module `onnxrt.ops_cpu.op_bitshift`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_bitshift

Runtime operator.

Classes#

class	truncated documentation
`BitShift`	BitShift ======== Bitwise shift operator performs element-wise operation. For each input element, if the attribute “direction” …

Properties#

property	truncated documentation
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default_modified`	Returns the list of modified parameters.
`args_mandatory`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`	constructor

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_bitshift.BitShift(onnx_node, desc=None, **options)#

Bases: OpRunBinaryNumpy

Bitwise shift operator performs element-wise operation. For each input element, if the

attribute “direction” is “RIGHT”, this operator moves its binary representation toward the right side so that the input value is effectively decreased. If the attribute “direction” is “LEFT”, bits of binary representation moves toward the left side, which results the increase of its actual value. The input X is the tensor to be shifted and another input Y specifies the amounts of shifting. For example, if “direction” is “Right”, X is [1, 4], and S is [1, 1], the corresponding output Z would be [0, 2]. If “direction” is “LEFT” with X=[1, 2] and S=[1, 2], the corresponding output Y would be [2, 8].

Because this operator supports Numpy-style broadcasting, X’s and Y’s shapes are not necessarily identical.

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Attributes

direction (required): Direction of moving bits. It can be either “RIGHT” (for right shift) or “LEFT” (for left shift). default value cannot be automatically retrieved (STRING)

Inputs

X (heterogeneous)T: First operand, input to be shifted.
Y (heterogeneous)T: Second operand, amounts of shift.

Outputs

Z (heterogeneous)T: Output tensor

Type Constraints

T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64): Constrain input and output types to integer tensors.

Version

Onnx name: BitShift

This version of the operator has been available since version 11.

Runtime implementation: BitShift

constructor

__init__(onnx_node, desc=None, **options)#: constructor

module onnxrt.ops_cpu.op_bitshift#