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.

stateless_random_ops.h 2.5 kB

5 years ago
5 years ago
5 years ago
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980
  1. /**
  2. * Copyright 2019-2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #ifndef GE_OP_STATELESS_RANDOM_OPS_H
  17. #define GE_OP_STATELESS_RANDOM_OPS_H
  18. #include "graph/operator.h"
  19. #include "graph/operator_reg.h"
  20. namespace ge {
  21. /**
  22. *@brief Draws samples from a multinomial distribution.
  23. *@par Inputs:
  24. include: \n
  25. *@li logits:2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :]\n
  26. *represents the unnormalized log probabilities for all classes.
  27. *@li num_samples:0-D. Number of independent samples to draw for each row slice.
  28. *@li seed:The seed to generate random.
  29. *@par Attributes:
  30. *output_dtype:Output data type.
  31. *@par Outputs:
  32. *y:Output random number.
  33. *@see StatelessMultinomial()
  34. *@par Third-party framework compatibility
  35. *compatible with StatelessMultinomial op of tensorflow
  36. */
  37. REG_OP(StatelessMultinomial)
  38. .INPUT(logits, TensorType({DT_FLOAT16,DT_FLOAT,DT_DOUBLE}))
  39. .INPUT(num_samples, TensorType({DT_INT32}))
  40. .INPUT(seed, TensorType({DT_INT32, DT_INT64}))
  41. .OUTPUT(y, TensorType({DT_INT32, DT_INT64}))
  42. .ATTR(output_dtype, Type, DT_INT64)
  43. .OP_END_FACTORY_REG(StatelessMultinomial)
  44. /**
  45. *@brief Outputs deterministic pseudorandom random integers from a uniform distribution.
  46. *@par Inputs:
  47. *@li shape: The shape of the output tensor.
  48. *@li seed: 2 seeds (shape [2]).
  49. *@li minval: Minimum value (inclusive, scalar).
  50. *@li maxval: Maximum value (exclusive, scalar).
  51. *@par Outputs:
  52. *y: Returns Random values with specified shape.
  53. *@par Third-party framework compatibility
  54. * Compatible with TensorFlow StatelessRandomUniformInt operator.
  55. */
  56. REG_OP(StatelessRandomUniformInt)
  57. .INPUT(shape, TensorType({DT_INT32, DT_INT64}))
  58. .INPUT(seed, TensorType({DT_INT32, DT_INT64}))
  59. .INPUT(minval, TensorType({DT_INT32, DT_INT64}))
  60. .INPUT(maxval, TensorType({DT_INT32, DT_INT64}))
  61. .OUTPUT(y, TensorType({DT_INT32, DT_INT64}))
  62. .OP_END_FACTORY_REG(StatelessRandomUniformInt)
  63. } // namespace ge
  64. #endif //GE_OP_STATELESS_RANDOM_OPS_H

图引擎模块(GE)是MindSpore的一个子模块,其代码由C++实现,位于前端模块ME和底层硬件之间,起到承接作用。图引擎模块以ME下发的图作为输入,然后进行一系列的深度图优化操作,最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点,做了特定的优化工作,以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时,GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成,详细的架构图如下所示