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Refactor tests to use TestCase class (#1517)

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Szymon Durawa 2020-07-29 16:08:19 +02:00 committed by GitHub
parent 6e0001a189
commit aef6016298
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1 changed files with 60 additions and 100 deletions
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158
ngraph/test/backend/reduce_max.in.cpp
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@ -16,17 +16,15 @@
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "util/all_close.hpp"
#include "util/all_close_f.hpp"
#include "util/known_element_types.hpp"
#include "util/ndarray.hpp"
#include "util/engine/test_engines.hpp"
#include "util/test_case.hpp"
#include "util/test_control.hpp"
#include "util/test_tools.hpp"
using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});
// ----------------------- keep dims = false ----------------------- //
@ -38,16 +36,13 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_to_scalar)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape);
copy_data(a, vector<float>{1, 2, 3, 4});
auto result = backend->create_tensor(element::f32, Shape{});
std::vector<float> a{1, 2, 3, 4};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{4}), read_vector<float>(result)));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>({4});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_to_scalar_int8)
@ -58,16 +53,13 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_to_scalar_int8)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::i8, shape);
copy_data(a, vector<int8_t>{1, 2, 3, 4});
auto result = backend->create_tensor(element::i8, Shape{});
std::vector<int8_t> a{1, 2, 3, 4};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_EQ((vector<int8_t>{4}), read_vector<int8_t>(result));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<int8_t>({a});
test_case.add_expected_output<int8_t>({4});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_columns)
@ -79,16 +71,13 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_columns)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{5, 6}), read_vector<float>(result)));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {5, 6});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows)
@ -100,16 +89,13 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{2, 4, 6}), read_vector<float>(result)));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {2, 4, 6});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows_int32)
@ -121,16 +107,13 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows_int32)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::i32, shape_a);
copy_data(a, vector<int32_t>{1, 2, 3, 4, 5, 6});
auto result = backend->create_tensor(element::i32, shape_rt);
std::vector<int32_t> a{1, 2, 3, 4, 5, 6};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_EQ((vector<int32_t>{2, 4, 6}), read_vector<int32_t>(result));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<int32_t>({a});
test_case.add_expected_output<int32_t>(shape_rt, {2, 4, 6});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows_zero)
@ -142,20 +125,16 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows_zero)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{});
auto result = backend->create_tensor(element::f32, shape_rt);
copy_data(result, vector<float>({3, 3, 3}));
std::vector<float> a{};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_EQ((vector<float>{-std::numeric_limits<float>::infinity(),
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt,
{-std::numeric_limits<float>::infinity(),
-std::numeric_limits<float>::infinity(),
-std::numeric_limits<float>::infinity()}),
read_vector<float>(result));
-std::numeric_limits<float>::infinity()});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_matrix_rows_zero_int32)
@ -263,19 +242,14 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_matrix_most_sig)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{19, 20, 21, 22, 23, 24, 25, 26, 27}),
read_vector<float>(result),
MIN_FLOAT_TOLERANCE_BITS));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {19, 20, 21, 22, 23, 24, 25, 26, 27});
test_case.run(MIN_FLOAT_TOLERANCE_BITS);
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_matrix_least_sig)
@ -287,19 +261,14 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_matrix_least_sig)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{3, 6, 9, 12, 15, 18, 21, 24, 27}),
read_vector<float>(result),
MIN_FLOAT_TOLERANCE_BITS));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {3, 6, 9, 12, 15, 18, 21, 24, 27});
test_case.run(MIN_FLOAT_TOLERANCE_BITS);
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_vector)
@ -311,19 +280,14 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_vector)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f((vector<float>{25.0f, 26.0f, 27.0f}),
read_vector<float>(result),
MIN_FLOAT_TOLERANCE_BITS));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {25.0f, 26.0f, 27.0f});
test_case.run(MIN_FLOAT_TOLERANCE_BITS);
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_scalar)
@ -335,18 +299,14 @@ NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_scalar)
auto f =
make_shared<Function>(make_shared<op::v1::ReduceMax>(A, axes, false), ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::f32, shape_a);
copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1});
auto result = backend->create_tensor(element::f32, shape_rt);
std::vector<float> a{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1};
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a});
EXPECT_TRUE(test::all_close_f(
(vector<float>{14.0f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
auto test_case = test::TestCase<TestEngine>(f);
test_case.add_input<float>({a});
test_case.add_expected_output<float>(shape_rt, {14.0f});
test_case.run(MIN_FLOAT_TOLERANCE_BITS);
}
NGRAPH_TEST(${BACKEND_NAME}, reduce_max_3d_to_scalar_int32)