module `onnxrt.ops_cpu.op_softmax`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_softmax

Runtime operator.

Classes#

class	truncated documentation
`_Softmax`
`Softmax_1`
`Softmax_13`	Softmax ======= The operator computes the normalized exponential values for the given input: Softmax(input, axis) = …
`Softmax_13`	Softmax ======= The operator computes the normalized exponential values for the given input: Softmax(input, axis) = …
`SoftmaxGrad_13`	SoftmaxGrad computes $dX = Y * ( dY - ReduceSum(Y * dY))$ . ONNX does not have a dot product, which can be …
`SoftmaxGrad_13`	SoftmaxGrad computes $dX = Y * ( dY - ReduceSum(Y * dY))$ . ONNX does not have a dot product, which can be …
`SoftmaxGradSchema`	Defines a schema for operators added in this package such as `SoftmaxGrad_13`.

Properties#

property	truncated documentation
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_run`
`_run`
`_run`
`_run`
`_run`
`_run`
`_run_inplace`
`_run_inplace`
`_run_inplace`
`_run_inplace`
`to_python`
`to_python`
`to_python`
`to_python`

Documentation#

Runtime operator.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_softmax.Softmax#: alias of Softmax_13

mlprodict.onnxrt.ops_cpu.op_softmax.SoftmaxGrad#: alias of SoftmaxGrad_13

class mlprodict.onnxrt.ops_cpu.op_softmax.SoftmaxGradSchema#

Bases: OperatorSchema

Defines a schema for operators added in this package such as SoftmaxGrad_13.

source on GitHub

__init__()#

class mlprodict.onnxrt.ops_cpu.op_softmax.SoftmaxGrad_13(onnx_node, desc=None, **options)#

Bases: OpRunBinaryNum

SoftmaxGrad computes $dX = Y * ( dY - ReduceSum(Y * dY))$ . ONNX does not have a dot product, which can be simulated as a pointwise-multiplication (“Mul”), followed by a “ReduceSum”. Unfortunately, the treatment of “axis” is different in “SoftmaxGrad” and “ReduceSum”. If axis=k for SoftmaxGrad, we need to specify [k, …, n-1] as the axes of reduction for “ReduceSum”, after accounting for negative-axis specification. An alternative solution would be to Flatten inputs to 2D and then reshape output back to original shape. Hopefully, many of these ops can be optimized away in the common-case of statically-known shapes.

source on GitHub

__init__(onnx_node, desc=None, **options)#

_find_custom_operator_schema(op_name)#

_run(grad, prob, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_softmax.Softmax_1(onnx_node, desc=None, **options)#

Bases: _Softmax

__init__(onnx_node, desc=None, **options)#

class mlprodict.onnxrt.ops_cpu.op_softmax.Softmax_13(onnx_node, desc=None, **options)#

Bases: _Softmax

Softmax#

The operator computes the normalized exponential values for the given input:

Softmax(input, axis) = Exp(input) / ReduceSum(Exp(input), axis=axis, keepdims=1)

The “axis” attribute indicates the dimension along which Softmax will be performed. The output tensor has the same shape and contains the Softmax values of the corresponding input.

Attributes

axis:

Describes the dimension Softmax 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: Softmax

This version of the operator has been available since version 13.

Runtime implementation: Softmax

__init__(onnx_node, desc=None, **options)#

class mlprodict.onnxrt.ops_cpu.op_softmax._Softmax(onnx_node, desc=None, expected_attributes=None, **options)#

Bases: OpRunUnaryNum

__init__(onnx_node, desc=None, expected_attributes=None, **options)#

_run(X, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

_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

source on GitHub

module onnxrt.ops_cpu.op_softmax#

Short summary#

Classes#

Properties#

Methods#

Documentation#

Softmax#

module `onnxrt.ops_cpu.op_softmax`#