forked from mindspore-Ecosystem/mindspore
!47437 ListExtend supports list, tuple and Tensor
Merge pull request !47437 from huangbingjian/list_extend
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6c1607c2ea
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@ -1,5 +1,5 @@
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/**
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* Copyright 2019-2022 Huawei Technologies Co., Ltd
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* Copyright 2019-2023 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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@ -157,16 +157,24 @@ FuncGraphPtr ListClear::GenerateFuncGraph(const abstract::AbstractBasePtrList &a
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}
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FuncGraphPtr ListExtend::GenerateFuncGraph(const abstract::AbstractBasePtrList &args_list) {
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abstract::CheckArgsSize("ListExtend", args_list, 2);
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constexpr size_t list_extend_args_size = 2;
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abstract::CheckArgsSize("ListExtend", args_list, list_extend_args_size);
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FuncGraphPtr ret = std::make_shared<FuncGraph>();
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ret->set_flag(FUNC_GRAPH_FLAG_CORE, true);
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ret->debug_info()->set_name("extend");
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constexpr size_t current_index = 0;
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constexpr size_t extend_index = 1;
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auto abs_current = args_list[current_index];
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auto abs_extend = args_list[extend_index];
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std::vector<AnfNodePtr> elems;
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elems.push_back(NewValueNode(prim::kPrimMakeList));
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AddNodeToElems(args_list[0], ret, &elems);
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AddNodeToElems(args_list[1], ret, &elems);
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auto abs_current_list = dyn_cast<abstract::AbstractList>(abs_current);
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MS_EXCEPTION_IF_NULL(abs_current_list);
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AddNodeToElems(abs_current_list, ret, &elems);
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AddNodeToElems(abs_extend, ret, &elems);
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auto out = ret->NewCNode(elems);
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ret->set_output(out);
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@ -174,14 +182,55 @@ FuncGraphPtr ListExtend::GenerateFuncGraph(const abstract::AbstractBasePtrList &
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}
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void ListExtend::AddNodeToElems(const AbstractBasePtr &arg, const FuncGraphPtr &ret, std::vector<AnfNodePtr> *elems) {
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abstract::AbstractListPtr arg_list = dyn_cast<abstract::AbstractList>(arg);
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MS_EXCEPTION_IF_NULL(arg_list);
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int64_t len = SizeToLong(arg_list->size());
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AnfNodePtr arg_node = ret->add_parameter();
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if (arg->isa<abstract::AbstractList>()) {
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auto arg_list = dyn_cast<abstract::AbstractList>(arg);
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if (arg_list->dynamic_len()) {
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MS_LOG(EXCEPTION) << "ListExtend does not support dynamic length list.";
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}
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int64_t len = SizeToLong(arg_list->size());
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for (int64_t i = 0; i < len; ++i) {
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auto value = ret->NewCNode({NewValueNode(prim::kPrimListGetItem), arg_node, NewValueNode(i)});
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elems->push_back(value);
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}
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return;
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}
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if (arg->isa<abstract::AbstractTuple>()) {
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auto arg_tuple = dyn_cast<abstract::AbstractTuple>(arg);
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if (arg_tuple->dynamic_len()) {
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MS_LOG(EXCEPTION) << "ListExtend does not support dynamic length tuple.";
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}
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int64_t len = SizeToLong(arg_tuple->size());
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for (int64_t i = 0; i < len; ++i) {
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auto value = ret->NewCNode({NewValueNode(prim::kPrimTupleGetItem), arg_node, NewValueNode(i)});
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elems->push_back(value);
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}
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return;
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}
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if (arg->isa<abstract::AbstractTensor>()) {
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auto abs_tensor = dyn_cast<abstract::AbstractTensor>(arg);
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auto shape_ptr = abs_tensor->BuildShape();
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MS_EXCEPTION_IF_NULL(shape_ptr);
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auto tensor_shape = shape_ptr->cast<abstract::ShapePtr>();
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MS_EXCEPTION_IF_NULL(tensor_shape);
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auto shape = tensor_shape->shape();
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if (shape.empty()) {
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MS_LOG(EXCEPTION) << "ListExtend does not support scalar tensor.";
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}
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if (shape[0] < 0) {
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MS_LOG(EXCEPTION) << "ListExtend does not support the tensor whose shapes has an uncertain 0th dimension.";
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}
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int64_t len = shape[0];
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std::string module_name = "mindspore.ops.composite.multitype_ops.getitem_impl";
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ValuePtr op = prim::GetPythonOps("getitem", module_name);
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for (int64_t i = 0; i < len; ++i) {
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auto value = ret->NewCNode({NewValueNode(op), arg_node, NewValueNode(i)});
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elems->push_back(value);
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}
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return;
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}
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MS_LOG(EXCEPTION) << "ListExtend supports list, tuple and Tensor, but got " << arg->ToString();
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}
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FuncGraphPtr ListReverse::GenerateFuncGraph(const abstract::AbstractBasePtrList &args_list) {
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@ -1,3 +1,17 @@
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# Copyright 2022-2023 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import pytest
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from mindspore.nn import Cell
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@ -0,0 +1,35 @@
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# Copyright 2023 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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""" test_list_extend """
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import numpy as np
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import mindspore as ms
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def test_list_extend_tensor():
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"""
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Feature: list extend.
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Description: support list extend.
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Expectation: No exception.
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"""
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@ms.jit
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def func():
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x = []
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y = ms.Tensor([[1, 2], [3, 4]])
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x.extend(y)
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return x
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out = func()
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assert np.all(out[0].asnumpy() == ms.Tensor([1, 2]).asnumpy())
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assert np.all(out[1].asnumpy() == ms.Tensor([3, 4]).asnumpy())
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@ -1,4 +1,4 @@
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# Copyright 2022 Huawei Technologies Co., Ltd
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# Copyright 2022-2023 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@ -91,3 +91,20 @@ def test_list_extend_4():
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return x
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out = list_net_4()
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assert np.all(out == ())
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def test_list_extend_tuple():
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"""
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Feature: list extend.
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Description: support list extend.
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Expectation: No exception.
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"""
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@jit
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def func():
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x = [1, 2, 3, 4]
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y = (5, 6, 7)
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x.extend(y)
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return x
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out = func()
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assert np.all(out == (1, 2, 3, 4, 5, 6, 7))
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