Upload cuda_inference_timm_image-classification_timm/resnet50.a1_in1k/benchmark.json with huggingface_hub
Browse files
cuda_inference_timm_image-classification_timm/resnet50.a1_in1k/benchmark.json
CHANGED
@@ -3,7 +3,7 @@
|
|
3 |
"name": "cuda_inference_timm_image-classification_timm/resnet50.a1_in1k",
|
4 |
"backend": {
|
5 |
"name": "pytorch",
|
6 |
-
"version": "2.4.0+
|
7 |
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
|
8 |
"task": "image-classification",
|
9 |
"library": "timm",
|
@@ -104,7 +104,7 @@
|
|
104 |
"load": {
|
105 |
"memory": {
|
106 |
"unit": "MB",
|
107 |
-
"max_ram":
|
108 |
"max_global_vram": 709.361664,
|
109 |
"max_process_vram": 0.0,
|
110 |
"max_reserved": 123.731968,
|
@@ -113,31 +113,31 @@
|
|
113 |
"latency": {
|
114 |
"unit": "s",
|
115 |
"count": 1,
|
116 |
-
"total": 7.
|
117 |
-
"mean": 7.
|
118 |
"stdev": 0.0,
|
119 |
-
"p50": 7.
|
120 |
-
"p90": 7.
|
121 |
-
"p95": 7.
|
122 |
-
"p99": 7.
|
123 |
"values": [
|
124 |
-
7.
|
125 |
]
|
126 |
},
|
127 |
"throughput": null,
|
128 |
"energy": {
|
129 |
"unit": "kWh",
|
130 |
-
"cpu": 4.
|
131 |
-
"ram": 2.
|
132 |
-
"gpu":
|
133 |
-
"total": 1.
|
134 |
},
|
135 |
"efficiency": null
|
136 |
},
|
137 |
"forward": {
|
138 |
"memory": {
|
139 |
"unit": "MB",
|
140 |
-
"max_ram":
|
141 |
"max_global_vram": 791.150592,
|
142 |
"max_process_vram": 0.0,
|
143 |
"max_reserved": 148.897792,
|
@@ -145,174 +145,166 @@
|
|
145 |
},
|
146 |
"latency": {
|
147 |
"unit": "s",
|
148 |
-
"count":
|
149 |
-
"total": 0.
|
150 |
-
"mean": 0.
|
151 |
-
"stdev": 0.
|
152 |
-
"p50": 0.
|
153 |
-
"p90": 0.
|
154 |
-
"p95": 0.
|
155 |
-
"p99": 0.
|
156 |
"values": [
|
157 |
-
0.
|
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 |
-
0.
|
292 |
-
0.0068986878395080565,
|
293 |
-
0.0068853759765625,
|
294 |
-
0.006859776020050049,
|
295 |
-
0.006907904148101806,
|
296 |
-
0.00692633581161499,
|
297 |
-
0.0068351998329162595,
|
298 |
-
0.00679423999786377,
|
299 |
-
0.006817791938781738
|
300 |
]
|
301 |
},
|
302 |
"throughput": {
|
303 |
"unit": "samples/s",
|
304 |
-
"value":
|
305 |
},
|
306 |
"energy": {
|
307 |
"unit": "kWh",
|
308 |
-
"cpu": 8.
|
309 |
-
"ram": 4.
|
310 |
-
"gpu": 1.
|
311 |
-
"total": 2.
