Upload cuda_inference_transformers_fill-mask_google-bert/bert-base-uncased/benchmark.json with huggingface_hub
Browse files
cuda_inference_transformers_fill-mask_google-bert/bert-base-uncased/benchmark.json
CHANGED
@@ -3,7 +3,7 @@
|
|
3 |
"name": "cuda_inference_transformers_fill-mask_google-bert/bert-base-uncased",
|
4 |
"backend": {
|
5 |
"name": "pytorch",
|
6 |
-
"version": "2.
|
7 |
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
|
8 |
"task": "fill-mask",
|
9 |
"library": "transformers",
|
@@ -11,7 +11,7 @@
|
|
11 |
"model": "google-bert/bert-base-uncased",
|
12 |
"processor": "google-bert/bert-base-uncased",
|
13 |
"device": "cuda",
|
14 |
-
"device_ids": "
|
15 |
"seed": 42,
|
16 |
"inter_op_num_threads": null,
|
17 |
"intra_op_num_threads": null,
|
@@ -111,24 +111,24 @@
|
|
111 |
"load": {
|
112 |
"memory": {
|
113 |
"unit": "MB",
|
114 |
-
"max_ram":
|
115 |
"max_global_vram": 68702.69952,
|
116 |
-
"max_process_vram":
|
117 |
"max_reserved": 589.299712,
|
118 |
"max_allocated": 533.571072
|
119 |
},
|
120 |
"latency": {
|
121 |
"unit": "s",
|
122 |
"count": 1,
|
123 |
-
"total": 8.
|
124 |
-
"mean": 8.
|
125 |
"stdev": 0.0,
|
126 |
-
"p50": 8.
|
127 |
-
"p90": 8.
|
128 |
-
"p95": 8.
|
129 |
-
"p99": 8.
|
130 |
"values": [
|
131 |
-
8.
|
132 |
]
|
133 |
},
|
134 |
"throughput": null,
|
@@ -138,161 +138,168 @@
|
|
138 |
"forward": {
|
139 |
"memory": {
|
140 |
"unit": "MB",
|
141 |
-
"max_ram":
|
142 |
"max_global_vram": 68702.69952,
|
143 |
-
"max_process_vram":
|
144 |
"max_reserved": 589.299712,
|
145 |
"max_allocated": 439.456768
|
146 |
},
|
147 |
"latency": {
|
148 |
"unit": "s",
|
149 |
-
"count":
|
150 |
-
"total": 1.
|
151 |
-
"mean": 0.
|
152 |
-
"stdev": 0.
|
153 |
-
"p50": 0.
|
154 |
-
"p90": 0.
|
155 |
-
"p95": 0.
|
156 |
-
"p99": 0.
|
157 |
"values": [
|
158 |
-
0.
|
159 |
-
0.
|
160 |
-
0.
|
161 |
-
0.
|
162 |
-
0.
|
163 |
-
0.
|
164 |
-
0.
|
165 |
-
0.
|
166 |
-
0.
|
167 |
-
0.
|
168 |
-
0.
|
169 |
-
0.
|
170 |
-
0.
|
171 |
-
0.
|
172 |
-
0.
|
173 |
-
0.
|
174 |
-
0.
|
175 |
-
0.
|
176 |
-
0.
|
177 |
-
0.
|
178 |
-
0.
|
179 |
-
0.
|
180 |
-
0.
|
181 |
-
0.
|
182 |
-
0.
|
183 |
-
0.
|
184 |
-
0.
|
185 |
-
0.
|
186 |
-
0.
|
187 |
-
0.
|
188 |
-
0.
|
189 |
-
0.
|
190 |
-
0.
|
191 |
-
0.
|
192 |
-
0.
|
193 |
-
0.
|
194 |
-
0.
|
195 |
-
0.
|
196 |
-
0.
|
197 |
-
0.
|
198 |
-
0.
|
199 |
-
0.
|
200 |
-
0.
|
201 |
-
0.
|
202 |
-
0.
|
203 |
-
0.
