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.

cluster.h 2.0 kB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758
  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 cluster.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_CLUSTER_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_CLUSTER_H_
  22. #include "graph/operator_reg.h"
  23. #include "graph/operator.h"
  24. namespace ge {
  25. /**
  26. * @brief Perform k-means clustering on a data matrix. \n
  27. * @par Inputs:
  28. * Three required inputs and one optional inputs, including:
  29. * @li x: A 2D tensor of data type float32.
  30. * @li y: A 2D tensor of data type float32.
  31. * @li sum_square_x: An optional 2D tensor of data type float32.
  32. * @li sum_square_y: A 2D tensor of data type float32. \n
  33. * @par Attributes:
  34. * use_actual_distance: Indicates whether to calculate the complete distance. \n
  35. * @par Outputs:
  36. * @li segment_sum: A tensor of data type float32.
  37. * @li segment_count: A tensor of data type float32.
  38. * @li k_mean_total_sum: A tensor of data type float32.
  39. */
  40. REG_OP(KMeansCentroids)
  41. .INPUT(x, TensorType({DT_FLOAT}))
  42. .INPUT(y, TensorType({DT_FLOAT}))
  43. .INPUT(sum_square_y, TensorType({DT_FLOAT}))
  44. .OPTIONAL_INPUT(sum_square_x, TensorType({DT_FLOAT}))
  45. .OUTPUT(segment_sum, TensorType({DT_FLOAT}))
  46. .OUTPUT(segment_count, TensorType({DT_FLOAT}))
  47. .OUTPUT(kmean_total_sum, TensorType({DT_FLOAT}))
  48. .ATTR(use_actual_distance, Bool, false)
  49. .OP_END_FACTORY_REG(KMeansCentroids)
  50. } // namespace ge
  51. #endif // OPS_BUILT_IN_OP_PROTO_INC_CLUSTER_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