|
312 |
},
|
313 |
"efficiency": {
|
314 |
"unit": "samples/kWh",
|
315 |
-
"value":
|
316 |
}
|
317 |
}
|
318 |
}
|
|
|
3 |
"name": "cuda_inference_timm_image-classification_timm/resnet50.a1_in1k",
|
4 |
"backend": {
|
5 |
"name": "pytorch",
|
6 |
+
"version": "2.4.0+cu124",
|
7 |
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
|
8 |
"task": "image-classification",
|
9 |
"library": "timm",
|
|
|
104 |
"load": {
|
105 |
"memory": {
|
106 |
"unit": "MB",
|
107 |
+
"max_ram": 854.171648,
|
108 |
"max_global_vram": 709.361664,
|
109 |
"max_process_vram": 0.0,
|
110 |
"max_reserved": 123.731968,
|
|
|
113 |
"latency": {
|
114 |
"unit": "s",
|
115 |
"count": 1,
|
116 |
+
"total": 7.67897314453125,
|
117 |
+
"mean": 7.67897314453125,
|
118 |
"stdev": 0.0,
|
119 |
+
"p50": 7.67897314453125,
|
120 |
+
"p90": 7.67897314453125,
|
121 |
+
"p95": 7.67897314453125,
|
122 |
+
"p99": 7.67897314453125,
|
123 |
"values": [
|
124 |
+
7.67897314453125
|
125 |
]
|
126 |
},
|
127 |
"throughput": null,
|
128 |
"energy": {
|
129 |
"unit": "kWh",
|
130 |
+
"cpu": 4.411601574999935e-06,
|
131 |
+
"ram": 2.390782810158575e-06,
|
132 |
+
"gpu": 6.4663940619999385e-06,
|
133 |
+
"total": 1.326877844715845e-05
|
134 |
},
|
135 |
"efficiency": null
|
136 |
},
|
137 |
"forward": {
|
138 |
"memory": {
|
139 |
"unit": "MB",
|
140 |
+
"max_ram": 1092.743168,
|
141 |
"max_global_vram": 791.150592,
|
142 |
"max_process_vram": 0.0,
|
143 |
"max_reserved": 148.897792,
|
|
|
145 |
},
|
146 |
"latency": {
|
147 |
"unit": "s",
|
148 |
+
"count": 135,
|
149 |
+
"total": 0.999097406387329,
|
150 |
+
"mean": 0.007400721528795031,
|
151 |
+
"stdev": 0.0002838832395345611,
|
152 |
+
"p50": 0.00725708818435669,
|
153 |
+
"p90": 0.007823769569396974,
|
154 |
+
"p95": 0.007904870271682738,
|
155 |
+
"p99": 0.008295587596893311,
|
156 |
"values": [
|
157 |
+
0.008054783821105957,
|
158 |
+
0.0078438401222229,
|
159 |
+
0.007836671829223632,
|
160 |
+
0.007786496162414551,
|
161 |
+
0.007877632141113282,
|
162 |
+
0.007773248195648194,
|
163 |
+
0.007872511863708496,
|
164 |
+
0.007829504013061523,
|
165 |
+
0.007906303882598878,
|
166 |
+
0.007904255867004394,
|
167 |
+
0.007786496162414551,
|
168 |
+
0.0077281279563903805,
|
169 |
+
0.007629824161529541,
|
170 |
+
0.007712768077850342,
|
171 |
+
0.007815167903900147,
|
172 |
+
0.007934944152832031,
|
173 |
+
0.00789299201965332,
|
174 |
+
0.008138784408569336,
|
175 |
+
0.008210432052612305,
|
176 |
+
0.007731200218200684,
|
177 |
+
0.007708672046661377,
|
178 |
+
0.007813119888305664,
|
179 |
+
0.007803872108459473,
|
180 |
+
0.007772160053253174,
|
181 |
+
0.00781004810333252,
|
182 |
+
0.007774208068847656,
|
183 |
+
0.007705599784851074,
|
184 |
+
0.007408639907836914,
|
185 |
+
0.007279615879058838,
|
186 |
+
0.007275519847869873,
|
187 |
+
0.007255040168762207,
|
188 |
+
0.007203839778900147,
|
189 |
+
0.00719155216217041,
|
190 |
+
0.007211008071899414,
|
191 |
+
0.007175168037414551,
|
192 |
+
0.007186431884765625,
|
193 |
+
0.0085350399017334,
|
194 |
+
0.008339455604553223,
|
195 |
+
0.007288832187652588,
|
196 |
+
0.007363584041595459,
|
197 |
+
0.007270400047302246,
|
198 |
+
0.007257120132446289,
|
199 |
+
0.0072130560874938965,
|
200 |
+
0.007184383869171143,
|
201 |
+
0.0072499198913574215,
|
202 |
+
0.0072468481063842774,
|
203 |
+
0.007373824119567871,
