You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

logsoftmax.py 2.0 kB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849
  1. # Copyright 2020 Huawei Technologies Co., Ltd
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. # ===========================================================================
  15. """generate json desc for LogSoftmax"""
  16. from mindspore._extends.graph_kernel.model import model_builder as builder
  17. def expand_logsoftmax(expand_info):
  18. """LogSoftmax expander"""
  19. # get op info.
  20. input_desc = expand_info['input_desc'][0]
  21. attrs = expand_info['attr']
  22. axis = None
  23. for item in attrs:
  24. if 'axis' in item:
  25. axis = item['axis']
  26. graph_builder = builder.GraphBuilder()
  27. if isinstance(axis, int):
  28. axis = (axis,)
  29. # generate a graph.
  30. with graph_builder.graph_scope('main') as graph_scope:
  31. # create tensor input.
  32. input_x = graph_builder.tensor(input_desc['shape'], input_desc['data_type'], input_desc['format'])
  33. graph_scope.set_input(input_x)
  34. # cal logsoftmax.
  35. max_x = graph_builder.emit('ReduceMax', [input_x], attrs={'reduce_axis': axis, 'keep_dims': True})
  36. data_sub = graph_builder.emit('Sub', [input_x, max_x])
  37. data_exp = graph_builder.emit('Exp', [data_sub])
  38. data_expsum = graph_builder.emit('ReduceSum', [data_exp], attrs={'reduce_axis': axis, 'keep_dims': True})
  39. log_expsum = graph_builder.emit('Log', [data_expsum])
  40. result = graph_builder.emit('Sub', [data_sub, log_expsum])
  41. # set graph output.
  42. graph_scope.set_output(result)
  43. graph = graph_builder.get()[0]
  44. return graph