//***************************************************************************** // 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 <algorithm> #include <cstdio> #include <iostream> #include <list> #include <memory> #include "gtest/gtest.h" #include "ngraph/autodiff/adjoints.hpp" #include "ngraph/file_util.hpp" #include "ngraph/graph_util.hpp" #include "ngraph/log.hpp" #include "ngraph/ngraph.hpp" #include "ngraph/op/batch_norm.hpp" #include "ngraph/op/get_output_element.hpp" #include "ngraph/op/parameter.hpp" #include "ngraph/pass/core_fusion.hpp" #include "ngraph/pass/cse.hpp" #include "ngraph/pass/manager.hpp" #include "ngraph/pass/reshape_elimination.hpp" #include "ngraph/pass/reshape_sinking.hpp" #include "ngraph/pass/visualize_tree.hpp" #include "ngraph/serializer.hpp" #include "ngraph/util.hpp" #include "util/all_close.hpp" #include "util/autodiff/backprop_function.hpp" #include "util/autodiff/numeric_compare.hpp" #include "util/ndarray.hpp" #include "util/random.hpp" #include "util/test_tools.hpp" using namespace ngraph; using namespace std; TEST(reshape_sinking, edge_splitting) { //checks if Reshapes are pushed through op::Abs, but stopped by Sum Shape shape_nhwc{16, 28, 28, 1}; Shape shape_nchw{16, 1, 28, 28}; auto a = make_shared<op::Parameter>(element::i32, shape_nhwc); auto reshape = make_shared<op::Reshape>(a, AxisVector{0, 3, 1, 2}, shape_nchw); auto absn = make_shared<op::Abs>(reshape); auto absn2 = make_shared<op::Abs>(absn); auto sum = make_shared<op::Sum>(reshape, AxisSet{0, 1, 2, 3}); auto func = make_shared<Function>(NodeVector{absn2, sum}, ParameterVector{a}); pass::Manager pass_manager; //size_t before_count = count_ops_of_type<op::Reshape>(func); pass_manager.register_pass<pass::VisualizeTree>("before.png"); pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); pass_manager.register_pass<pass::VisualizeTree>("after.png"); pass_manager.run_passes(func); ASSERT_EQ(func->get_results().at(1)->get_argument(0), sum); auto new_reshape = std::dynamic_pointer_cast<op::Reshape>(func->get_results().at(0)->get_argument(0)); ASSERT_TRUE(new_reshape); ASSERT_EQ(new_reshape->get_shape(), shape_nchw); } TEST(reshape_sinking, broadcast_swimming) { Shape shape_nchw{1, 32, 536, 536}; Shape shape_nhwc{1, 536, 536, 32}; Shape shape_weights{16, 32, 3, 3}; Shape conv_nhwc{1, 534, 534, 16}; Shape conv_nchw{1, 16, 534, 534}; AxisVector to_nhwc{0, 2, 3, 1}; AxisVector to_nchw{0, 3, 1, 2}; size_t channel = 16; auto bias = make_shared<op::Parameter>(element::i32, Shape{channel}); auto bias_reshape = make_shared<op::Reshape>(bias, AxisVector{0}, Shape{1, channel}); auto bias_broadcast = make_shared<op::Broadcast>(bias_reshape, conv_nhwc, AxisSet{1, 2}); auto input = make_shared<op::Parameter>(element::i32, shape_nhwc); auto reshape_input = make_shared<op::Reshape>(input, to_nchw, shape_nchw); auto weights = make_shared<op::Parameter>(element::i32, shape_weights); auto conv = make_shared<op::Convolution>(reshape_input, weights); auto conv_reshape = make_shared<op::Reshape>(conv, to_nhwc, conv_nhwc); auto add = bias_broadcast + conv_reshape; auto relu = make_shared<op::Relu>(add); auto func = make_shared<Function>(NodeVector{relu}, ParameterVector{bias, input, weights}); pass::Manager pass_manager; pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); pass_manager.run_passes(func); ASSERT_EQ(add->get_shape(), conv_nchw); ASSERT_EQ(add->get_argument(0)->get_shape(), conv_nchw); ASSERT_EQ(add->get_argument(1), conv); } #ifndef