|
204 |
-
0.
|
205 |
-
0.
|
206 |
-
0.
|
207 |
-
0.
|
208 |
-
0.
|
209 |
-
0.
|
210 |
-
0.
|
211 |
-
0.
|
212 |
-
0.
|
213 |
-
0.
|
214 |
-
0.
|
215 |
-
0.
|
216 |
-
0.
|
217 |
-
0.
|
218 |
-
0.
|
219 |
-
0.
|
220 |
-
0.
|
221 |
-
0.
|
222 |
-
0.
|
223 |
-
0.
|
224 |
-
0.
|
225 |
-
0.
|
226 |
-
0.
|
227 |
-
0.
|
228 |
-
0.
|
229 |
-
0.
|
230 |
-
0.
|
231 |
-
0.
|
232 |
-
0.
|
233 |
-
0.
|
234 |
-
0.
|
235 |
-
0.
|
236 |
-
0.
|
237 |
-
0.
|
238 |
-
0.
|
239 |
-
0.
|
240 |
-
0.
|
241 |
-
0.
|
242 |
-
0.
|
243 |
-
0.
|
244 |
-
0.
|
245 |
-
0.
|
246 |
-
0.
|
247 |
-
0.
|
248 |
-
0.
|
249 |
-
0.
|
250 |
-
0.
|
251 |
-
0.
|
252 |
-
0.
|
253 |
-
0.
|
254 |
-
0.
|
255 |
-
0.
|
256 |
-
0.
|
257 |
-
0.
|
258 |
-
0.
|
259 |
-
0.
|
260 |
-
0.
|
261 |
-
0.
|
262 |
-
0.
|
263 |
-
0.
|
264 |
-
0.
|
265 |
-
0.
|
266 |
-
0.
|
267 |
-
0.
|
268 |
-
0.
|
269 |
-
0.
|
270 |
-
0.
|
271 |
-
0.
|
272 |
-
0.
|
273 |
-
0.
|
274 |
-
0.
|
275 |
-
0.
|
276 |
-
0.
|
277 |
-
0.
|
278 |
-
0.
|
279 |
-
0.
|
280 |
-
0.
|
281 |
-
0.
|
282 |
-
0.
|
283 |
-
0.
|
284 |
-
0.
|
285 |
-
0.
|
286 |
-
0.
|
287 |
-
0.
|
288 |
-
0.
|
289 |
-
0.
|
290 |
-
0.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
291 |
]
|
292 |
},
|
293 |
"throughput": {
|
294 |
"unit": "samples/s",
|
295 |
-
"value":
|
296 |
},
|
297 |
"energy": null,
|
298 |
"efficiency": null
|
|
|
3 |
"name": "cuda_inference_transformers_fill-mask_google-bert/bert-base-uncased",
|
4 |
"backend": {
|
5 |
"name": "pytorch",
|
6 |
+
"version": "2.2.0.dev20231010+rocm5.7",
|
7 |
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
|
8 |
"task": "fill-mask",
|
9 |
"library": "transformers",
|
|
|
11 |
"model": "google-bert/bert-base-uncased",
|
12 |
"processor": "google-bert/bert-base-uncased",
|
13 |
"device": "cuda",
|
14 |
+
"device_ids": "6",
|
15 |
"seed": 42,
|
16 |
"inter_op_num_threads": null,
|
17 |
"intra_op_num_threads": null,
|
|
|
111 |
"load": {
|
112 |
"memory": {
|
113 |
"unit": "MB",
|
114 |
+
"max_ram": 946.982912,
|
115 |
"max_global_vram": 68702.69952,
|
116 |
+
"max_process_vram": 47096.79104,
|
117 |
"max_reserved": 589.299712,
|
118 |
"max_allocated": 533.571072
|
119 |
},
|
120 |
"latency": {
|
121 |
"unit": "s",
|
122 |
"count": 1,
|
123 |
+
"total": 8.0222158203125,
|
124 |
+
"mean": 8.0222158203125,
|
125 |
"stdev": 0.0,
|
126 |
+
"p50": 8.0222158203125,
|
127 |
+
"p90": 8.0222158203125,
|
128 |
+
"p95": 8.0222158203125,
|
129 |
+
"p99": 8.0222158203125,
|
130 |
"values": [
|
131 |
+
8.0222158203125
|
132 |
]
|
133 |
},
|
134 |
"throughput": null,
|
|
|
138 |
"forward": {
|
139 |
"memory": {
|
140 |
"unit": "MB",
|
141 |
