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author | Chunseok Lee <chunseok.lee@samsung.com> | 2020-04-23 14:45:49 +0900 |
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committer | Chunseok Lee <chunseok.lee@samsung.com> | 2020-04-23 14:45:49 +0900 |
commit | e2ef8438a24f7c56a0744eb579a6e293ee2fbf8e (patch) | |
tree | 44a1a7951d168dd4370e13593ed03f4bc6d920c5 /compiler/mir-onnx-importer/Op/MatMul.cpp | |
parent | 302e6564a7a76109e1178207e44e45a58631c477 (diff) | |
download | nnfw-e2ef8438a24f7c56a0744eb579a6e293ee2fbf8e.tar.gz nnfw-e2ef8438a24f7c56a0744eb579a6e293ee2fbf8e.tar.bz2 nnfw-e2ef8438a24f7c56a0744eb579a6e293ee2fbf8e.zip |
Imported Upstream version 1.4.0upstream/1.4.0submit/tizen/20200423.054851
Diffstat (limited to 'compiler/mir-onnx-importer/Op/MatMul.cpp')
-rw-r--r-- | compiler/mir-onnx-importer/Op/MatMul.cpp | 50 |
1 files changed, 50 insertions, 0 deletions
diff --git a/compiler/mir-onnx-importer/Op/MatMul.cpp b/compiler/mir-onnx-importer/Op/MatMul.cpp new file mode 100644 index 000000000..6d8ea6b83 --- /dev/null +++ b/compiler/mir-onnx-importer/Op/MatMul.cpp @@ -0,0 +1,50 @@ +/* + * 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 "MatMul.h" + +#include "ONNXHelpers.h" + +#include "mir/ops/FullyConnectedOp.h" + +namespace mir_onnx +{ + +void convertMatMulV1(const onnx::NodeProto &onnx_node, ConverterContext *context) +{ + std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node); + mir::Graph *graph = context->getGraph(); + + assert(inputs.size() == 2); + auto A = inputs[0]; + auto B = inputs[1]; + // MatMul multiply N-dimentional matrix + // FullyConnected layer multiply only 2-dimentional matrix + if (A->getShape().rank() != 2 || B->getShape().rank() != 2) + throw std::runtime_error("Supported only 2D matrix multiplying!"); + // Calculate A * B. + auto result = createOp<mir::ops::FullyConnectedOp>(graph, A, B)->getOutput(0); + + context->setNodeOutputs(onnx_node, {result}); +} + +void convertMatMulV9(const onnx::NodeProto &onnx_node, ConverterContext *context) +{ + // Other type constraints + convertMatMulV1(onnx_node, context); +} + +} // namespace mir_onnx |