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//*****************************************************************************
// 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_f.hpp"
#include "util/test_control.hpp"
#include "util/test_tools.hpp"
using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
NGRAPH_TEST(${BACKEND_NAME}, create_dynamic_backend)
{
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
ASSERT_NE(backend, nullptr);
ASSERT_TRUE(backend->supports_dynamic_tensors());
}
NGRAPH_TEST(${BACKEND_NAME}, create_dynamic_tensor)
{
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
auto t = backend->create_dynamic_tensor(element::f32, PartialShape{2, Dimension::dynamic(), 3});
ASSERT_TRUE(t->get_partial_shape().same_scheme(PartialShape{2, Dimension::dynamic(), 3}));
}
NGRAPH_TEST(${BACKEND_NAME}, dynamic_abc)
{
//
// Create a graph for f(a,b,c) = (a+b)*c, where a, b, c all have shape {2,?,3}.
//
auto a = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
auto b = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
auto c = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
auto a_plus_b_times_c = (a + b) * c;
auto f = make_shared<Function>(NodeVector{a_plus_b_times_c}, ParameterVector{a, b, c});
//
// Get a backend with dynamic support, and compile f.
//
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
auto ex = backend->compile(f);
//
// Create a dynamic output tensor with shape {2,?,3}.
//
auto t_r =
backend->create_dynamic_tensor(element::f32, PartialShape{2, Dimension::dynamic(), 3});
//
// For each of n=[0,...,5), run the compiled executable against a test vector of shape
// {2,n,3}, and check the results.
//
for (size_t middle_dim = 0; middle_dim < 5; middle_dim++)
{
// Fill in some test input values, which we'll use for a, b, and c.
vector<float> inputs(2 * middle_dim * 3);
for (size_t i = 0; i < 2 * middle_dim * 3; i++)
{
inputs[i] = i;
}
// Create static tensors for the inputs and copy data.
auto t_a = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
auto t_b = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
auto t_c = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
copy_data(t_a, inputs);
copy_data(t_b, inputs);
copy_data(t_c, inputs);
// Call ex, writing result into t_r (note we're using the same t_r from outside the loop.)
ex->call_with_validate({t_r}, {t_a, t_b, t_c});
// After call, t_r should have a shape of {2,n,3}.
ASSERT_EQ(t_r->get_shape(), (Shape{2, middle_dim, 3}));
// Read out the results, and compare them against expected values.
auto results = read_vector<float>(t_r);
vector<float> expected_values(2 * middle_dim * 3);
for (size_t i = 0; i < 2 * middle_dim * 3; i++)
{
expected_values[i] = (i + i) * i;
}
EXPECT_TRUE(test::all_close_f(results, expected_values));
}
}
static void axpy_test(const PartialShape& input_pshape, const std::vector<Shape>& input_shapes)
{
auto a = make_shared<op::Parameter>(element::f32, input_pshape);
auto x = make_shared<op::Parameter>(element::f32, input_pshape);
auto y = make_shared<op::Parameter>(element::f32, input_pshape);
auto axpy = a * x + y;
auto f = make_shared<Function>(NodeVector{axpy}, ParameterVector{a, x, y});
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
auto ex = backend->compile(f);
auto t_r = backend->create_dynamic_tensor(element::f32, input_pshape);
for (auto& shape : input_shapes)
{
vector<float> inputs(shape_size(shape));
for (size_t i = 0; i < shape_size(shape); i++)
{
inputs[i] = i;
}
auto t_a = backend->create_tensor(element::f32, shape);
auto t_x = backend->create_tensor(element::f32, shape);
auto t_y = backend->create_tensor(element::f32, shape);
copy_data(t_a, inputs);
copy_data(t_x, inputs);
copy_data(t_y, inputs);
ex->call_with_validate({t_r}, {t_a, t_x, t_y});
ASSERT_EQ(t_r->get_shape(), shape);
auto results = read_vector<float>(t_r);
vector<float> expected_values(shape_size(shape));
for (size_t i = 0; i < shape_size(shape); i++)
{
expected_values[i] = (i * i) + i;
}
EXPECT_TRUE(test::all_close_f(results, expected_values));
}
}
NGRAPH_TEST(${BACKEND_NAME}, dynamic_axpy)
{
// Test with shape {?, 3, 3}.
axpy_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
// Test with shape {?, ?, ?}.
