File size: 2,510 Bytes
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 | // 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 "expand_quantization_modules.h"
#include <algorithm>
#include "pass_level2.h"
namespace pnnx {
void expand_quantization_modules(Graph& graph)
{
while (1)
{
bool matched = false;
for (size_t i = 0; i < graph.ops.size(); i++)
{
Operator* op = graph.ops[i];
if (op->type == "nn.intrinsic.quantized.ConvReLU2d")
{
op->type = "nn.quantized.Conv2d";
}
else if (op->type == "nn.intrinsic.quantized.LinearReLU")
{
op->type = "nn.quantized.Linear";
}
else
{
continue;
}
// expand to nn.quantized.Conv2d / nn.quantized.Linear + nn.ReLU
matched = true;
// insert new operator before all output consumers
const Operator* cur = 0;
{
int cur_index = graph.ops.size() - 1;
for (auto& c : op->outputs[0]->consumers)
{
int c_index = std::find(graph.ops.begin(), graph.ops.end(), c) - graph.ops.begin();
cur_index = std::min(cur_index, c_index);
}
cur = graph.ops[cur_index];
}
Operator* op_relu = graph.new_operator_before("nn.ReLU", op->name + "_relu", cur);
Operand* r0 = graph.new_operand(op->name + "_norelu");
r0->producer = op;
r0->consumers.push_back(op_relu);
op_relu->inputs.push_back(r0);
op_relu->outputs.push_back(op->outputs[0]);
op_relu->outputs[0]->producer = op_relu;
op->outputs[0] = r0;
break;
}
if (!matched)
break;
}
}
} // namespace pnnx
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