56 lines
2.2 KiB
C++
56 lines
2.2 KiB
C++
//*****************************************************************************
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// Copyright 2017-2020 Intel Corporation
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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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#include "gtest/gtest.h"
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#include "ngraph/ngraph.hpp"
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#include "ngraph/runtime/tensor.hpp"
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#include "runtime/backend.hpp"
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#include "util/all_close_f.hpp"
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#include "util/test_control.hpp"
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#include "util/test_tools.hpp"
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using namespace std;
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using namespace ngraph;
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static string s_manifest = "${MANIFEST}";
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NGRAPH_TEST(${BACKEND_NAME}, reshape_v1)
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{
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auto arg = std::make_shared<op::Parameter>(element::i64, PartialShape::dynamic());
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auto pattern = make_shared<op::Parameter>(element::i64, PartialShape::dynamic(1));
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auto reshape_v1 = std::make_shared<op::v1::Reshape>(arg, pattern, false);
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auto f = std::make_shared<Function>(NodeVector{reshape_v1}, ParameterVector{arg, pattern});
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auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
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auto ex = backend->compile(f);
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auto arg_data = vector<int64_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
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auto pattern_data = vector<int64_t>{2, 2, 3};
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auto arg_tensor = backend->create_tensor(element::i64, Shape{arg_data.size()});
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auto pattern_tensor = backend->create_tensor(element::i64, Shape{pattern_data.size()});
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copy_data(arg_tensor, arg_data);
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copy_data(pattern_tensor, pattern_data);
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auto output = backend->create_dynamic_tensor(element::i64, PartialShape::dynamic());
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ex->call_with_validate({output}, {arg_tensor, pattern_tensor});
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ASSERT_EQ(output->get_element_type(), element::i64);
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EXPECT_EQ(read_vector<int64_t>(output),
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vector<int64_t>({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}));
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}
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