115 lines
4.4 KiB
C++
115 lines
4.4 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.hpp"
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#include "util/all_close_f.hpp"
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#include "util/known_element_types.hpp"
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#include "util/ndarray.hpp"
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#include "util/test_control.hpp"
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#include "util/test_tools.hpp"
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NGRAPH_SUPPRESS_DEPRECATED_START
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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}, relu_2Dfprop)
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{
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auto shape_a = Shape{2, 5};
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auto A = make_shared<op::Parameter>(element::f32, shape_a);
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auto relu = make_shared<op::Relu>(A);
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auto shape_rt = Shape{2, 5};
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auto f = make_shared<Function>(relu, ParameterVector{A});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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auto a = backend->create_tensor(element::f32, shape_a);
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copy_data(a, vector<float>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5});
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auto result = backend->create_tensor(element::f32, shape_rt);
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vector<float> expected{1, 8, 0, 17, 0, 1, 8, 0, 17, 0};
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auto handle = backend->compile(f);
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handle->call_with_validate({result}, {a});
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EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected, MIN_FLOAT_TOLERANCE_BITS));
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}
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NGRAPH_TEST(${BACKEND_NAME}, relu_2Dfprop_i32)
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{
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auto shape_a = Shape{2, 5};
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auto A = make_shared<op::Parameter>(element::i32, shape_a);
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auto relu = make_shared<op::Relu>(A);
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auto shape_rt = Shape{2, 5};
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auto f = make_shared<Function>(relu, ParameterVector{A});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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auto a = backend->create_tensor(element::i32, shape_a);
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copy_data(a, vector<int32_t>{1, 8, -8, 17, -2, 1, 8, -8, 17, -1});
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auto result = backend->create_tensor(element::i32, shape_rt);
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vector<int32_t> expected{1, 8, 0, 17, 0, 1, 8, 0, 17, 0};
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auto handle = backend->compile(f);
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handle->call_with_validate({result}, {a});
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EXPECT_EQ(expected, read_vector<int32_t>(result));
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}
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NGRAPH_TEST(${BACKEND_NAME}, relu_4Dfprop)
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{
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auto shape_a = Shape{2, 2, 2, 2};
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auto A = make_shared<op::Parameter>(element::f32, shape_a);
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auto relu = make_shared<op::Relu>(A);
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auto shape_rt = Shape{2, 2, 2, 2};
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auto f = make_shared<Function>(relu, ParameterVector{A});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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auto a = backend->create_tensor(element::f32, shape_a);
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copy_data(a, vector<float>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1});
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auto result = backend->create_tensor(element::f32, shape_rt);
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vector<float> expected{1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1};
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auto handle = backend->compile(f);
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handle->call_with_validate({result}, {a});
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EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected, MIN_FLOAT_TOLERANCE_BITS));
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}
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NGRAPH_TEST(${BACKEND_NAME}, fuse_max_with_constant_zero_input_as_relu)
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{
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auto shape_a = Shape{2, 5};
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auto A = op::Constant::create(element::f32, shape_a, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
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auto B = make_shared<op::Parameter>(element::f32, shape_a);
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auto max = make_shared<op::Maximum>(A, B);
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auto shape_rt = Shape{2, 5};
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auto f = make_shared<Function>(max, ParameterVector{B});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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auto b = backend->create_tensor(element::f32, shape_a);
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copy_data(b, vector<float>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5});
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auto result = backend->create_tensor(element::f32, shape_rt);
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vector<float> expected{1, 8, 0, 17, 0, 1, 8, 0, 17, 0};
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auto handle = backend->compile(f);
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handle->call_with_validate({result}, {b});
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EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected, MIN_FLOAT_TOLERANCE_BITS));
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}
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