Commit 32ca10d7 authored by Jayaram Bobba's avatar Jayaram Bobba Committed by Scott Cyphers

Move codegen tests to a separate module and add selectively (#2559)

parent 56772c9e
......@@ -82,6 +82,9 @@ endif()
if (NGRAPH_CPU_ENABLE)
list(APPEND SRC core_fusion.cpp builder_quantization.cpp)
list(APPEND SRC backend_performance.cpp cpu_fusion.cpp cpu_test.cpp cpu_debugger.cpp)
if (NOT NGRAPH_DEX_ONLY)
list(APPEND SRC cpu_codegen.cpp)
endif()
if (NGRAPH_HALIDE)
list(APPEND SRC halide.cpp)
endif()
......
//*****************************************************************************
// Copyright 2017-2019 Intel Corporation
//
// Licensed 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.
//*****************************************************************************
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "util/all_close.hpp"
#include "util/ndarray.hpp"
using namespace ngraph;
using namespace std;
TEST(cpu_codegen, abc)
{
Shape shape{2, 2};
auto A = make_shared<op::Parameter>(element::f32, shape);
auto B = make_shared<op::Parameter>(element::f32, shape);
auto C = make_shared<op::Parameter>(element::f32, shape);
auto f = make_shared<Function>((A + B) * C, ParameterVector{A, B, C});
auto backend = runtime::Backend::create("CPU");
// Create some tensors for input/output
shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> c = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape);
copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector());
copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector());
copy_data(c, test::NDArray<float, 2>({{9, 10}, {11, 12}}).get_vector());
ngraph::pass::PassConfig pass_config{ngraph::pass::CompilationMode::CODEGEN};
auto handle = backend->compile(f, pass_config);
handle->call_with_validate({result}, {a, b, c});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector());
handle->call_with_validate({result}, {b, a, c});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector());
handle->call_with_validate({result}, {a, c, b});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{50, 72}, {98, 128}})).get_vector());
}
......@@ -892,41 +892,6 @@ TEST(cpu_test, convert_inplace)
EXPECT_EQ((vector<int8_t>{1, 2, 3, -2}), read_vector<int8_t>(result));
}
TEST(cpu_test, abc_codegen)
{
Shape shape{2, 2};
auto A = make_shared<op::Parameter>(element::f32, shape);
auto B = make_shared<op::Parameter>(element::f32, shape);
auto C = make_shared<op::Parameter>(element::f32, shape);
auto f = make_shared<Function>((A + B) * C, ParameterVector{A, B, C});
auto backend = runtime::Backend::create("CPU");
// Create some tensors for input/output
shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> c = backend->create_tensor(element::f32, shape);
shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape);
copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector());
copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector());
copy_data(c, test::NDArray<float, 2>({{9, 10}, {11, 12}}).get_vector());
ngraph::pass::PassConfig pass_config{ngraph::pass::CompilationMode::CODEGEN};
auto handle = backend->compile(f, pass_config);
handle->call_with_validate({result}, {a, b, c});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector());
handle->call_with_validate({result}, {b, a, c});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{54, 80}, {110, 144}})).get_vector());
handle->call_with_validate({result}, {a, c, b});
EXPECT_EQ(read_vector<float>(result),
(test::NDArray<float, 2>({{50, 72}, {98, 128}})).get_vector());
}
TEST(cpu_test, rotated_pooling)
{
auto make_f = [&](bool is_4d, bool avgpool) {
......
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