|
204 |
+
0.007241727828979493,
|
205 |
+
0.007201791763305664,
|
206 |
+
0.007222271919250488,
|
207 |
+
0.007262207984924316,
|
208 |
+
0.007222271919250488,
|
209 |
+
0.007189504146575928,
|
210 |
+
0.007243711948394776,
|
211 |
+
0.0071792640686035155,
|
212 |
+
0.007157760143280029,
|
213 |
+
0.007209983825683594,
|
214 |
+
0.0072837119102478025,
|
215 |
+
0.007194623947143554,
|
216 |
+
0.00719046401977539,
|
217 |
+
0.007168000221252442,
|
218 |
+
0.007235583782196045,
|
219 |
+
0.007169023990631103,
|
220 |
+
0.0071792640686035155,
|
221 |
+
0.007184383869171143,
|
222 |
+
0.007186431884765625,
|
223 |
+
0.007203839778900147,
|
224 |
+
0.007215104103088379,
|
225 |
+
0.00724070405960083,
|
226 |
+
0.007172160148620606,
|
227 |
+
0.007219200134277344,
|
228 |
+
0.007197696208953858,
|
229 |
+
0.007197696208953858,
|
230 |
+
0.00719046401977539,
|
231 |
+
0.007205952167510987,
|
232 |
+
0.007245823860168457,
|
233 |
+
0.007279615879058838,
|
234 |
+
0.0071905279159545895,
|
235 |
+
0.007226431846618652,
|
236 |
+
0.007196671962738037,
|
237 |
+
0.007189504146575928,
|
238 |
+
0.007163871765136718,
|
239 |
+
0.007210015773773193,
|
240 |
+
0.007234560012817383,
|
241 |
+
0.007358463764190673,
|
242 |
+
0.00733900785446167,
|
243 |
+
0.007796735763549805,
|
244 |
+
0.007671807765960693,
|
245 |
+
0.007378943920135498,
|
246 |
+
0.007372799873352051,
|
247 |
+
0.007404543876647949,
|
248 |
+
0.007287807941436767,
|
249 |
+
0.0073471999168395995,
|
250 |
+
0.007394303798675537,
|
251 |
+
0.007633920192718506,
|
252 |
+
0.007411712169647216,
|
253 |
+
0.007445504188537597,
|
254 |
+
0.0074967360496521,
|
255 |
+
0.007529471874237061,
|
256 |
+
0.007478271961212158,
|
257 |
+
0.0073062400817871095,
|
258 |
+
0.007262207984924316,
|
259 |
+
0.007244800090789795,
|
260 |
+
0.007238656044006348,
|
261 |
+
0.00725708818435669,
|
262 |
+
0.007237631797790528,
|
263 |
+
0.00724889612197876,
|
264 |
+
0.007309311866760254,
|
265 |
+
0.007243775844573975,
|
266 |
+
0.0072325119972229,
|
267 |
+
0.007243775844573975,
|
268 |
+
0.007250944137573242,
|
269 |
+
0.007228415966033935,
|
270 |
+
0.007189504146575928,
|
271 |
+
0.0072837119102478025,
|
272 |
+
0.0072468481063842774,
|
273 |
+
0.007203839778900147,
|
274 |
+
0.0071823358535766605,
|
275 |
+
0.007196671962738037,
|
276 |
+
0.007265279769897461,
|
277 |
+
0.007225344181060791,
|
278 |
+
0.007269375801086426,
|
279 |
+
0.00719974422454834,
|
280 |
+
0.007237631797790528,
|
281 |
+
0.007175168037414551,
|
282 |
+
0.007219200134277344,
|
283 |
+
0.007203839778900147,
|
284 |
+
0.0073697280883789065,
|
285 |
+
0.007237631797790528,
|
286 |
+
0.007476223945617676,
|
287 |
+
0.007269343852996826,
|
288 |
+
0.007417856216430664,
|
289 |
+
0.007299071788787842,
|
290 |
+
0.007231488227844239,
|
291 |
+
0.007181312084197998
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
292 |
]
|
293 |
},
|
294 |
"throughput": {
|
295 |
"unit": "samples/s",
|
296 |
+
"value": 135.12196021822453
|
297 |
},
|
298 |
"energy": {
|
299 |
"unit": "kWh",
|
300 |
+
"cpu": 8.229956506226121e-08,
|
301 |
+
"ram": 4.493005148389291e-08,
|
302 |
+
"gpu": 1.7017638135172345e-07,
|
303 |
+
"total": 2.974059978978776e-07
|
304 |
},
|
305 |
"efficiency": {
|
306 |
"unit": "samples/kWh",
|
307 |
+
"value": 3362406.969153921
|
308 |
}
|
309 |
}
|
310 |
}
|