Coverage for mlprodict/onnxrt/ops_cpu/op_conv_transpose.py: 94%

1# -*- encoding: utf-8 -*- 

2# pylint: disable=E0203,E1101,C0111 

3""" 

4@file 

5@brief Runtime operator. 

6""" 

7import numpy 

8from ._op import OpRun 

9from .op_conv_transpose_ import ( # pylint: disable=E0611,E0401 

10 ConvTransposeFloat, ConvTransposeDouble) 

11 

12 

13class ConvTranspose(OpRun): 

14 

15 atts = {'auto_pad': 'NOTSET', 'group': 1, 

16 'dilations': [], 

17 'kernel_shape': [], 

18 'pads': [], 

19 'strides': [], 

20 'output_padding': [], 

21 'output_shape': []} 

22 

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

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

25 expected_attributes=ConvTranspose.atts, 

26 **options) 

27 self._init() 

28 

29 def _init(self): 

30 self.rt32_ = ConvTransposeFloat() 

31 self.rt64_ = ConvTransposeDouble() 

32 for rt in [self.rt32_, self.rt64_]: 

33 rt.init(self.auto_pad, 

34 numpy.array(self.dilations, dtype=numpy.int64), 

35 self.group, 

36 numpy.array(self.kernel_shape, dtype=numpy.int64), 

37 numpy.array(self.pads, dtype=numpy.int64), 

38 numpy.array(self.strides, dtype=numpy.int64), 

39 numpy.array(self.output_padding, dtype=numpy.int64), 

40 numpy.array(self.output_shape, dtype=numpy.int64)) 

41 

42 def _run(self, X, W, B=None, attributes=None, verbose=0, fLOG=None): # pylint: disable=W0221 

43 if X.dtype == numpy.float32: 

44 return (self.rt32_.compute(X, W, B), ) 

45 return (self.rt64_.compute(X, W, B), )