# -*- encoding: utf-8 -*-
# pylint: disable=E0203,E1101,C0111
"""
Runtime operator.
:githublink:`%|py|7`
"""
from collections import OrderedDict
import numpy
from ._op_helper import _get_typed_class_attribute
from ._op import OpRunUnaryNum, RuntimeTypeError
from ._new_ops import OperatorSchema
from .op_svm_regressor_ import ( # pylint: disable=E0611,E0401
RuntimeSVMRegressorFloat,
RuntimeSVMRegressorDouble,
)
[docs]class SVMRegressorCommon(OpRunUnaryNum):
[docs] def __init__(self, dtype, onnx_node, desc=None,
expected_attributes=None, **options):
OpRunUnaryNum.__init__(self, onnx_node, desc=desc,
expected_attributes=expected_attributes,
**options)
self._init(dtype=dtype)
[docs] def _get_typed_attributes(self, k):
return _get_typed_class_attribute(self, k, self.__class__.atts)
[docs] def _find_custom_operator_schema(self, op_name):
"""
Finds a custom operator defined by this runtime.
:githublink:`%|py|33`
"""
if op_name == "SVMRegressorDouble":
return SVMRegressorDoubleSchema()
raise RuntimeError( # pragma: no cover
"Unable to find a schema for operator '{}'.".format(op_name))
[docs] def _init(self, dtype):
if dtype == numpy.float32:
self.rt_ = RuntimeSVMRegressorFloat(50)
elif dtype == numpy.float64:
self.rt_ = RuntimeSVMRegressorDouble(50)
else:
raise RuntimeTypeError( # pragma: no cover
"Unsupported dtype={}.".format(dtype))
atts = [self._get_typed_attributes(k)
for k in SVMRegressor.atts]
self.rt_.init(*atts)
[docs] def _run(self, x): # pylint: disable=W0221
"""
This is a C++ implementation coming from
:epkg:`onnxruntime`.
`svm_regressor.cc
<https://github.com/microsoft/onnxruntime/blob/master/onnxruntime/core/providers/cpu/ml/svm_regressor.cc>`_.
See class :class:`RuntimeSVMRegressor
<mlprodict.onnxrt.ops_cpu.op_svm_regressor_.RuntimeSVMRegressor>`.
:githublink:`%|py|59`
"""
pred = self.rt_.compute(x)
if pred.shape[0] != x.shape[0]:
pred = pred.reshape(x.shape[0], pred.shape[0] // x.shape[0])
return (pred, )
[docs]class SVMRegressor(SVMRegressorCommon):
atts = OrderedDict([
('coefficients', numpy.empty(0, dtype=numpy.float32)),
('kernel_params', numpy.empty(0, dtype=numpy.float32)),
('kernel_type', b'NONE'),
('n_supports', 0),
('one_class', 0),
('post_transform', b'NONE'),
('rho', numpy.empty(0, dtype=numpy.float32)),
('support_vectors', numpy.empty(0, dtype=numpy.float32)),
])
[docs] def __init__(self, onnx_node, desc=None, **options):
SVMRegressorCommon.__init__(
self, numpy.float32, onnx_node, desc=desc,
expected_attributes=SVMRegressor.atts,
**options)
[docs]class SVMRegressorDouble(SVMRegressorCommon):
atts = OrderedDict([
('coefficients', numpy.empty(0, dtype=numpy.float64)),
('kernel_params', numpy.empty(0, dtype=numpy.float64)),
('kernel_type', b'NONE'),
('n_supports', 0),
('one_class', 0),
('post_transform', b'NONE'),
('rho', numpy.empty(0, dtype=numpy.float64)),
('support_vectors', numpy.empty(0, dtype=numpy.float64)),
])
[docs] def __init__(self, onnx_node, desc=None, **options):
SVMRegressorCommon.__init__(
self, numpy.float64, onnx_node, desc=desc,
expected_attributes=SVMRegressorDouble.atts,
**options)
[docs]class SVMRegressorDoubleSchema(OperatorSchema):
"""
Defines a schema for operators added in this package
such as :class:`SVMRegressorDouble <mlprodict.onnxrt.ops_cpu.op_svm_regressor.SVMRegressorDouble>`.
:githublink:`%|py|110`
"""
[docs] def __init__(self):
OperatorSchema.__init__(self, 'SVMRegressorDouble')
self.attributes = SVMRegressorDouble.atts
