| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| */ |
| |
| /*! |
| * \file np_dediff1d_op.cc |
| * \brief CPU implementation of numpy-compatible ediff1d operator |
| */ |
| |
| #include "./np_ediff1d_op-inl.h" |
| |
| namespace mxnet { |
| namespace op { |
| |
| inline bool EDiff1DType(const nnvm::NodeAttrs& attrs, |
| std::vector<int>* in_attrs, |
| std::vector<int>* out_attrs) { |
| CHECK_GE(in_attrs->size(), 1U); |
| CHECK_LE(in_attrs->size(), 3U); |
| CHECK_EQ(out_attrs->size(), 1U); |
| TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0)); |
| |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| if (param.to_begin_arr_given && param.to_end_arr_given) { |
| TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1)); |
| TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(2)); |
| } else if (param.to_begin_arr_given || param.to_end_arr_given) { |
| TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1)); |
| } |
| |
| TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0)); |
| |
| return out_attrs->at(0) != -1 && in_attrs->at(0) != -1; |
| } |
| |
| inline TShape NumpyEDiff1DShapeImpl(std::vector<TShape>* in_attrs, |
| const bool to_begin_arr_given, |
| const bool to_end_arr_given, |
| dmlc::optional<double> to_begin_scalar, |
| dmlc::optional<double> to_end_scalar) { |
| size_t out = (in_attrs->at(0).Size() > 0) ? in_attrs->at(0).Size() - 1 : 0; |
| // case 1: when both `to_begin` and `to_end` are arrays |
| if (to_begin_arr_given && to_end_arr_given) { |
| out += in_attrs->at(1).Size() + in_attrs->at(2).Size(); |
| // case 2: only one of the parameters is an array |
| } else if (to_begin_arr_given || to_end_arr_given) { |
| out += in_attrs->at(1).Size(); |
| // if the other one is a scalar |
| if (to_begin_scalar.has_value() || to_end_scalar.has_value()) { |
| out += 1; |
| } |
| // case 3: neither of the parameters is an array |
| } else { |
| // case 3.1: both of the parameters are scalars |
| if (to_begin_scalar.has_value() && to_end_scalar.has_value()) { |
| out += 2; |
| // case 3.2: only one of the parameters is a scalar |
| } else if (to_begin_scalar.has_value() || to_end_scalar.has_value()) { |
| out += 1; |
| } |
| // case 3.3: they are both `None` -- skip |
| } |
| TShape oshape = TShape(1, out); |
| return oshape; |
| } |
| |
| inline bool EDiff1DShape(const nnvm::NodeAttrs& attrs, |
| std::vector<TShape>* in_attrs, |
| std::vector<TShape>* out_attrs) { |
| CHECK_GE(in_attrs->size(), 1U); |
| CHECK_LE(in_attrs->size(), 3U); |
| CHECK_EQ(out_attrs->size(), 1U); |
| if (!shape_is_known(in_attrs->at(0))) { |
| return false; |
| } |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| SHAPE_ASSIGN_CHECK(*out_attrs, |
| 0, |
| NumpyEDiff1DShapeImpl(in_attrs, |
| param.to_begin_arr_given, |
| param.to_end_arr_given, |
| param.to_begin_scalar, |
| param.to_end_scalar)); |
| return shape_is_known(out_attrs->at(0)); |
| } |
| |
| DMLC_REGISTER_PARAMETER(EDiff1DParam); |
| |
| NNVM_REGISTER_OP(_npi_ediff1d) |
| .set_attr_parser(ParamParser<EDiff1DParam>) |
| .set_num_inputs([](const nnvm::NodeAttrs& attrs) { |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| int num_inputs = 1; |
| if (param.to_begin_arr_given) |
| num_inputs += 1; |
| if (param.to_end_arr_given) |
| num_inputs += 1; |
| return num_inputs; |
| }) |
| .set_num_outputs(1) |
| .set_attr<nnvm::FListInputNames>( |
| "FListInputNames", |
| [](const NodeAttrs& attrs) { |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| int num_inputs = 1; |
| if (param.to_begin_arr_given) |
| num_inputs += 1; |
| if (param.to_end_arr_given) |
| num_inputs += 1; |
| if (num_inputs == 1) |
| return std::vector<std::string>{"input1"}; |
| if (num_inputs == 2) |
| return std::vector<std::string>{"input1", "input2"}; |
| return std::vector<std::string>{"input1", "input2", "input3"}; |
| }) |
| .set_attr<mxnet::FInferShape>("FInferShape", EDiff1DShape) |
| .set_attr<nnvm::FInferType>("FInferType", EDiff1DType) |
| .set_attr<FCompute>("FCompute<cpu>", EDiff1DForward<cpu>) |
| .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_npi_backward_ediff1d"}) |
| .set_attr<nnvm::FInplaceOption>("FInplaceOption", |
| [](const NodeAttrs& attrs) { |
| return std::vector<std::pair<int, int> >{{0, 0}}; |
| }) |
| .add_argument("input1", "NDArray-or-Symbol", "Source input") |
| .add_argument("input2", "NDArray-or-Symbol", "Source input") |
| .add_argument("input3", "NDArray-or-Symbol", "Source input") |
| .add_arguments(EDiff1DParam::__FIELDS__()); |
| |
| NNVM_REGISTER_OP(_npi_backward_ediff1d) |
| .set_attr_parser(ParamParser<EDiff1DParam>) |
| .set_num_inputs([](const nnvm::NodeAttrs& attrs) { |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| int num_inputs = 2; |
| if (param.to_begin_arr_given) |
| num_inputs += 1; |
| if (param.to_end_arr_given) |
| num_inputs += 1; |
| return num_inputs; |
| }) |
| .set_num_outputs([](const nnvm::NodeAttrs& attrs) { |
| const EDiff1DParam& param = nnvm::get<EDiff1DParam>(attrs.parsed); |
| int num_inputs = 1; |
| if (param.to_begin_arr_given) |
| num_inputs += 1; |
| if (param.to_end_arr_given) |
| num_inputs += 1; |
| return num_inputs; |
| }) |
| .set_attr<nnvm::TIsBackward>("TIsBackward", true) |
| .set_attr<mxnet::FCompute>("FCompute<cpu>", EDiff1DBackward<cpu>); |
| |
| } // namespace op |
| } // namespace mxnet |
