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Browse files- cli.log +0 -0
- text_classification/lvwerra/distilbert-imdb/.hydra/config.yaml +94 -0
- text_classification/lvwerra/distilbert-imdb/.hydra/hydra.yaml +173 -0
- text_classification/lvwerra/distilbert-imdb/.hydra/overrides.yaml +1 -0
- text_classification/lvwerra/distilbert-imdb/benchmark_report.json +107 -0
- text_classification/lvwerra/distilbert-imdb/cli.log +113 -0
- text_classification/lvwerra/distilbert-imdb/experiment_config.json +107 -0
- text_classification/lvwerra/distilbert-imdb/forward_codecarbon.json +33 -0
- text_classification/lvwerra/distilbert-imdb/preprocess_codecarbon.json +33 -0
cli.log
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File without changes
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text_classification/lvwerra/distilbert-imdb/.hydra/config.yaml
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backend:
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name: pytorch
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version: 2.4.0
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_target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
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task: text-classification
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model: lvwerra/distilbert-imdb
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processor: lvwerra/distilbert-imdb
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library: null
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device: cuda
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device_ids: '0'
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seed: 42
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+
inter_op_num_threads: null
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intra_op_num_threads: null
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hub_kwargs: {}
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no_weights: true
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device_map: null
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+
torch_dtype: null
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amp_autocast: false
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amp_dtype: null
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eval_mode: true
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to_bettertransformer: false
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low_cpu_mem_usage: null
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attn_implementation: null
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cache_implementation: null
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torch_compile: false
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torch_compile_config: {}
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quantization_scheme: null
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quantization_config: {}
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deepspeed_inference: false
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deepspeed_inference_config: {}
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peft_type: null
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peft_config: {}
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launcher:
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name: process
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_target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
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device_isolation: true
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device_isolation_action: warn
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start_method: spawn
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benchmark:
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name: energy_star
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_target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
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dataset_name: EnergyStarAI/text_classification
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dataset_config: ''
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dataset_split: train
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num_samples: 1000
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input_shapes:
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batch_size: 1
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text_column_name: text
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truncation: true
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max_length: -1
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dataset_prefix1: ''
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dataset_prefix2: ''
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t5_task: ''
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image_column_name: image
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resize: false
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question_column_name: question
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context_column_name: context
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sentence1_column_name: sentence1
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sentence2_column_name: sentence2
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audio_column_name: audio
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iterations: 10
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warmup_runs: 10
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energy: true
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forward_kwargs: {}
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generate_kwargs: {}
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call_kwargs: {}
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experiment_name: text_classification
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environment:
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cpu: ' AMD EPYC 7R32'
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cpu_count: 48
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cpu_ram_mb: 200472.73984
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system: Linux
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machine: x86_64
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platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
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processor: x86_64
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python_version: 3.9.20
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gpu:
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- NVIDIA A10G
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gpu_count: 1
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gpu_vram_mb: 24146608128
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81 |
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optimum_benchmark_version: 0.2.0
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82 |
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optimum_benchmark_commit: null
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transformers_version: 4.44.0
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transformers_commit: null
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accelerate_version: 0.33.0
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accelerate_commit: null
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diffusers_version: 0.30.0
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diffusers_commit: null
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optimum_version: null
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optimum_commit: null
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timm_version: null
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timm_commit: null
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peft_version: null
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peft_commit: null
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text_classification/lvwerra/distilbert-imdb/.hydra/hydra.yaml
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hydra:
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run:
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3 |
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dir: ./runs/text_classification/lvwerra/distilbert-imdb/
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4 |
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sweep:
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5 |
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dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
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6 |
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subdir: ${hydra.job.num}
|
7 |
+
launcher:
|
8 |
+
_target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
|
9 |
+
sweeper:
|
10 |
+
_target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
|
11 |
+
max_batch_size: null
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12 |
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params: null
|
13 |
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help:
|
14 |
+
app_name: ${hydra.job.name}
|
15 |
+
header: '${hydra.help.app_name} is powered by Hydra.
