module onnxrt.ops_cpu.op_log_softmax
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_log_softmax
Runtime operator.
Classes#
class |
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LogSoftmax ========== The operator computes the log of softmax values for the given input: LogSoftmax(input, axis) = … |
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_log_softmax.LogSoftmax(onnx_node, desc=None, **options)#
Bases:
Softmax_13
The operator computes the log of softmax values for the given input:
LogSoftmax(input, axis) = Log(Softmax(input, axis=axis))
The “axis” attribute indicates the dimension along which LogSoftmax will be performed. The output tensor has the same shape and contains the LogSoftmax values of the corresponding input.
Attributes
axis:
Describes the dimension LogSoftmax will be performed on. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(input).
Default value is
nameaxisi-1typeINT
(INT)Inputs
input (heterogeneous)T: The input tensor of rank >= axis.
Outputs
output (heterogeneous)T: The output values with the same shape as the input tensor.
Type Constraints
T tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to float tensors.
Version
Onnx name: LogSoftmax
This version of the operator has been available since version 13.
Runtime implementation:
LogSoftmax
- __init__(onnx_node, desc=None, **options)#
- _run(X, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.
- _run_inplace(X)#
- to_python(inputs)#
Returns a python code equivalent to this operator.
- Parameters:
inputs – inputs name
- Returns:
imports, python code, both as strings