ONE - On-device Neural Engine
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Tanh.cpp
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1/*
2 * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
18
20
21#include <loco.h>
22
23#include <memory>
24
25namespace
26{
27
28using namespace moco;
29
33class TFTanhGraphUpdate final : public GraphUpdate
34{
35public:
36 TFTanhGraphUpdate(TFTanh *node, TensorName &&name) : _node(node), _name(name) {}
37
38 void input(const SymbolTable *) const override;
39
40private:
41 TFTanh *_node;
42 TensorName _name;
43};
44
45void TFTanhGraphUpdate::input(const SymbolTable *table) const
46{
47 loco::Node *target = table->node(_name);
48 _node->x(target);
49}
50
51} // namespace
52
53namespace moco
54{
55
56bool TanhGraphBuilder::validate(const tensorflow::NodeDef &node) const
57{
58 return node.input_size() == 1;
59}
60
61void TanhGraphBuilder::build(const tensorflow::NodeDef &node, GraphBuilderContext *context) const
62{
63 assert(context != nullptr);
64
65 loco::Graph *graph = context->graph();
66 SymbolTable *tensor_names = context->tensor_names();
67 UpdateQueue *updates = context->updates();
68
69 // creating TF dialect Tanh node
70 auto tf_tanh = graph->nodes()->create<TFTanh>();
71 tf_tanh->name(node.name());
72
73 // register string-name to node
74 TensorName output_name(node.name(), 0);
75 tensor_names->enroll(output_name, tf_tanh);
76
77 // Queue node input update
78 auto tf_tanh_update = std::make_unique<TFTanhGraphUpdate>(tf_tanh, TensorName(node.input(0)));
79 updates->enroll(std::move(tf_tanh_update));
80}
81
82} // namespace moco
A neural network graph.
Definition Graph.h:161
Logical unit of computation.
Definition Node.h:54
Class to store context to build loco graph IR from TensorFlow.
Interface to connect the graph.
virtual void input(const SymbolTable *) const =0
Do the graph input connections using the SymbolTable.
Class to store and query loco::Node* with string name key.
void enroll(const TensorName &tensor_name, loco::Node *node)
Registers a name with corresponding loco::Node *.
loco::Node * node(const TensorName &tensor_name) const
Queries enrolled(registered) with name and return node if found Will throw runtime_error if not found...
void build(const tensorflow::NodeDef &, GraphBuilderContext *) const override
Definition Tanh.cpp:61
bool validate(const tensorflow::NodeDef &) const override
Definition Tanh.cpp:56
Class to store GraphUpdate objects.
void enroll(std::unique_ptr< GraphUpdate > &&update)
Registers GraphUpdate objects.
Definition Log.h:23
Option< std::string > target(optname("--target"), overview("select target language to emit for given architecture." "Valid values are '" NNC_TARGET_ARM_CPP "', '" NNC_TARGET_X86_CPP "', '" NNC_TARGET_ARM_GPU_CPP "', '" NNC_TARGET_INTERPRETER "'"), std::string(), optional(false), optvalues(NNC_TARGET_ARM_CPP "," NNC_TARGET_X86_CPP "," NNC_TARGET_ARM_GPU_CPP "," NNC_TARGET_INTERPRETER), nullptr, separators("="))
Definition Options.h:47
NodeName name(void) const
Definition TFNodeDecl.h:50