|
16 |
+
|
17 |
+
'
|
18 |
+
footer: 'Powered by Hydra (https://hydra.cc)
|
19 |
+
|
20 |
+
Use --hydra-help to view Hydra specific help
|
21 |
+
|
22 |
+
'
|
23 |
+
template: '${hydra.help.header}
|
24 |
+
|
25 |
+
== Configuration groups ==
|
26 |
+
|
27 |
+
Compose your configuration from those groups (group=option)
|
28 |
+
|
29 |
+
|
30 |
+
$APP_CONFIG_GROUPS
|
31 |
+
|
32 |
+
|
33 |
+
== Config ==
|
34 |
+
|
35 |
+
Override anything in the config (foo.bar=value)
|
36 |
+
|
37 |
+
|
38 |
+
$CONFIG
|
39 |
+
|
40 |
+
|
41 |
+
${hydra.help.footer}
|
42 |
+
|
43 |
+
'
|
44 |
+
hydra_help:
|
45 |
+
template: 'Hydra (${hydra.runtime.version})
|
46 |
+
|
47 |
+
See https://hydra.cc for more info.
|
48 |
+
|
49 |
+
|
50 |
+
== Flags ==
|
51 |
+
|
52 |
+
$FLAGS_HELP
|
53 |
+
|
54 |
+
|
55 |
+
== Configuration groups ==
|
56 |
+
|
57 |
+
Compose your configuration from those groups (For example, append hydra/job_logging=disabled
|
58 |
+
to command line)
|
59 |
+
|
60 |
+
|
61 |
+
$HYDRA_CONFIG_GROUPS
|
62 |
+
|
63 |
+
|
64 |
+
Use ''--cfg hydra'' to Show the Hydra config.
|
65 |
+
|
66 |
+
'
|
67 |
+
hydra_help: ???
|
68 |
+
hydra_logging:
|
69 |
+
version: 1
|
70 |
+
formatters:
|
71 |
+
colorlog:
|
72 |
+
(): colorlog.ColoredFormatter
|
73 |
+
format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
|
74 |
+
handlers:
|
75 |
+
console:
|
76 |
+
class: logging.StreamHandler
|
77 |
+
formatter: colorlog
|
78 |
+
stream: ext://sys.stdout
|
79 |
+
root:
|
80 |
+
level: INFO
|
81 |
+
handlers:
|
82 |
+
- console
|
83 |
+
disable_existing_loggers: false
|
84 |
+
job_logging:
|
85 |
+
version: 1
|
86 |
+
formatters:
|
87 |
+
simple:
|
88 |
+
format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
|
89 |
+
colorlog:
|
90 |
+
(): colorlog.ColoredFormatter
|
91 |
+
format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
|
92 |
+
- %(message)s'
|
93 |
+
log_colors:
|
94 |
+
DEBUG: purple
|
95 |
+
INFO: green
|
96 |
+
WARNING: yellow
|
97 |
+
ERROR: red
|
98 |
+
CRITICAL: red
|
99 |
+
handlers:
|
100 |
+
console:
|
101 |
+
class: logging.StreamHandler
|
102 |
+
formatter: colorlog
|
103 |
+
stream: ext://sys.stdout
|
104 |
+
file:
|
105 |
+
class: logging.FileHandler
|
106 |
+
formatter: simple
|
107 |
+
filename: ${hydra.job.name}.log
|
108 |
+
root:
|
109 |
+
level: INFO
|
110 |
+
handlers:
|
111 |
+
- console
|
112 |
+
- file
|
113 |
+
disable_existing_loggers: false
|
114 |
+
env: {}
|
115 |
+
mode: RUN
|
116 |
+
searchpath: []
|
117 |
+
callbacks: {}
|
118 |
+
output_subdir: .hydra
|
119 |
+
overrides:
|
120 |
+
hydra:
|
121 |
+
- hydra.run.dir=./runs/text_classification/lvwerra/distilbert-imdb/
|
122 |
+
- hydra.mode=RUN
|
123 |
+
task: []
|
124 |
+
job:
|
125 |
+
name: cli
|
126 |
+
chdir: true
|
127 |
+
override_dirname: ''
|
128 |
+
id: ???
|
129 |
+
num: ???
