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deep_md.h 2.0 kB

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  1. /**
  2. * Copyright 2021 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. /*!
  17. * \file deep_md.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_DEEP_MD_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_DEEP_MD_H_
  22. #include "graph/operator_reg.h"
  23. namespace ge {
  24. /**
  25. * @brief Calculate ProdForceSeA. \n
  26. *
  27. * @par Inputs:
  28. * Five inputs, including:
  29. * @li net_deriv: A Tensor. Must be one of the following types: float16, float32, float64.
  30. * @li in_deriv: A Tensor. Must be one of the following types: float16, float32, float64.
  31. * @li nlist: A Tensor. dtype is int32.
  32. * @li natoms: A Tensor. dtype is int32. \n
  33. *
  34. * @par Outputs:
  35. * atom_force: A Tensor. Must be one of the following types: float16, float32, float64. \n
  36. *
  37. * @par Attributes:
  38. * Two attributes, including:
  39. * @li n_a_sel: A Scalar.
  40. * @li n_r_sel: A Scalar. \n
  41. *
  42. * @par Restrictions:
  43. * Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
  44. */
  45. REG_OP(ProdForceSeA)
  46. .INPUT(net_deriv, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
  47. .INPUT(in_deriv, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
  48. .INPUT(nlist, TensorType({DT_INT32}))
  49. .INPUT(natoms, TensorType({DT_INT32}))
  50. .OUTPUT(atom_force, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
  51. .REQUIRED_ATTR(n_a_sel, Int)
  52. .REQUIRED_ATTR(n_r_sel, Int)
  53. .OP_END_FACTORY_REG(ProdForceSeA)
  54. } // namespace ge
  55. #endif // OPS_BUILT_IN_OP_PROTO_INC_DEEP_MD_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