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Diffstat (limited to 'compiler/locomotiv/src/Node/EltwiseAdd.test.cpp')
-rw-r--r-- | compiler/locomotiv/src/Node/EltwiseAdd.test.cpp | 121 |
1 files changed, 121 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/EltwiseAdd.test.cpp b/compiler/locomotiv/src/Node/EltwiseAdd.test.cpp new file mode 100644 index 000000000..2899dccdd --- /dev/null +++ b/compiler/locomotiv/src/Node/EltwiseAdd.test.cpp @@ -0,0 +1,121 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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 "NodeExecution.h" + +#include "locomotiv/NodeData.h" +#include "NodeDataImpl.h" +#include "NodeDomain.h" + +#include <nncc/core/ADT/tensor/Shape.h> +#include <nncc/core/ADT/tensor/Buffer.h> +#include <nncc/core/ADT/tensor/LexicalLayout.h> +#include <nncc/core/ADT/tensor/Index.h> +#include <nncc/core/ADT/tensor/IndexEnumerator.h> + +#include <gtest/gtest.h> + +using nncc::core::ADT::tensor::Shape; +using nncc::core::ADT::tensor::LexicalLayout; +using nncc::core::ADT::tensor::make_buffer; +using nncc::core::ADT::tensor::IndexEnumerator; + +/* +test case generated from the following: + +x = tf.constant([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18], + shape=[1, 3, 3, 2], dtype=tf.float32) +y = tf.constant([-1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -11, -12, -13, -14, -15, -16, -17, -18], + shape=[1, 3, 3, 2], dtype=tf.float32) +out = tf.math.add(x, y) + +with tf.Session() as sess: + print(sess.run(out)) +*/ +TEST(NodeExecution_EltwiseAdd, f32) +{ + float x_val[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18}; + float y_val[] = {-1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -11, -12, -13, -14, -15, -16, -17, -18}; + float out_val[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; + + // make EltwiseAdd(Pull, Pull) + auto g = loco::make_graph(); + Shape input_shape{1, 3, 3, 2}; // NHWC + + auto inp_lhs = g->nodes()->create<loco::Pull>(); + { + inp_lhs->dtype(loco::DataType::FLOAT32); + inp_lhs->shape({1, 3, 3, 2}); + } + + auto inp_rhs = g->nodes()->create<loco::Pull>(); + { + inp_rhs->dtype(loco::DataType::FLOAT32); + inp_rhs->shape({1, 3, 3, 2}); + } + + auto eltwise_add = g->nodes()->create<loco::EltwiseAdd>(); + { + eltwise_add->lhs(inp_lhs); + eltwise_add->rhs(inp_rhs); + } + + // Make and assign data to two pull nodes + auto inp_lhs_buf = make_buffer<float, LexicalLayout>(input_shape); + { + int n = 0; + for (IndexEnumerator e{inp_lhs_buf.shape()}; e.valid(); e.advance()) + { + inp_lhs_buf.at(e.current()) = x_val[n++]; + } + } + + auto inp_rhs_buf = make_buffer<float, LexicalLayout>(input_shape); + { + int n = 0; + for (IndexEnumerator e{inp_rhs_buf.shape()}; e.valid(); e.advance()) + { + inp_rhs_buf.at(e.current()) = y_val[n++]; + } + } + + auto inp_lhs_data = locomotiv::make_data(inp_lhs_buf); + locomotiv::annot_data(inp_lhs, std::move(inp_lhs_data)); + locomotiv::annot_domain(inp_lhs, loco::Domain::Tensor); + + auto inp_rhs_data = locomotiv::make_data(inp_rhs_buf); + locomotiv::annot_data(inp_rhs, std::move(inp_rhs_data)); + locomotiv::annot_domain(inp_rhs, loco::Domain::Tensor); + + // run the network + locomotiv::NodeExecution::get().run(eltwise_add); + + // get result + auto eltwise_add_data = locomotiv::annot_data(eltwise_add); + + // comparing the result + ASSERT_NE(eltwise_add_data, nullptr); + ASSERT_EQ(eltwise_add_data->dtype(), loco::DataType::FLOAT32); + ASSERT_EQ(*(eltwise_add_data->shape()), Shape({1, 3, 3, 2})); + + uint32_t n = 0; + for (IndexEnumerator e{*(eltwise_add_data->shape())}; e.valid(); e.advance()) + { + ASSERT_FLOAT_EQ(eltwise_add_data->as_f32_bufptr()->at(e.current()), out_val[n++]); + } + + ASSERT_EQ(locomotiv::annot_domain(eltwise_add), loco::Domain::Tensor); +} |