|
130 |
+
config_name: text_classification
|
131 |
+
env_set:
|
132 |
+
OVERRIDE_BENCHMARKS: '1'
|
133 |
+
env_copy: []
|
134 |
+
config:
|
135 |
+
override_dirname:
|
136 |
+
kv_sep: '='
|
137 |
+
item_sep: ','
|
138 |
+
exclude_keys: []
|
139 |
+
runtime:
|
140 |
+
version: 1.3.2
|
141 |
+
version_base: '1.3'
|
142 |
+
cwd: /
|
143 |
+
config_sources:
|
144 |
+
- path: hydra.conf
|
145 |
+
schema: pkg
|
146 |
+
provider: hydra
|
147 |
+
- path: optimum_benchmark
|
148 |
+
schema: pkg
|
149 |
+
provider: main
|
150 |
+
- path: hydra_plugins.hydra_colorlog.conf
|
151 |
+
schema: pkg
|
152 |
+
provider: hydra-colorlog
|
153 |
+
- path: /optimum-benchmark/examples/energy_star
|
154 |
+
schema: file
|
155 |
+
provider: command-line
|
156 |
+
- path: ''
|
157 |
+
schema: structured
|
158 |
+
provider: schema
|
159 |
+
output_dir: /runs/text_classification/lvwerra/distilbert-imdb
|
160 |
+
choices:
|
161 |
+
benchmark: energy_star
|
162 |
+
launcher: process
|
163 |
+
backend: pytorch
|
164 |
+
hydra/env: default
|
165 |
+
hydra/callbacks: null
|
166 |
+
hydra/job_logging: colorlog
|
167 |
+
hydra/hydra_logging: colorlog
|
168 |
+
hydra/hydra_help: default
|
169 |
+
hydra/help: default
|
170 |
+
hydra/sweeper: basic
|
171 |
+
hydra/launcher: basic
|
172 |
+
hydra/output: default
|
173 |
+
verbose: false
|
text_classification/lvwerra/distilbert-imdb/.hydra/overrides.yaml
ADDED
@@ -0,0 +1 @@
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|
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[]
|
text_classification/lvwerra/distilbert-imdb/benchmark_report.json
ADDED
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|
1 |
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{
|
2 |
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"forward": {
|
3 |
+
"memory": null,
|
4 |
+
"latency": null,
|
5 |
+
"throughput": null,
|
6 |
+
"energy": {
|
7 |
+
"unit": "kWh",
|
8 |
+
"cpu": 4.260780552715292e-05,
|
9 |
+
"ram": 3.4574266295975873e-07,
|
10 |
+
"gpu": 0.00017310774959720005,
|
11 |
+
"total": 0.00021606129778731272
|
12 |
+
},
|
13 |
+
"efficiency": {
|
14 |
+
"unit": "samples/kWh",
|
15 |
+
"value": 4628316.178052323
|
16 |
+
},
|
17 |
+
"measures": [
|
18 |
+
{
|
19 |
+
"unit": "kWh",
|
20 |
+
"cpu": 4.788936625555525e-05,
|
21 |
+
"ram": 3.8862747000765976e-07,
|
22 |
+
"gpu": 0.0001874179277120006,
|
23 |
+
"total": 0.00023569592143756352
|
24 |
+
},
|
25 |
+
{
|
26 |
+
"unit": "kWh",
|
27 |
+
"cpu": 4.7766895256945064e-05,
|
28 |
+
"ram": 3.8767394184333563e-07,
|
29 |
+
"gpu": 0.0001924432095100001,
|
30 |
+
"total": 0.00024059777870878848
|
31 |
+
},
|
32 |
+
{
|
33 |
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"unit": "kWh",
|
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"cpu": 4.6929548840971095e-05,
|
35 |
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|
36 |
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|
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},
|
39 |
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{
|
40 |
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"unit": "kWh",
|
41 |
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|
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"ram": 3.774017563084604e-07,
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44 |
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|
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|
46 |
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{
|
47 |
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"unit": "kWh",
|
48 |
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"cpu": 4.7223995263193466e-05,
|
49 |
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"ram": 3.832759843263221e-07,
|
50 |
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51 |
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"total": 0.00023929075792751976
|
52 |
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},
|
53 |
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{
|
54 |
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"unit": "kWh",
|
55 |
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"cpu": 4.684199172222349e-05,
|
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"ram": 3.8018074362500645e-07,
|
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"gpu": 0.0001938818217720002,
|
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"total": 0.00024110399423784884
|
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},
|
60 |
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{
|
61 |
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"unit": "kWh",
|
62 |
