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boosted_trees_ops.h 1.9 kB

5 years ago
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  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_BOOSTED_TREES_OPS_H_
  17. #define GE_OP_BOOSTED_TREES_OPS_H_
  18. #include "graph/operator_reg.h"
  19. namespace ge {
  20. /**
  21. *@brief Bucketize each feature based on bucket boundaries.
  22. *@par Inputs:
  23. *The input float_values can be 1-D tensor, bucket_boundaries can be 1-D. Inputs include: \n
  24. * @li float_values: List of Rank 1 Tensor each containing float values for a single feature. \n
  25. * @li bucket_boundaries:List of Rank 1 Tensors each containing the bucket boundaries for a single. \n
  26. *@par Attributes:
  27. *@li num_features:number of features \n
  28. *@par Outputs:
  29. *@li y:List of Rank 1 Tensors each containing the bucketized values for a single feature. \n
  30. *@attention Constraints: \n
  31. *-The implementation for BoostedTreesBucketize on Ascend uses AI CPU, with bad performance. \n
  32. *@par Quantization supported or not
  33. *Not supported
  34. *@par Quantized inference supported or not
  35. *Supported
  36. *@par L2 convergence supported or not
  37. *@par Multiple batches supported or not
  38. */
  39. REG_OP(BoostedTreesBucketize)
  40. .DYNAMIC_INPUT(float_values, TensorType({DT_FLOAT}))
  41. .DYNAMIC_INPUT(bucket_boundaries, TensorType({DT_FLOAT}))
  42. .DYNAMIC_OUTPUT(y, TensorType({DT_INT32}))
  43. .REQUIRED_ATTR(num_features, Int)
  44. .OP_END_FACTORY_REG(BoostedTreesBucketize)
  45. } // namespace ge
  46. #endif // GE_OP_BOOSTED_TREES_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