module onnxrt.ops_cpu.op_mul
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_mul
Runtime operator.
Classes#
class |
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Mul === Performs element-wise binary multiplication (with Numpy-style broadcasting support). This operator supports **multidirectional … |
Properties#
property |
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Returns the list of arguments as well as the list of parameters with the default values (close to the signature). … |
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Returns the list of modified parameters. |
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Returns the list of optional arguments. |
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Returns the list of optional arguments. |
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Returns all parameters in a dictionary. |
Methods#
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Documentation#
Runtime operator.
- class mlprodict.onnxrt.ops_cpu.op_mul.Mul(onnx_node, desc=None, **options)#
Bases:
OpRunBinaryNumpy
===
Performs element-wise binary multiplication (with Numpy-style broadcasting support).
This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
(Opset 14 change): Extend supported types to include uint8, int8, uint16, and int16.
Inputs
A (heterogeneous)T: First operand.
B (heterogeneous)T: Second operand.
Outputs
C (heterogeneous)T: Result, has same element type as two inputs
Type Constraints
T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to all numeric tensors.
Version
Onnx name: Mul
This version of the operator has been available since version 14.
Runtime implementation:
Mul
- __init__(onnx_node, desc=None, **options)#