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"cpu": 0.0,
|
63 |
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"ram": 0.0,
|
64 |
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"gpu": 0.0,
|
65 |
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"total": 0.0
|
66 |
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},
|
67 |
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{
|
68 |
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"unit": "kWh",
|
69 |
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"cpu": 4.735134136597233e-05,
|
70 |
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"ram": 3.84304577944752e-07,
|
71 |
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"gpu": 0.00019417182200399952,
|
72 |
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"total": 0.0002419074679479165
|
73 |
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},
|
74 |
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{
|
75 |
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"unit": "kWh",
|
76 |
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"cpu": 4.7663552540278215e-05,
|
77 |
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"ram": 3.868384880703386e-07,
|
78 |
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"gpu": 0.00019212626481200125,
|
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"total": 0.00024017665584034984
|
80 |
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},
|
81 |
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{
|
82 |
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"unit": "kWh",
|
83 |
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"cpu": 4.785699072361202e-05,
|
84 |
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"ram": 3.882431057744409e-07,
|
85 |
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"gpu": 0.00019838932537799905,
|
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"total": 0.0002466345592073852
|
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}
|
88 |
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]
|
89 |
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},
|
90 |
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"preprocess": {
|
91 |
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"memory": null,
|
92 |
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"latency": null,
|
93 |
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"throughput": null,
|
94 |
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"energy": {
|
95 |
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"unit": "kWh",
|
96 |
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"cpu": 4.9598188381952e-06,
|
97 |
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"ram": 3.1790701493725636e-08,
|
98 |
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"gpu": 9.521952061999732e-06,
|
99 |
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"total": 1.4513561601688657e-05
|
100 |
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},
|
101 |
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"efficiency": {
|
102 |
+
"unit": "samples/kWh",
|
103 |
+
"value": 68901075.2456275
|
104 |
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},
|
105 |
+
"measures": null
|
106 |
+
}
|
107 |
+
}
|
text_classification/lvwerra/distilbert-imdb/cli.log
ADDED
@@ -0,0 +1,113 @@
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|
1 |
+
[2024-10-02 04:04:36,478][launcher][INFO] - ََAllocating process launcher
|
2 |
+
[2024-10-02 04:04:36,478][process][INFO] - + Setting multiprocessing start method to spawn.
|
3 |
+
[2024-10-02 04:04:36,486][device-isolation][INFO] - + Launched device(s) isolation process 72
|
4 |
+
[2024-10-02 04:04:36,486][device-isolation][INFO] - + Isolating device(s) [0]
|
5 |
+
[2024-10-02 04:04:36,491][process][INFO] - + Launched benchmark in isolated process 73.
|
6 |
+
[PROC-0][2024-10-02 04:04:39,199][datasets][INFO] - PyTorch version 2.4.0 available.
|
7 |
+
[PROC-0][2024-10-02 04:04:40,152][backend][INFO] - َAllocating pytorch backend
|
8 |
+
[PROC-0][2024-10-02 04:04:40,152][backend][INFO] - + Setting random seed to 42
|
9 |
+
[PROC-0][2024-10-02 04:04:41,112][pytorch][INFO] - + Using AutoModel class AutoModelForSequenceClassification
|
10 |
+
[PROC-0][2024-10-02 04:04:41,112][pytorch][INFO] - + Creating backend temporary directory
|
11 |
+
[PROC-0][2024-10-02 04:04:41,113][pytorch][INFO] - + Loading model with random weights
|
12 |
+
[PROC-0][2024-10-02 04:04:41,113][pytorch][INFO] - + Creating no weights model
|
13 |
+
[PROC-0][2024-10-02 04:04:41,113][pytorch][INFO] - + Creating no weights model directory
|
14 |
+
