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be903e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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 "inline_block.h"
#include "../pass_level1.h"
#include <set>
#include <torch/csrc/jit/passes/quantization/helper.h>
#include <torch/csrc/api/include/torch/version.h>
namespace pnnx {
static void inlineCallTo(torch::jit::Node* to_replace, torch::jit::Function* callee)
{
torch::jit::WithInsertPoint guard(to_replace);
std::unordered_map<torch::jit::Value*, torch::jit::Value*> value_map;
#if TORCH_VERSION_MAJOR >= 2 || (TORCH_VERSION_MAJOR >= 1 && TORCH_VERSION_MINOR >= 11)
std::vector<torch::jit::Value*> new_outputs = torch::jit::insertGraph(*to_replace->owningGraph(), *(toGraphFunction(*callee).graph()), to_replace->inputs(), value_map);
#else
std::vector<torch::jit::Value*> new_outputs = torch::jit::insertGraph(*to_replace->owningGraph(), *(callee->graph()), to_replace->inputs(), value_map);
#endif
const auto& old_outputs = to_replace->outputs();
for (size_t i = 0; i < old_outputs.size(); ++i)
{
new_outputs[i]->copyMetadata(old_outputs[i]);
old_outputs[i]->replaceAllUsesWith(new_outputs[i]);
}
to_replace->destroy();
}
static void inlineCalls(torch::jit::Block* block, const std::vector<std::string>& module_operators, std::set<std::string>& inlined_modules, bool inside_module_op = false)
{
for (auto it = block->nodes().begin(), end = block->nodes().end(); it != end;)
{
torch::jit::Node* n = *it++;
if (n->kind() == c10::prim::CallFunction)
{
auto function_constant = n->input(0)->node();
auto fun_type = function_constant->output()->type()->expect<torch::jit::FunctionType>();
if (!fun_type->function()->isGraphFunction())
continue;
#if TORCH_VERSION_MAJOR >= 2 || (TORCH_VERSION_MAJOR >= 1 && TORCH_VERSION_MINOR >= 11)
inlineCalls(toGraphFunction(*(fun_type->function())).graph()->block(), module_operators, inlined_modules, inside_module_op);
#else
inlineCalls(fun_type->function()->graph()->block(), module_operators, inlined_modules, inside_module_op);
#endif
n->removeInput(0);
fprintf(stderr, "inline function %s\n", fun_type->function()->name().c_str());
pnnx::inlineCallTo(n, fun_type->function());
}
else if (n->kind() == c10::prim::CallMethod)
{
auto class_type = n->input(0)->type()->cast<torch::jit::ClassType>();
if (!class_type)
continue;
const std::string& function_name = n->s(torch::jit::attr::name);
torch::jit::Function& function = class_type->getMethod(function_name);
if (!function.isGraphFunction())
continue;
std::string class_type_str = torch::jit::removeTorchMangle(class_type->str());
std::string class_type_str_no_torch_prefix = class_type_str.substr(10);
if (!inside_module_op)
{
if (std::find(module_operators.begin(), module_operators.end(), class_type_str_no_torch_prefix) != module_operators.end())
{
#if TORCH_VERSION_MAJOR >= 2 || (TORCH_VERSION_MAJOR >= 1 && TORCH_VERSION_MINOR >= 11)
inlineCalls(toGraphFunction(function).graph()->block(), module_operators, inlined_modules, true);
#else
inlineCalls(function.graph()->block(), module_operators, inlined_modules, true);
#endif
continue;
}
bool skip_inline = false;
for (const auto& ow : get_global_pnnx_fuse_module_passes())
{
if (class_type_str == ow->match_type_str())
{
skip_inline = true;
break;
}
}
if (skip_inline)
continue;
}
#if TORCH_VERSION_MAJOR >= 2 || (TORCH_VERSION_MAJOR >= 1 && TORCH_VERSION_MINOR >= 11)
inlineCalls(toGraphFunction(function).graph()->block(), module_operators, inlined_modules, inside_module_op);
#else
inlineCalls(function.graph()->block(), module_operators, inlined_modules, inside_module_op);
#endif
inlined_modules.insert(class_type_str_no_torch_prefix);
// fprintf(stderr, "inline %s\n", class_type_str_no_torch_prefix.c_str());
// fprintf(stderr, "inline method %s %s %s\n", function.name().c_str(), class_type->str().c_str(), n->input(0)->node()->s(torch::jit::attr::name).c_str());
pnnx::inlineCallTo(n, &function);
}
else
{
for (auto b : n->blocks())
{
inlineCalls(b, module_operators, inlined_modules, inside_module_op);
}
}
}
}
void inline_block(std::shared_ptr<torch::jit::Graph>& graph, const std::vector<std::string>& module_operators)
{
std::set<std::string> inlined_modules;
inlineCalls(graph->block(), module_operators, inlined_modules);
for (const auto& x : inlined_modules)
{
if (x == "torch.nn.modules.container.Sequential")
continue;
fprintf(stderr, "inline module = %s\n", x.c_str());
}
}
} // namespace pnnx
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