axpy_test(PartialShape::dynamic(3),
{Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
// Test with shape ?. (Rank unknown.)
axpy_test(PartialShape::dynamic(),
{Shape{2, 3, 3},
Shape{5, 3, 3},
Shape{2, 5, 2},
Shape{8, 1, 8},
Shape{5},
Shape{8, 2},
Shape{8, 2, 8, 2},
Shape{2, 3, 4, 5, 2}});
}
static void to_vector_test(const PartialShape& input_pshape, const std::vector<Shape>& input_shapes)
{
auto x = make_shared<op::Parameter>(element::f32, input_pshape);
shared_ptr<Node> x_new_shape = make_shared<op::ShapeOf>(x);
x_new_shape = make_shared<op::Product>(x_new_shape, AxisSet{0});
x_new_shape = make_shared<op::Reshape>(x_new_shape, AxisVector{}, Shape{1});
auto x_reshaped = make_shared<op::DynReshape>(x, x_new_shape);
auto f = make_shared<Function>(NodeVector{x_reshaped}, ParameterVector{x});
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
auto ex = backend->compile(f);
auto t_r = backend->create_dynamic_tensor(element::f32, PartialShape::dynamic(1));
for (auto& shape : input_shapes)
{
vector<float> inputs(shape_size(shape));
for (size_t i = 0; i < shape_size(shape); i++)
{
inputs[i] = i;
}
auto t_x = backend->create_tensor(element::f32, shape);
copy_data(t_x, inputs);
ex->call_with_validate({t_r}, {t_x});
ASSERT_EQ(t_r->get_shape(), (Shape{shape_size(shape)}));
auto results = read_vector<float>(t_r);
EXPECT_TRUE(test::all_close_f(results, inputs));
}
}
NGRAPH_TEST(${BACKEND_NAME}, dynamic_to_vector)
{
// Test with shape {?, 3, 3}.
to_vector_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
// Test with shape {?, ?, ?}.
to_vector_test(PartialShape::dynamic(3),
{Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
// Test with shape ?. (Rank unknown.)
to_vector_test(PartialShape::dynamic(),
{Shape{2, 3, 3},
Shape{5, 3, 3},
Shape{2, 5, 2},
Shape{8, 1, 8},
Shape{5},
Shape{8, 2},
Shape{8, 2, 8, 2},
Shape{2, 3, 4, 5, 2}});
}
static void reverse_shape_test(const PartialShape& input_pshape,
const std::vector<Shape>& input_shapes)
{
auto x = make_shared<op::Parameter>(element::f32, input_pshape);
shared_ptr<Node> x_new_shape = make_shared<op::ShapeOf>(x);
x_new_shape = make_shared<op::Reverse>(x_new_shape, AxisSet{0});
auto x_reshaped = make_shared<op::DynReshape>(x, x_new_shape);
auto f = make_shared<Function>(NodeVector{x_reshaped}, ParameterVector{x});
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
auto ex = backend->compile(f);
auto t_r = backend->create_dynamic_tensor(element::f32, PartialShape::dynamic());
for (auto& shape : input_shapes)
{
vector<float> inputs(shape_size(shape));
for (size_t i = 0; i < shape_size(shape); i++)
{
inputs[i] = i;
}
auto t_x = backend->create_tensor(element::f32, shape);
copy_data(t_x, inputs);
ex->call_with_validate({t_r}, {t_x});
Shape expected_shape = shape;
std::reverse(expected_shape.begin(), expected_shape.end());
ASSERT_EQ(t_r->get_shape(), expected_shape);
auto results = read_vector<float>(t_r);
EXPECT_TRUE(test::all_close_f(results, inputs));
}
}
NGRAPH_TEST(${BACKEND_NAME}, dynamic_reverse_shape)
{
// Test with shape {?, 3, 3}.
reverse_shape_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
// Test with shape {?, ?, ?}.
reverse_shape_test(PartialShape::dynamic(3),
{Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
// Test with shape ?. (Rank unknown.)
reverse_shape_test(PartialShape::dynamic(),
{Shape{2, 3, 3},
Shape{5, 3, 3},
Shape{2, 5, 2},
Shape{8, 1, 8},
Shape{5},
Shape{8, 2},
Shape{8, 2, 8, 2},
Shape{2, 3, 4, 5, 2}});
}