[PROC-0][2024-10-02 04:04:41,113][pytorch][INFO] - + Creating no weights model state dict
|
15 |
+
[PROC-0][2024-10-02 04:04:41,115][pytorch][INFO] - + Saving no weights model safetensors
|
16 |
+
[PROC-0][2024-10-02 04:04:41,115][pytorch][INFO] - + Saving no weights model pretrained config
|
17 |
+
[PROC-0][2024-10-02 04:04:41,116][pytorch][INFO] - + Loading no weights AutoModel
|
18 |
+
[PROC-0][2024-10-02 04:04:41,116][pytorch][INFO] - + Loading model directly on device: cuda
|
19 |
+
[PROC-0][2024-10-02 04:04:41,430][pytorch][INFO] - + Turning on model's eval mode
|
20 |
+
[PROC-0][2024-10-02 04:04:41,436][benchmark][INFO] - Allocating energy_star benchmark
|
21 |
+
[PROC-0][2024-10-02 04:04:41,436][energy_star][INFO] - + Loading raw dataset
|
22 |
+
[PROC-0][2024-10-02 04:04:42,817][energy_star][INFO] - + Initializing Inference report
|
23 |
+
[PROC-0][2024-10-02 04:04:42,817][energy][INFO] - + Tracking GPU energy on devices [0]
|
24 |
+
[PROC-0][2024-10-02 04:04:46,994][energy_star][INFO] - + Preprocessing dataset
|
25 |
+
[PROC-0][2024-10-02 04:04:47,415][energy][INFO] - + Saving codecarbon emission data to preprocess_codecarbon.json
|
26 |
+
[PROC-0][2024-10-02 04:04:47,415][energy_star][INFO] - + Preparing backend for Inference
|
27 |
+
[PROC-0][2024-10-02 04:04:47,415][energy_star][INFO] - + Initialising dataloader
|
28 |
+
[PROC-0][2024-10-02 04:04:47,415][energy_star][INFO] - + Warming up backend for Inference
|
29 |
+
[PROC-0][2024-10-02 04:04:47,900][energy_star][INFO] - + Running Inference energy tracking for 10 iterations
|
30 |
+
[PROC-0][2024-10-02 04:04:47,900][energy_star][INFO] - + Iteration 1/10
|
31 |
+
[PROC-0][2024-10-02 04:04:51,958][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
32 |
+
[PROC-0][2024-10-02 04:04:51,958][energy_star][INFO] - + Iteration 2/10
|
33 |
+
[PROC-0][2024-10-02 04:04:56,006][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
34 |
+
[PROC-0][2024-10-02 04:04:56,007][energy_star][INFO] - + Iteration 3/10
|
35 |
+
[PROC-0][2024-10-02 04:04:59,983][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
36 |
+
[PROC-0][2024-10-02 04:04:59,983][energy_star][INFO] - + Iteration 4/10
|
37 |
+
[PROC-0][2024-10-02 04:05:03,927][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
38 |
+
[PROC-0][2024-10-02 04:05:03,928][energy_star][INFO] - + Iteration 5/10
|
39 |
+
[PROC-0][2024-10-02 04:05:07,928][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
40 |
+
[PROC-0][2024-10-02 04:05:07,929][energy_star][INFO] - + Iteration 6/10
|
41 |
+
[PROC-0][2024-10-02 04:05:11,897][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
42 |
+
[PROC-0][2024-10-02 04:05:11,898][energy_star][INFO] - + Iteration 7/10
|
43 |
+
[PROC-0][2024-10-02 04:05:15,894][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
44 |
+
[PROC-0][2024-10-02 04:05:15,895][energy_star][INFO] - + Iteration 8/10
|
45 |
+
[PROC-0][2024-10-02 04:05:19,906][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
46 |
+
[PROC-0][2024-10-02 04:05:19,907][energy_star][INFO] - + Iteration 9/10
|
47 |
+
[PROC-0][2024-10-02 04:05:23,945][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
48 |
+
[PROC-0][2024-10-02 04:05:23,945][energy_star][INFO] - + Iteration 10/10
|
49 |
+
[PROC-0][2024-10-02 04:05:28,000][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
|
50 |
+
[PROC-0][2024-10-02 04:05:28,000][energy][INFO] - + forward energy consumption:
|
51 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + CPU: 0.000043 (kWh)
|
52 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + GPU: 0.000173 (kWh)
|
53 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + RAM: 0.000000 (kWh)
|
54 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + total: 0.000216 (kWh)
|
55 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + forward_iteration_1 energy consumption:
|
56 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + CPU: 0.000048 (kWh)
|
57 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + GPU: 0.000187 (kWh)
|
58 |
+
[PROC-0][2024-10-02 04:05:28,001][energy][INFO] - + RAM: 0.000000 (kWh)
|
59 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + total: 0.000236 (kWh)
|
60 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + forward_iteration_2 energy consumption:
|
61 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + CPU: 0.000048 (kWh)
|
62 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + GPU: 0.000192 (kWh)
|
63 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + RAM: 0.000000 (kWh)
|
64 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + total: 0.000241 (kWh)
|
65 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + forward_iteration_3 energy consumption:
