module onnxrt.ops_cpu.op_reduce_prod
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_reduce_prod
Runtime operator.
Classes#
class |
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ReduceProd ========== Computes the product of the input tensor’s element along the provided axes. The resulting tensor … |
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ReduceProd ========== Computes the product of the input tensor’s element along the provided axes. The resulting tensor … |
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 arguments as well as the list of parameters with the default values (close to the signature). … |
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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 modified parameters. |
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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 the list of optional arguments. |
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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 the list of optional arguments. |
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Returns all parameters in a dictionary. |
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Returns all parameters in a dictionary. |
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Returns all parameters in a dictionary. |
Methods#
method |
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Documentation#
Runtime operator.
- mlprodict.onnxrt.ops_cpu.op_reduce_prod.ReduceProd#
alias of
ReduceProd_18
- class mlprodict.onnxrt.ops_cpu.op_reduce_prod.ReduceProd_1(onnx_node, desc=None, **options)#
Bases:
OpRunReduceNumpy
- __init__(onnx_node, desc=None, **options)#
- _run(data, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.
- class mlprodict.onnxrt.ops_cpu.op_reduce_prod.ReduceProd_18(onnx_node, desc=None, **options)#
Bases:
OpRun
ReduceProd#
Computes the product of the input tensor’s element along the provided axes. The resulting tensor has the same rank as the input if keepdims equals 1. If keepdims equals 0, then the resulting tensor has the reduced dimension pruned.
The above behavior is similar to numpy, with the exception that numpy defaults keepdims to False instead of True.
Attributes
keepdims: Keep the reduced dimension or not, default 1 means keep reduced dimension. Default value is
namekeepdimsi1typeINT
(INT)noop_with_empty_axes: Defines behavior if ‘axes’ is empty. Default behavior with ‘false’ is to reduce all axes. When axes is empty and this attribute is set to true, input tensor will not be reduced,and the output tensor would be equivalent to input tensor. Default value is
namenoopwithemptyaxesi0typeINT
(INT)
Inputs
Between 1 and 2 inputs.
data (heterogeneous)T: An input tensor.
axes (optional, heterogeneous)tensor(int64): Optional input list of integers, along which to reduce. The default is to reduce over all the dimensions of the input tensor if ‘noop_with_empty_axes’ is false, else act as an Identity op when ‘noop_with_empty_axes’ is true. Accepted range is [-r, r-1] where r = rank(data).
Outputs
reduced (heterogeneous)T: Reduced output tensor.
Type Constraints
T tensor(uint32), tensor(uint64), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to high-precision numeric tensors.
Version
Onnx name: ReduceProd
This version of the operator has been available since version 18.
Runtime implementation:
ReduceProd
- __init__(onnx_node, desc=None, **options)#
- _run(data, axes=None, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.