module `onnxrt.ops_cpu._op`#

Short summary#

module mlprodict.onnxrt.ops_cpu._op

Shortcut to ops_cpu.

Classes#

class	truncated documentation
`DefaultNone`	Default value for parameters when the parameter is not set but the operator has a default behaviour for it.
`OpRun`	Ancestor to all operators in this subfolder. The runtime for every node can checked into ONNX unit tests. …
`OpRunArg`	Ancestor to all unary operators in this subfolder and which produces position of extremas (ArgMax, …). Checks …
`OpRunBinary`	Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.
`OpRunBinaryComparison`	Ancestor to all binary operators in this subfolder comparing tensors.
`OpRunBinaryNum`	Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.
`OpRunBinaryNumpy`	Implements the inplaces logic. numpy_fct is a binary numpy function which takes two matrices and has a argument …
`OpRunClassifierProb`	Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.
`OpRunCustom`	Automates some methods for custom operators defined outside mlprodict.
`OpRunReduceNumpy`	Implements the reduce logic. It must have a parameter axes.
`OpRunUnary`	Ancestor to all unary operators in this subfolder. Checks that inputs type are the same.
`OpRunUnaryNum`	Ancestor to all unary and numerical operators in this subfolder. Checks that inputs type are the same.
`RuntimeTypeError`	Raised when a type of a variable is unexpected.

Functions#

function	truncated documentation
`_build_schemas`

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`	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_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_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.
`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.
`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.
`nb_classes`	Returns the number of expected classes.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__init__`
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`__str__`	usual
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`	Finds a custom operator defined by this runtime.
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_find_custom_operator_schema`
`_infer_shapes`	Should be overwritten.
`_infer_shapes`
`_infer_shapes`	Returns the same shape by default. We assume the operator returns the biggest shapes as the operator could …
`_infer_shapes`	Returns the same shape by default. We assume the operator returns the biggest shapes as the operator could …
`_infer_shapes`	Returns the same shape by default. We assume the operator returns the biggest shapes as the operator could …
`_infer_shapes`	Returns the same shape by default. We assume the operator returns the biggest shapes as the operator could …
`_infer_shapes`	Returns the same for the labels and the probabilities.
`_infer_shapes`	Should be overwritten.
`_infer_shapes`	Returns the same shape by default.
`_infer_shapes`	Returns the same shape by default.
`_infer_shapes`	Returns the same shape by default.
`_infer_sizes`	Should be overwritten.
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`	Should be overwritten.
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_types`	Should be overwritten.
`_infer_types`
`_infer_types`	Returns the boolean type.
`_infer_types`
`_infer_types`	Returns the boolean type.
`_infer_types`	Returns the boolean type.
`_infer_types`	Returns the type of the labels and the probabilities.
`_infer_types`	Should be overwritten.
`_infer_types`	Returns the same type by default.
`_infer_types`	Returns the same type by default.
`_infer_types`	Returns the same type by default.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run`	Should be overwritten.
`_run_no_checks_`
`_run_no_checks_`	Calls method `_run`.
`_run_no_checks_`	Calls method `_run`.
`_run_no_checks_`	Calls method `_run`.
`_run_no_checks_`	Calls method `_run`.
`_run_no_checks_`
`_run_no_checks_`
`_run_no_checks_`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`_to_python_numpy`
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`enable_inplace_compute`	Tells the node that one input can be overwritten.
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`
`infer_shapes`	Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.
`infer_shapes`
`infer_shapes`
`infer_shapes`
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_sizes`	Infer sizes required for computation. It works the same way as method run.
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`
`infer_types`	Infer types of the outputs given the types of the inputs. It works the same way as method run.
`infer_types`
`infer_types`
`infer_types`
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`need_context`	Tells the runtime if this node needs the context (all the results produced so far) as it may silently access …
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`run`	Calls method `_run`.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`switch_initializers_dtype`	Switches all initializers to `numpy.float64`. If model is None, a simple cast is done.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.
`to_python`	Returns a python code equivalent to this operator.

Documentation#

Shortcut to ops_cpu.

source on GitHub

class mlprodict.onnxrt.ops_cpu._op.DefaultNone#

Bases: object

Default value for parameters when the parameter is not set but the operator has a default behaviour for it.

source on GitHub

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

Bases: object

Ancestor to all operators in this subfolder. The runtime for every node can checked into ONNX unit tests.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

__str__()#

usual

source on GitHub

_find_custom_operator_schema(op_name)#

_infer_shapes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(*args, **kwargs)#

Should be overwritten.

source on GitHub

_run(*args, **kwargs)#

Should be overwritten.

source on GitHub

_to_python_numpy(inputs, numpy_name)#

property args_default#

Returns the list of arguments as well as the list of parameters with the default values (close to the signature).

source on GitHub

property args_default_modified#

Returns the list of modified parameters.

source on GitHub

property args_mandatory#

Returns the list of optional arguments.

source on GitHub

property args_optional#

Returns the list of optional arguments.

source on GitHub

property atts_value#: Returns all parameters in a dictionary.

enable_inplace_compute(index)#

Tells the node that one input can be overwritten.

