module onnx_tools.exports.skl2onnx_helper#

Short summary#

module mlprodict.onnx_tools.exports.skl2onnx_helper

Helpers to run examples created with sklearn-onnx.

source on GitHub

Functions#

function

truncated documentation

_clean_initializer_name

_clean_operator_name

_clean_variable_name

_copy_inout

add_onnx_graph

Adds a whole ONNX graph to an existing one following skl2onnx API assuming this ONNX graph implements an …

get_tensor_elem_type

Returns the element type if that makes sense for this object.

get_tensor_shape

Returns the shape if that makes sense for this object.

Documentation#

Helpers to run examples created with sklearn-onnx.

source on GitHub

mlprodict.onnx_tools.exports.skl2onnx_helper._clean_initializer_name(name, scope)#
mlprodict.onnx_tools.exports.skl2onnx_helper._clean_operator_name(name, scope)#
mlprodict.onnx_tools.exports.skl2onnx_helper._clean_variable_name(name, scope)#
mlprodict.onnx_tools.exports.skl2onnx_helper._copy_inout(inout, scope, new_name)#
mlprodict.onnx_tools.exports.skl2onnx_helper.add_onnx_graph(scope, operator, container, onx)#

Adds a whole ONNX graph to an existing one following skl2onnx API assuming this ONNX graph implements an operator.

Parameters:

  • scope – scope (to get unique names)

  • operator – operator

  • container – container

  • onx – ONNX graph

source on GitHub

mlprodict.onnx_tools.exports.skl2onnx_helper.get_tensor_elem_type(obj)#

Returns the element type if that makes sense for this object.

source on GitHub

mlprodict.onnx_tools.exports.skl2onnx_helper.get_tensor_shape(obj)#

Returns the shape if that makes sense for this object.

source on GitHub