NGRAPH_JSON_DISABLE TEST(reshape_sinking, mnist_conv) { const string json_path = file_util::path_join(SERIALIZED_ZOO, "tf_conv_mnist_nhwc.json"); const string json_string = file_util::read_file_to_string(json_path); stringstream ss(json_string); shared_ptr<Function> func = ngraph::deserialize(ss); pass::Manager pass_manager; size_t before_count = count_ops_of_type<op::Reshape>(func); //pass_manager.register_pass<pass::VisualizeTree>("before.png"); pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); //pass_manager.register_pass<pass::CoreFusion>(); //pass_manager.register_pass<runtime::cpu::pass::CPUFusion>(); //pass_manager.register_pass<pass::VisualizeTree>("after.png"); pass_manager.run_passes(func); size_t before_after = count_ops_of_type<op::Reshape>(func); ASSERT_LE(before_after, before_count); } #endif TEST(reshape_sinking, nasnet_pooladd) { Shape input_shape{1, 3, 3, 1}; auto input_type = element::f32; auto output_type = element::f32; auto X = make_shared<op::Parameter>(input_type, input_shape); auto c_weights = op::Constant::create(input_type, Shape{1, 1, 1, 1}, {3}); auto reshape1 = make_shared<op::Reshape>(X, AxisVector{0, 3, 1, 2}, Shape{1, 1, 3, 3}); auto avgpool = make_shared<op::AvgPool>(reshape1, Shape{1, 1}, Strides{1, 1}, Shape{0, 0}, Shape{0, 0}); auto reshape2 = make_shared<op::Reshape>(avgpool, AxisVector{0, 2, 3, 1}, Shape{1, 3, 3, 1}); auto maxpool = make_shared<op::MaxPool>(reshape1, Shape{1, 1}, Strides{1, 1}, Shape{0, 0}, Shape{0, 0}); auto reshape3 = make_shared<op::Reshape>(maxpool, AxisVector{0, 2, 3, 1}, Shape{1, 3, 3, 1}); auto const1 = op::Constant::create(input_type, Shape{1, 3, 3, 1}, {3}); auto add1 = make_shared<op::Add>(reshape3, const1); auto add2 = make_shared<op::Add>(add1, reshape2); auto func = make_shared<Function>(add2, ParameterVector{X}); pass::Manager pass_manager; size_t before_count = count_ops_of_type<op::Reshape>(func); pass_manager.register_pass<pass::VisualizeTree>("before.png"); pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); pass_manager.register_pass<pass::VisualizeTree>("after.png"); pass_manager.run_passes(func); size_t before_after = count_ops_of_type<op::Reshape>(func); ASSERT_LE(before_after, before_count); } TEST(reshape_sinking, slice_pad) { Shape shape_a{100, 8, 8, 1}; AxisVector to_nhwc{0, 2, 3, 1}; AxisVector to_nchw{0, 3, 1, 2}; auto A = make_shared<op::Parameter>(element::f32, shape_a); auto pad_value = op::Constant::create<float>(element::f32, Shape{}, std::vector<float>{0.0f}); CoordinateDiff padding_below{0, 0, 0, 0}; CoordinateDiff padding_above{0, 1, 1, 0}; auto reshape1 = make_shared<op::Reshape>(A, to_nchw, Shape{100, 1, 8, 8}); auto maxpool = make_shared<op::MaxPool>(reshape1, Shape{1, 1}, Strides{2, 2}, Shape{0, 0}, Shape{0, 0}); auto reshape2 = make_shared<op::Reshape>(maxpool, to_nhwc, Shape{100, 4, 4, 1}); auto pad = make_shared<op::Pad>(reshape2, pad_value, padding_below, padding_above); auto slice = make_shared<op::Slice>( pad, Coordinate{0, 1, 1, 0}, Coordinate{100, 5, 5, 1}, Strides{1, 1, 1, 1}); auto reshape3 = make_shared<op::Reshape>(slice, to_nchw, Shape{100, 1, 4, 4}); auto avgpool = make_shared<op::AvgPool>(reshape3, Shape{1, 1}, Strides{2, 2}); auto reshape4 = make_shared<op::Reshape>(avgpool, to_nhwc, Shape{100, 1, 2, 2}); auto f = make_shared<Function>(reshape4, ParameterVector{A}); pass::Manager pass_manager; size_t before_count = count_ops_of_type<op::Reshape>(f); pass_manager.register_pass<pass::VisualizeTree>("before.png"); pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); pass_manager.register_pass<pass::VisualizeTree>("after.png"); pass_manager.run_passes(f); size_t before_after = count_ops_of_type<op::Reshape>(f); ASSERT_LE(before_after, before_count); } TEST(reshape_sinking, concat) { Shape shape{}; Shape shape_w{1, 1, 1, 1}; Shape shape_x{1, 3, 3, 1}; Shape shape_b{1, 3, 3, 1}; Shape r_shape{1, 3, 3, 2}; auto B_ = op::Constant::create(element::f32, shape_w, {3}); auto B = make_shared<op::Reshape>(B_, AxisVector{3, 2, 0, 1}, Shape{1, 1, 1, 1}); /* nchw */ auto A_ = make_shared<op::Parameter>(element::f32, shape_x); auto A = make_shared<op::Reshape>(A_, AxisVector{0, 3, 1, 2}, Shape{1, 1, 3, 3}); /* nchw */ auto C = op::Constant::create(element::f32, Shape{1}, {2}); auto R = make_shared<op::Parameter>(element::f32, r_shape); auto conv = make_shared<op::Convolution>(A, B, Strides{1, 1}, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1}); auto reshape_conv = make_shared<op::Reshape>(conv, AxisVector{0, 2, 3, 1}, Shape{1, 3, 3, 1}); /* nhwc */ auto broadcast = make_shared<op::Broadcast>(C, reshape_conv->get_shape(), AxisSet{0, 1, 2}); auto add = broadcast + reshape_conv; auto B1_ = op::Constant::create(element::f32, shape_w, {3}); auto B1 = make_shared<op::Reshape>(B1_, AxisVector{3, 2, 0, 1}, Shape{1, 1, 1, 1}); auto A1_ = make_shared<op::Parameter>(element::f32, shape_x); auto A1 = make_shared<op::Reshape>(A1_, AxisVector{0, 3, 1, 2}, Shape{1, 1, 3, 3}); auto C1 = op::Constant::create(element::f32, Shape{1}, {2}); auto R1 = make_shared<op::Parameter>(element::f32, r_shape); auto conv1 = make_shared<op::Convolution>(A1, B1, Strides{1, 1}, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1}); auto reshape_conv1 = make_shared<op::Reshape>(conv1, AxisVector{0, 2, 3, 1}, Shape{1, 3, 3, 1}); auto broadcast1 = make_shared<op::Broadcast>(C1, reshape_conv->get_shape(), AxisSet{0, 1, 2}); auto add1 = broadcast1 + reshape_conv1; auto concat = make_shared<op::Concat>(NodeVector{add, add1}, 3); auto relu = make_shared<op::Relu>(concat); auto reshape_relu = make_shared<op::Reshape>(relu, AxisVector{0, 3, 1, 2}, Shape{1, 2, 3, 3}); /* nchw */ auto B2_ = op::Constant::create(element::f32, Shape{1, 1, 2, 1}, {2}); auto B2 = make_shared<op::Reshape>(B2_, AxisVector{3, 2, 0, 1}, Shape{1, 2, 1, 1}); auto conv2 = make_shared<op::Convolution>(reshape_relu, B2, Strides{1, 1}, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1}); auto reshape_conv2 = make_shared<op::Reshape>(conv2, AxisVector{0, 2, 3, 1}, Shape{1, 3, 3, 1}); /* nhwc */ auto f = make_shared<Function>(reshape_conv2, ParameterVector{A_, A1_}); pass::Manager pass_manager; size_t before_count = count_ops_of_type<op::Reshape>(f); pass_manager.register_pass<pass::VisualizeTree>("before.png"); pass_manager.register_pass<pass::ReshapeSinking>(); pass_manager.register_pass<pass::ReshapeElimination>(); pass_manager.register_pass<pass::CommonSubexpressionElimination>(); pass_manager.register_pass<pass::VisualizeTree>("after.png"); pass_manager.run_passes(f); size_t before_after = count_ops_of_type<op::Reshape>(f); ASSERT_LE(before_after, before_count); } TEST(reshape_sinking, pass_property) { auto pass = std::make_shared<ngraph::pass::ReshapeSinking>(); ASSERT_EQ(true, pass->get_property(pass::PassProperty::REQUIRE_STATIC_SHAPE)); ASSERT_EQ(false, pass->get_property(pass::PassProperty::CHANGE_DYNAMIC_STATE)); }