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
|
# Copyright (c) 2022 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.
# Script that dumps FM of FP32 model
# NOTE This script runs on dalgona
import numpy as np
import json
from pathlib import Path
# Dump FP32 model's intermediate FM data and their names
#
# Before
# self._dir/
#
# After
# self._dir/
# tensors.json
# <TENSOR_ID>.npy
# NOTE tensors.json has a dictionary {TENSOR_NAME -> TENSOR_ID}
class DumpFP32FM:
def StartAnalysis(self, args):
self._dir = Path(args)
self._num_data = 0
# Dict {tensor_name -> tid}
self._tname_to_tid = dict()
self._tensor_count = 0
def EndNetworkExecution(self, outputs):
self._num_data += 1
def DefaultOpPost(self, name, opcode, inputs, outputs):
# Save intermediate FM into <tid>.npy
data_path = self._dir / str(self._num_data)
data_path.mkdir(parents=False, exist_ok=True)
for output in outputs:
name = output['name']
data = output['data']
if name in self._tname_to_tid:
tid = self._tname_to_tid[name]
else:
tid = self._tensor_count
self._tname_to_tid[name] = tid
self._tensor_count += 1
np.save(str(data_path / str(tid)), data)
def EndAnalysis(self):
# Save tensor name : tensor id pairs
with open(self._dir / 'tensors.json', 'w') as f:
json.dump(self._tname_to_tid, f, indent=2)
|