+
"max_ram": 1084.862464,
|
142 |
"max_global_vram": 68702.69952,
|
143 |
+
"max_process_vram": 237212.884992,
|
144 |
"max_reserved": 589.299712,
|
145 |
"max_allocated": 439.456768
|
146 |
},
|
147 |
"latency": {
|
148 |
"unit": "s",
|
149 |
+
"count": 140,
|
150 |
+
"total": 1.0030574531555176,
|
151 |
+
"mean": 0.0071646960939679835,
|
152 |
+
"stdev": 0.00037430606419756976,
|
153 |
+
"p50": 0.007102169990539551,
|
154 |
+
"p90": 0.007583194828033448,
|
155 |
+
"p95": 0.007632730889320373,
|
156 |
+
"p99": 0.008038914513587948,
|
157 |
"values": [
|
158 |
+
0.007846251964569092,
|
159 |
+
0.007688490867614746,
|
160 |
+
0.007654891014099121,
|
161 |
+
0.007640330791473388,
|
162 |
+
0.007684330940246582,
|
163 |
+
0.007304969787597656,
|
164 |
+
0.007356811046600342,
|
165 |
+
0.007289610862731934,
|
166 |
+
0.007249929904937744,
|
167 |
+
0.007470890998840332,
|
168 |
+
0.008162092208862305,
|
169 |
+
0.006934410095214844,
|
170 |
+
0.006910409927368164,
|
171 |
+
0.006923369884490967,
|
172 |
+
0.006878729820251465,
|
173 |
+
0.006957930088043213,
|
174 |
+
0.006864009857177734,
|
175 |
+
0.006900650024414062,
|
176 |
+
0.007057291030883789,
|
177 |
+
0.007127049922943115,
|
178 |
+
0.007180970191955566,
|
179 |
+
0.006889450073242188,
|
180 |
+
0.006898890018463135,
|
181 |
+
0.0068900899887084964,
|
182 |
+
0.0068545699119567875,
|
183 |
+
0.006871530055999756,
|
184 |
+
0.006911690235137939,
|
185 |
+
0.006983689785003662,
|
186 |
+
0.007002729892730713,
|
187 |
+
0.006895209789276123,
|
188 |
+
0.006999050140380859,
|
189 |
+
0.006968810081481934,
|
190 |
+
0.008366251945495605,
|
191 |
+
0.007415209770202637,
|
192 |
+
0.007457291126251221,
|
193 |
+
0.007448970794677734,
|
194 |
+
0.007292651176452637,
|
195 |
+
0.007418409824371338,
|
196 |
+
0.007416650772094726,
|
197 |
+
0.007372011184692382,
|
198 |
+
0.007317131042480469,
|
199 |
+
0.007518089771270752,
|
200 |
+
0.007526731014251709,
|
201 |
+
0.00756273078918457,
|
202 |
+
0.0075163311958312985,
|
203 |
+
0.007611371040344238,
|
204 |
+
0.007517611026763916,
|
205 |
+
0.0076011309623718265,
|
206 |
+
0.007590250968933105,
|
207 |
+
0.007579211235046387,
|
208 |
+
0.007569611072540283,
|
209 |
+
0.007548810958862305,
|
210 |
+
0.007562891006469726,
|
211 |
+
0.007561611175537109,
|
212 |
+
0.007538889884948731,
|
213 |
+
0.0075764918327331544,
|
214 |
+
0.007570250988006592,
|
215 |
+
0.007591210842132569,
|
216 |
+
0.00756865119934082,
|
217 |
+
0.0075588908195495606,
|
218 |
+
0.0075779309272766115,
|
219 |
+
0.007391049861907959,
|
220 |
+
0.007177771091461182,
|
221 |
+
0.007008490085601807,
