial dimension is set to 1.

public UniformQuantizedConvolution.Options rhsQuantizationAxis (Long rhsQuantizationAxis)

Parameters

rhsQuantizationAxis	Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For the `rhs`, only per-tensor quantization or per-channel quantization along `kernel_output_feature_dimension` is supported. Thus, this must be set to -1 or `dimension_numbers.kernel_output_feature_dimension`. Other values will raise error at OpKernel construction.

rhsQuantizationAxis

Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For the `rhs`, only per-tensor quantization or per-channel quantization along `kernel_output_feature_dimension` is supported. Thus, this must be set to -1 or `dimension_numbers.kernel_output_feature_dimension`. Other values will raise error at OpKernel construction.

public UniformQuantizedConvolution.Options windowStrides (List<Long> windowStrides)

Parameters

windowStrides	The stride of the sliding window for each spatial dimension of `lhs`. Must be an empty list (default) or a list of size (number of spatial dimensions). If an empty list is provided, the stride for each spatial dimension is set to 1.