|
66 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + CPU: 0.000047 (kWh)
|
67 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + GPU: 0.000188 (kWh)
|
68 |
+
[PROC-0][2024-10-02 04:05:28,002][energy][INFO] - + RAM: 0.000000 (kWh)
|
69 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + total: 0.000235 (kWh)
|
70 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + forward_iteration_4 energy consumption:
|
71 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + CPU: 0.000047 (kWh)
|
72 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + GPU: 0.000193 (kWh)
|
73 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + RAM: 0.000000 (kWh)
|
74 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + total: 0.000240 (kWh)
|
75 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + forward_iteration_5 energy consumption:
|
76 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + CPU: 0.000047 (kWh)
|
77 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + GPU: 0.000192 (kWh)
|
78 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + RAM: 0.000000 (kWh)
|
79 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + total: 0.000239 (kWh)
|
80 |
+
[PROC-0][2024-10-02 04:05:28,003][energy][INFO] - + forward_iteration_6 energy consumption:
|
81 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + CPU: 0.000047 (kWh)
|
82 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + GPU: 0.000194 (kWh)
|
83 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + RAM: 0.000000 (kWh)
|
84 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + total: 0.000241 (kWh)
|
85 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + forward_iteration_7 energy consumption:
|
86 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + CPU: 0.000000 (kWh)
|
87 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + GPU: 0.000000 (kWh)
|
88 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + RAM: 0.000000 (kWh)
|
89 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + total: 0.000000 (kWh)
|
90 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + forward_iteration_8 energy consumption:
|
91 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + CPU: 0.000047 (kWh)
|
92 |
+
[PROC-0][2024-10-02 04:05:28,004][energy][INFO] - + GPU: 0.000194 (kWh)
|
93 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + RAM: 0.000000 (kWh)
|
94 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + total: 0.000242 (kWh)
|
95 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + forward_iteration_9 energy consumption:
|
96 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + CPU: 0.000048 (kWh)
|
97 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + GPU: 0.000192 (kWh)
|
98 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + RAM: 0.000000 (kWh)
|
99 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + total: 0.000240 (kWh)
|
100 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + forward_iteration_10 energy consumption:
|
101 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + CPU: 0.000048 (kWh)
|
102 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + GPU: 0.000198 (kWh)
|
103 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + RAM: 0.000000 (kWh)
|
104 |
+
[PROC-0][2024-10-02 04:05:28,005][energy][INFO] - + total: 0.000247 (kWh)
|
105 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + preprocess energy consumption:
|
106 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + CPU: 0.000005 (kWh)
|
107 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + GPU: 0.000010 (kWh)
|
108 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + RAM: 0.000000 (kWh)
|
109 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + total: 0.000015 (kWh)
|
110 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + forward energy efficiency: 4628316.178052 (samples/kWh)
|
111 |
+
[PROC-0][2024-10-02 04:05:28,006][energy][INFO] - + preprocess energy efficiency: 68901075.245627 (samples/kWh)
|
112 |
+
[2024-10-02 04:05:28,610][device-isolation][INFO] - + Closing device(s) isolation process...
|
113 |
+
[2024-10-02 04:05:28,660][datasets][INFO] - PyTorch version 2.4.0 available.
|
text_classification/lvwerra/distilbert-imdb/experiment_config.json
ADDED
@@ -0,0 +1,107 @@
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|
1 |
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text_classification/lvwerra/distilbert-imdb/forward_codecarbon.json
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{
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text_classification/lvwerra/distilbert-imdb/preprocess_codecarbon.json
ADDED
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