forked from huggingface/transformers
273 lines (234 loc) 路 9.22 KB
/
self-push.yml
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
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
name: Self-hosted runner (push)
on:
push:
branches:
- master
- model-templates
paths:
- "src/**"
- "tests/**"
- ".github/**"
- "templates/**"
# pull_request:
repository_dispatch:
jobs:
run_tests_torch_gpu:
runs-on: [self-hosted, gpu, single-gpu]
steps:
- uses: actions/checkout@v2
- name: Python version
run: |
which python
python --version
pip --version
- name: Current dir
run: pwd
- run: nvidia-smi
- name: Loading cache.
uses: actions/cache@v2
id: cache
with:
path: .env
key: v1.1-tests_torch_gpu-${{ hashFiles('setup.py') }}
- name: Create new python env (on self-hosted runners we have to handle isolation ourselves)
run: |
python -m venv .env
source .env/bin/activate
which python
python --version
pip --version
- name: Install dependencies
run: |
source .env/bin/activate
pip install --upgrade pip
pip install .[torch,sklearn,testing,onnxruntime,sentencepiece]
pip install git+https://github.com/huggingface/datasets
- name: Are GPUs recognized by our DL frameworks
run: |
source .env/bin/activate
python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
# - name: Create model files
# run: |
# source .env/bin/activate
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/encoder-bert-tokenizer.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/pt-encoder-bert-tokenizer.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/standalone.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/tf-encoder-bert-tokenizer.json --path=templates/adding_a_new_model
- name: Run all non-slow tests on GPU
env:
OMP_NUM_THREADS: 1
CUDA_VISIBLE_DEVICES: 0
run: |
source .env/bin/activate
python -m pytest -n 2 --dist=loadfile -s --make-reports=tests_torch_gpu tests
- name: Failure short reports
if: ${{ always() }}
run: cat reports/tests_torch_gpu_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: run_all_tests_torch_gpu_test_reports
path: reports
run_tests_tf_gpu:
runs-on: [self-hosted, gpu, single-gpu]
steps:
- uses: actions/checkout@v2
- name: Python version
run: |
which python
python --version
pip --version
- name: Current dir
run: pwd
- run: nvidia-smi
- name: Loading cache.
uses: actions/cache@v2
id: cache
with:
path: .env
key: v1.1-tests_tf_gpu-${{ hashFiles('setup.py') }}
- name: Create new python env (on self-hosted runners we have to handle isolation ourselves)
run: |
python -m venv .env
source .env/bin/activate
which python
python --version
pip --version
- name: Install dependencies
run: |
source .env/bin/activate
pip install --upgrade pip
pip install .[tf,sklearn,testing,onnxruntime,sentencepiece]
pip install git+https://github.com/huggingface/datasets
- name: Are GPUs recognized by our DL frameworks
run: |
source .env/bin/activate
TF_CPP_MIN_LOG_LEVEL=3 python -c "import tensorflow as tf; print('TF GPUs available:', bool(tf.config.list_physical_devices('GPU')))"
TF_CPP_MIN_LOG_LEVEL=3 python -c "import tensorflow as tf; print('Number of TF GPUs available:', len(tf.config.list_physical_devices('GPU')))"
- name: Create model files
run: |
source .env/bin/activate
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/encoder-bert-tokenizer.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/pt-encoder-bert-tokenizer.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/standalone.json --path=templates/adding_a_new_model
# transformers-cli add-new-model --testing --testing_file=templates/adding_a_new_model/tests/tf-encoder-bert-tokenizer.json --path=templates/adding_a_new_model
- name: Run all non-slow tests on GPU
env:
OMP_NUM_THREADS: 1
CUDA_VISIBLE_DEVICES: 0
run: |
source .env/bin/activate
python -m pytest -n 2 --dist=loadfile -s --make-reports=tests_tf_gpu tests
- name: Failure short reports
if: ${{ always() }}
run: cat reports/tests_tf_gpu_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: run_all_tests_tf_gpu_test_reports
path: reports
run_tests_torch_multi_gpu:
runs-on: [self-hosted, gpu, multi-gpu]
steps:
- uses: actions/checkout@v2
- name: Python version
run: |
which python
python --version
pip --version
- name: Current dir
run: pwd
- run: nvidia-smi
- name: Loading cache.
uses: actions/cache@v2
id: cache
with:
path: .env
key: v1.1-tests_torch_multi_gpu-${{ hashFiles('setup.py') }}
- name: Create new python env (on self-hosted runners we have to handle isolation ourselves)
run: |
python -m venv .env
source .env/bin/activate
which python
python --version
pip --version
- name: Install dependencies
run: |
source .env/bin/activate
pip install --upgrade pip
pip install .[torch,sklearn,testing,onnxruntime,sentencepiece]
pip install git+https://github.com/huggingface/datasets
- name: Are GPUs recognized by our DL frameworks
run: |
source .env/bin/activate
python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
- name: Run all non-slow tests on GPU
env:
OMP_NUM_THREADS: 1
run: |
source .env/bin/activate
python -m pytest -n 2 --dist=loadfile -s --make-reports=tests_torch_multi_gpu tests
- name: Failure short reports
if: ${{ always() }}
run: cat reports/tests_torch_multi_gpu_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: run_all_tests_torch_multi_gpu_test_reports
path: reports
run_tests_tf_multi_gpu:
runs-on: [self-hosted, gpu, multi-gpu]
steps:
- uses: actions/checkout@v2
- name: Python version
run: |
which python
python --version
pip --version
- name: Current dir
run: pwd
- run: nvidia-smi
- name: Loading cache.
uses: actions/cache@v2
id: cache
with:
path: .env
key: v1.1-tests_tf_multi_gpu-${{ hashFiles('setup.py') }}
- name: Create new python env (on self-hosted runners we have to handle isolation ourselves)
run: |
python -m venv .env
source .env/bin/activate
which python
python --version
pip --version
- name: Install dependencies
run: |
source .env/bin/activate
pip install --upgrade pip
pip install .[tf,sklearn,testing,onnxruntime,sentencepiece]
pip install git+https://github.com/huggingface/datasets
- name: Are GPUs recognized by our DL frameworks
run: |
source .env/bin/activate
TF_CPP_MIN_LOG_LEVEL=3 python -c "import tensorflow as tf; print('TF GPUs available:', bool(tf.config.list_physical_devices('GPU')))"
TF_CPP_MIN_LOG_LEVEL=3 python -c "import tensorflow as tf; print('Number of TF GPUs available:', len(tf.config.list_physical_devices('GPU')))"
- name: Run all non-slow tests on GPU
env:
OMP_NUM_THREADS: 1
run: |
source .env/bin/activate
python -m pytest -n 2 --dist=loadfile -s --make-reports=tests_tf_multi_gpu tests
- name: Failure short reports
if: ${{ always() }}
run: cat reports/tests_tf_multi_gpu_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: run_all_tests_tf_multi_gpu_test_reports
path: reports