Parameters: index – input index

source on GitHub

infer_shapes(*args, **kwargs)#

Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.

source on GitHub

infer_sizes(*args, **kwargs)#

Infer sizes required for computation. It works the same way as method run.

source on GitHub

infer_types(*args, **kwargs)#

Infer types of the outputs given the types of the inputs. It works the same way as method run.

source on GitHub

need_context()#

Tells the runtime if this node needs the context (all the results produced so far) as it may silently access one of them (operator Loop). The default answer is False.

source on GitHub

run(*args, **kwargs)#

Calls method _run.

source on GitHub

switch_initializers_dtype(dtype_in=<class 'numpy.float32'>, dtype_out=<class 'numpy.float64'>)#

Switches all initializers to numpy.float64. If model is None, a simple cast is done.

Parameters

dtype_in – previous type
dtype_out – next type

Returns

done operations

source on GitHub

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

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnary

Ancestor to all unary operators in this subfolder and which produces position of extremas (ArgMax, …). Checks that inputs type are the same. The class must have attributes axis, keepdim.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x)#

Returns the same shape by default.

source on GitHub

_infer_types(x)#

Returns the same type by default.

source on GitHub

_run_no_checks_(x)#

run(x)#

Calls method _run.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x, y)#

Returns the same shape by default. We assume the operator returns the biggest shapes as the operator could be using broacasting.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(x, y)#

Returns the boolean type.

source on GitHub

_run_no_checks_(x, y)#

Calls method _run.

source on GitHub

run(x, y)#

Calls method _run.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunBinary

Ancestor to all binary operators in this subfolder comparing tensors.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_types(x, y)#

Returns the boolean type.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunBinary

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_run_no_checks_(x, y)#

Calls method _run.

source on GitHub

run(x, y)#

Calls method _run.

source on GitHub

class mlprodict.onnxrt.ops_cpu._op.OpRunBinaryNumpy(numpy_fct, onnx_node, desc=None, expected_attributes=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunBinaryNum

Implements the inplaces logic. numpy_fct is a binary numpy function which takes two matrices and has a argument out for inplace operations.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_run(a, b)#

Should be overwritten.

source on GitHub

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

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnary

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x)#

Returns the same for the labels and the probabilities.

source on GitHub

_infer_types(x)#

Returns the type of the labels and the probabilities.

source on GitHub

_run_no_checks_(x)#

property nb_classes#

Returns the number of expected classes.

source on GitHub

run(x)#

Calls method _run.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Automates some methods for custom operators defined outside mlprodict.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

class OpRunCustomSchema(cls)#

Bases: mlprodict.onnxrt.ops_cpu._new_ops.OperatorSchema

Custom schema.

source on GitHub

__init__(cls)#

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_find_custom_operator_schema(op_name)#

Finds a custom operator defined by this runtime.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnaryNum

Implements the reduce logic. It must have a parameter axes.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Ancestor to all unary operators in this subfolder. Checks that inputs type are the same.

source on GitHub

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x)#

Returns the same shape by default.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(x)#

Returns the same type by default.

source on GitHub

infer_shapes(x)#

Infer shapes of the outputs given the shapes of the inputs. It works the same way as method run.

source on GitHub

infer_types(x)#

Infer types of the outputs given the types of the inputs. It works the same way as method run.

source on GitHub

run(x)#

Calls method _run.

source on GitHub

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

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnary

Ancestor to all unary and numerical operators in this subfolder. Checks that inputs type are the same.

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Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

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_run_no_checks_(x)#

run(x)#

Calls method _run.

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exception mlprodict.onnxrt.ops_cpu._op.RuntimeTypeError#

Bases: RuntimeError

Raised when a type of a variable is unexpected.

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mlprodict.onnxrt.ops_cpu._op._build_schemas()#

module onnxrt.ops_cpu._new_ops

module onnxrt.ops_cpu._op_classifier_string

module onnxrt.ops_cpu._op#

Short summary#

Classes#

Functions#

Properties#

Methods#

Documentation#

module `onnxrt.ops_cpu._op`#