haojin2 commented on a change in pull request #16865: [numpy]add op insert URL: https://github.com/apache/incubator-mxnet/pull/16865#discussion_r354603595
########## File path: src/operator/numpy/np_insert_op.cc ########## @@ -0,0 +1,177 @@ +/* + * 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. + */ + +/*! + * Copyright (c) 2019 by Contributors + * \file np_insert_op.cc + * \brief CPU Implementation of numpy insert operations + */ + +#include <vector> +#include "./np_insert_op-inl.h" + +namespace mxnet { +namespace op { + +DMLC_REGISTER_PARAMETER(NumpyInsertParam); + +bool NumpyInsertType(const nnvm::NodeAttrs& attrs, + std::vector<int> *in_type, + std::vector<int> *out_type) { + const NumpyInsertParam& param = nnvm::get<NumpyInsertParam>(attrs.parsed); + int insize = (param.step.has_value() || param.int_ind.has_value()) ? 2 : 3; + CHECK_EQ(in_type->size(), insize); + CHECK_EQ(out_type->size(), 1U); + if (insize == 3) { + CHECK_NE((*in_type)[2], -1) << "Index type must be set for insert operator\n"; + CHECK(((*in_type)[2] == mshadow::DataType<int64_t>::kFlag) + || ((*in_type)[2] == mshadow::DataType<int32_t>::kFlag)) + << "Index type only support int32 or int64.\n"; + } + TYPE_ASSIGN_CHECK(*out_type, 0, (*in_type)[0]); + TYPE_ASSIGN_CHECK(*out_type, 0, (*in_type)[1]); + TYPE_ASSIGN_CHECK(*in_type, 0, (*out_type)[0]); + return (*in_type)[0] != -1; +} + +bool NumpyInsertShape(const nnvm::NodeAttrs& attrs, + mxnet::ShapeVector *in_shape, + mxnet::ShapeVector *out_shape) { + using namespace mshadow; + const NumpyInsertParam& param = nnvm::get<NumpyInsertParam>(attrs.parsed); + CHECK_EQ(in_shape->size(), + (param.step.has_value() || param.int_ind.has_value()) ? 2U : 3U); + mxnet::TShape &arrshape = (*in_shape)[insert_::kArr]; + mxnet::TShape &valshape = (*in_shape)[insert_::kValues]; + mxnet::TShape &objShape = (*in_shape)[insert_::kObj]; + if (in_shape->size() == 3U) { + CHECK_LE(objShape.ndim(), 1) + << "index array argument obj to insert must be one dimensional or scale.\n"; + } + + out_shape->clear(); + + int ndim = arrshape.ndim(); + int axis = param.axis.has_value() ? param.axis.value() : 0; + if (!(param.axis.has_value())) { + arrshape = Shape1(arrshape.Size()); + ndim = 1; + } else if (ndim == 0) { + CHECK_EQ(valshape.ndim(), 0) + << "'arr' is a 0-d array, 'values' can not assign to it. " + << "alueError: assignment to 0-d array."; + out_shape->push_back(valshape); + return shape_is_known(valshape); + } else { + CHECK(axis >= -1 * arrshape.ndim() && axis < arrshape.ndim()) + << "Axis should be in the range of [-r, r-1] where r is the rank of input tensor"; + axis += (axis < 0) ? arrshape.ndim() : 0; + } + + int seq_cnt = -1; + int N = arrshape[axis]; + if (in_shape->size() == 3U) { + seq_cnt = objShape.Size(); + } else if (param.step.has_value()) { + int step = param.step.value(); + int stop, start; + if (param.stop.has_value()) { + stop = param.stop.value(); + stop += (stop < 0) ? N : 0; + stop = (stop < 0) ? ((step < 0) ? -1 : 0) : stop; + stop = (stop >= N) ? ((step < 0) ? N - 1 : N) : stop; + } else { + stop = (step > 0) ? N : -1; + } + if (param.start.has_value()) { + start = param.start.value(); + start += (start < 0) ? N : 0; + start = (start < 0) ? ((step < 0) ? -1 : 0) : start; + start = (start >= N) ? ((step < 0) ? N - 1 : N) : start; + } else { + start = (step > 0) ? 0 : N - 1; + } + seq_cnt = 0; + if (step > 0 && stop >= start) { + seq_cnt = (stop - start + step - 1) / step; + } else if (step < 0 && stop <= start) { + seq_cnt = (stop - start + step + 1) / step; + } + } + + mxnet::TShape newshape(arrshape); + mxnet::TShape val_newshape(arrshape.ndim(), -1); + int numnew = 0; // amount of new column insert to 'arr' in 'axis' + // modify values's ndim to arr's ndim, for broadcast easily later + // e.g. value shape: (2,) arr shape: (3, 2) => value shape: (1, 2) + for (int i = valshape.ndim() - 1, j = arrshape.ndim() - 1; i >= 0 || j >= 0; --i, --j) { + if (i >= 0 && j >= 0) { + val_newshape[j] = valshape[i]; + } else if (i >= 0) { + CHECK_EQ(valshape[i], 1) << "index exceed limits."; + } else { + val_newshape[j] = 1; + } + } + valshape.assign(val_newshape.begin(), val_newshape.end()); + + if (param.int_ind.has_value() || + (in_shape->size() == 3U && objShape.ndim() == 0)) { Review comment: alignment ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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