Coverage for mlprodict/onnxrt/ops_cpu/op_fft.py: 93%

1# -*- encoding: utf-8 -*- 

2# pylint: disable=E0203,E1101,C0111 

3""" 

4@file 

5@brief Runtime operator. 

6""" 

7import numpy 

8from numpy.fft import fft 

9from ._op import OpRun 

10from ._new_ops import OperatorSchema 

11 

12 

13class FFT(OpRun): 

14 

15 atts = {'axis': -1} 

16 

17 def __init__(self, onnx_node, desc=None, **options): 

18 OpRun.__init__(self, onnx_node, desc=desc, 

19 expected_attributes=FFT.atts, 

20 **options) 

21 

22 def _find_custom_operator_schema(self, op_name): 

23 if op_name == "FFT": 

24 return FFTSchema() 

25 raise RuntimeError( # pragma: no cover 

26 f"Unable to find a schema for operator '{op_name}'.") 

27 

28 def _run(self, a, fft_length=None, attributes=None, verbose=0, fLOG=None): # pylint: disable=W0221 

29 if fft_length is not None: 

30 fft_length = fft_length[0] 

31 y = fft(a, fft_length, axis=self.axis) 

32 else: 

33 y = fft(a, axis=self.axis) 

34 if a.dtype in (numpy.float32, numpy.complex64): 

35 return (y.astype(numpy.complex64), ) 

36 if a.dtype in (numpy.float64, numpy.complex128): 

37 return (y.astype(numpy.complex128), ) 

38 raise TypeError( # pragma: no cover 

39 f"Unexpected input type: {a.dtype!r}.") 

40 

41 def to_python(self, inputs): 

42 if len(inputs) == 1: 

43 return ('from numpy.fft import fft', 

44 f"return fft({inputs[0]}, axis={self.axis})") 

45 return ('from numpy.fft import fft', 

46 f"return fft({inputs[0]}, {inputs[1]}[0], axis={self.axis})") 

47 

48 

49class FFTSchema(OperatorSchema): 

50 """ 

51 Defines a schema for operators added in this package 

52 such as @see cl FFT. 

53 """ 

54 

55 def __init__(self): 

56 OperatorSchema.__init__(self, 'FFT') 

57 self.attributes = FFT.atts