module onnxrt.ops_cpu.op_prelu
#
Short summary#
module mlprodict.onnxrt.ops_cpu.op_prelu
Runtime operator.
Classes#
class |
truncated documentation |
---|---|
PRelu ===== PRelu takes input data (Tensor<T>) and slope tensor as input, and produces one output data (Tensor<T>) where … |
Properties#
property |
truncated documentation |
---|---|
|
Returns the list of arguments as well as the list of parameters with the default values (close to the signature). … |
|
Returns the list of modified parameters. |
|
Returns the list of optional arguments. |
|
Returns the list of optional arguments. |
|
Returns all parameters in a dictionary. |
Methods#
method |
truncated documentation |
---|---|
Documentation#
Runtime operator.
- class mlprodict.onnxrt.ops_cpu.op_prelu.PRelu(onnx_node, desc=None, **options)#
Bases:
OpRun
PRelu takes input data (Tensor<T>) and slope tensor as input, and produces one output data (Tensor<T>) where the function f(x) = slope * x for x < 0, f(x) = x for x >= 0., is applied to the data tensor elementwise.
History - Version 16 adds bfloat16 to the types allowed. This operator supports unidirectional broadcasting (tensor slope should be unidirectional broadcastable to input tensor X); for more details please check Broadcasting in ONNX.
Inputs
X (heterogeneous)T: Input tensor
slope (heterogeneous)T: Slope tensor. The shape of slope can be smaller then first input X; if so, its shape must be unidirectional broadcastable to X
Outputs
Y (heterogeneous)T: Output tensor (same size as X)
Type Constraints
T tensor(bfloat16), tensor(float16), tensor(float), tensor(double), tensor(uint32), tensor(uint64), tensor(int32), tensor(int64): Constrain input and output types to float/int tensors.
Version
Onnx name: PRelu
This version of the operator has been available since version 16.
Runtime implementation:
PRelu
- __init__(onnx_node, desc=None, **options)#
- _run(x, slope, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.
- to_python(inputs)#
Returns a python code equivalent to this operator.
- Parameters:
inputs – inputs name
- Returns:
imports, python code, both as strings