|
222 |
+
0.006701930046081543,
|
223 |
+
0.006764490127563477,
|
224 |
+
0.006726569175720215,
|
225 |
+
0.006678090095520019,
|
226 |
+
0.006694570064544678,
|
227 |
+
0.0067024102210998535,
|
228 |
+
0.006730888843536377,
|
229 |
+
0.006672490119934082,
|
230 |
+
0.006723209857940674,
|
231 |
+
0.006744329929351807,
|
232 |
+
0.006723689079284668,
|
233 |
+
0.006959691047668457,
|
234 |
+
0.007156970024108887,
|
235 |
+
0.006916170120239258,
|
236 |
+
0.006933290004730225,
|
237 |
+
0.007370730876922607,
|
238 |
+
0.007219850063323974,
|
239 |
+
0.006695209980010986,
|
240 |
+
0.0069420900344848635,
|
241 |
+
0.00688001012802124,
|
242 |
+
0.0069089698791503906,
|
243 |
+
0.006768330097198487,
|
244 |
+
0.006665929794311524,
|
245 |
+
0.0069635300636291505,
|
246 |
+
0.0067622499465942384,
|
247 |
+
0.006724009990692139,
|
248 |
+
0.006731529235839844,
|
249 |
+
0.006728970050811768,
|
250 |
+
0.006694570064544678,
|
251 |
+
0.006697450160980225,
|
252 |
+
0.006749448776245118,
|
253 |
+
0.0067428889274597165,
|
254 |
+
0.006732009887695313,
|
255 |
+
0.00672992992401123,
|
256 |
+
0.006764490127563477,
|
257 |
+
0.0067267298698425295,
|
258 |
+
0.00670288896560669,
|
259 |
+
0.00701521110534668,
|
260 |
+
0.006711369037628174,
|
261 |
+
0.0069139299392700195,
|
262 |
+
0.0067144098281860356,
|
263 |
+
0.006903210163116455,
|
264 |
+
0.006924489974975586,
|
265 |
+
0.006775050163269043,
|
266 |
+
0.006709449768066407,
|
267 |
+
0.006687530040740967,
|
268 |
+
0.006681768894195556,
|
269 |
+
0.006758729934692383,
|
270 |
+
0.006681290149688721,
|
271 |
+
0.006770890235900879,
|
272 |
+
0.0075540909767150876,
|
273 |
+
0.007632330894470215,
|
274 |
+
0.007596170902252198,
|
275 |
+
0.007408650875091552,
|
276 |
+
0.0070913701057434084,
|
277 |
+
0.0071011300086975095,
|
278 |
+
0.007200331211090088,
|
279 |
+
0.0070889701843261715,
|
280 |
+
0.0075294508934021,
|
281 |
+
0.007523050785064697,
|
282 |
+
0.007602571010589599,
|
283 |
+
0.00758241081237793,
|
284 |
+
0.007561611175537109,
|
285 |
+
0.00756705093383789,
|
286 |
+
0.007548810958862305,
|
287 |
+
0.0075712108612060545,
|
288 |
+
0.00755233097076416,
|
289 |
+
0.0075609698295593265,
|
290 |
+
0.007525771141052246,
|
291 |
+
0.007570411205291748,
|
292 |
+
0.007545451164245606,
|
293 |
+
0.00754033088684082,
|
294 |
+
0.007550411224365235,
|
295 |
+
0.0072220897674560545,
|
296 |
+
0.007169610977172851,
|
297 |
+
0.007103209972381592
|
298 |
]
|
299 |
},
|
300 |
"throughput": {
|
301 |
"unit": "samples/s",
|
302 |
+
"value": 139.57326129183738
|
303 |
},
|
304 |
"energy": null,
|
305 |
"efficiency": null
|