module onnxrt.ops_cpu.op_mean
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_mean
Runtime operator.
Classes#
class |
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Mean ==== Element-wise mean of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs … |
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#
method |
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Documentation#
Runtime operator.
- class mlprodict.onnxrt.ops_cpu.op_mean.Mean(onnx_node, desc=None, **options)#
Bases:
OpRun
Element-wise mean of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.
Inputs
Between 1 and 2147483647 inputs.
data_0 (variadic, heterogeneous)T: List of tensors for mean.
Outputs
mean (heterogeneous)T: Output tensor.
Type Constraints
T tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to float tensors.
Version
Onnx name: Mean
This version of the operator has been available since version 13.
Runtime implementation:
Mean
- __init__(onnx_node, desc=None, **options)#
- _run(*args, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.
- _run_inplace(*args)#