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runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/.hydra/config.yaml ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ backend:
2
+ name: pytorch
3
+ version: 2.4.0
4
+ _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
5
+ task: text-generation
6
+ model: meta-llama/Llama-3.1-8B-Instruct
7
+ processor: meta-llama/Llama-3.1-8B-Instruct
8
+ library: null
9
+ device: cuda
10
+ device_ids: '0'
11
+ seed: 42
12
+ inter_op_num_threads: null
13
+ intra_op_num_threads: null
14
+ hub_kwargs: {}
15
+ no_weights: true
16
+ device_map: null
17
+ torch_dtype: null
18
+ amp_autocast: false
19
+ amp_dtype: null
20
+ eval_mode: true
21
+ to_bettertransformer: false
22
+ low_cpu_mem_usage: null
23
+ attn_implementation: null
24
+ cache_implementation: null
25
+ torch_compile: false
26
+ torch_compile_config: {}
27
+ quantization_scheme: null
28
+ quantization_config: {}
29
+ deepspeed_inference: false
30
+ deepspeed_inference_config: {}
31
+ peft_type: null
32
+ peft_config: {}
33
+ launcher:
34
+ name: process
35
+ _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
36
+ device_isolation: false
37
+ device_isolation_action: warn
38
+ start_method: spawn
39
+ benchmark:
40
+ name: energy_star
41
+ _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
42
+ dataset_name: EnergyStarAI/text_generation
43
+ dataset_config: ''
44
+ dataset_split: train
45
+ num_samples: 1000
46
+ input_shapes:
47
+ batch_size: 1
48
+ text_column_name: text
49
+ truncation: true
50
+ max_length: -1
51
+ dataset_prefix1: ''
52
+ dataset_prefix2: ''
53
+ t5_task: ''
54
+ image_column_name: image
55
+ resize: false
56
+ question_column_name: question
57
+ context_column_name: context
58
+ sentence1_column_name: sentence1
59
+ sentence2_column_name: sentence2
60
+ audio_column_name: audio
61
+ iterations: 10
62
+ warmup_runs: 10
63
+ energy: true
64
+ forward_kwargs: {}
65
+ generate_kwargs:
66
+ max_new_tokens: 10
67
+ min_new_tokens: 10
68
+ call_kwargs: {}
69
+ experiment_name: text_generation
70
+ environment:
71
+ cpu: ' AMD EPYC 7R13 Processor'
72
+ cpu_count: 48
73
+ cpu_ram_mb: 195171.078144
74
+ system: Linux
75
+ machine: x86_64
76
+ platform: Linux-5.10.214-202.855.amzn2.x86_64-x86_64-with-glibc2.35
77
+ processor: x86_64
78
+ python_version: 3.9.20
79
+ gpu:
80
+ - NVIDIA L4
81
+ - NVIDIA L4
82
+ - NVIDIA L4
83
+ - NVIDIA L4
84
+ gpu_count: 4
85
+ gpu_vram_mb: 96611598336
86
+ optimum_benchmark_version: 0.2.0
87
+ optimum_benchmark_commit: null
88
+ transformers_version: 4.44.0
89
+ transformers_commit: null
90
+ accelerate_version: 0.33.0
91
+ accelerate_commit: null
92
+ diffusers_version: 0.30.0
93
+ diffusers_commit: null
94
+ optimum_version: null
95
+ optimum_commit: null
96
+ timm_version: null
97
+ timm_commit: null
98
+ peft_version: null
99
+ peft_commit: null
runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/.hydra/hydra.yaml ADDED
@@ -0,0 +1,175 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ hydra:
2
+ run:
3
+ dir: /runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24
4
+ sweep:
5
+ dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
6
+ 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
12
+ params: null
13
+ 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_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24
122
+ - hydra.mode=RUN
123
+ task:
124
+ - backend.model=meta-llama/Llama-3.1-8B-Instruct
125
+ - backend.processor=meta-llama/Llama-3.1-8B-Instruct
126
+ job:
127
+ name: cli
128
+ chdir: true
129
+ override_dirname: backend.model=meta-llama/Llama-3.1-8B-Instruct,backend.processor=meta-llama/Llama-3.1-8B-Instruct
130
+ id: ???
131
+ num: ???
132
+ config_name: text_generation
133
+ env_set:
134
+ OVERRIDE_BENCHMARKS: '1'
135
+ env_copy: []
136
+ config:
137
+ override_dirname:
138
+ kv_sep: '='
139
+ item_sep: ','
140
+ exclude_keys: []
141
+ runtime:
142
+ version: 1.3.2
143
+ version_base: '1.3'
144
+ cwd: /
145
+ config_sources:
146
+ - path: hydra.conf
147
+ schema: pkg
148
+ provider: hydra
149
+ - path: optimum_benchmark
150
+ schema: pkg
151
+ provider: main
152
+ - path: hydra_plugins.hydra_colorlog.conf
153
+ schema: pkg
154
+ provider: hydra-colorlog
155
+ - path: /optimum-benchmark/examples/energy_star
156
+ schema: file
157
+ provider: command-line
158
+ - path: ''
159
+ schema: structured
160
+ provider: schema
161
+ output_dir: /runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24
162
+ choices:
163
+ benchmark: energy_star
164
+ launcher: process
165
+ backend: pytorch
166
+ hydra/env: default
167
+ hydra/callbacks: null
168
+ hydra/job_logging: colorlog
169
+ hydra/hydra_logging: colorlog
170
+ hydra/hydra_help: default
171
+ hydra/help: default
172
+ hydra/sweeper: basic
173
+ hydra/launcher: basic
174
+ hydra/output: default
175
+ verbose: false
runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/.hydra/overrides.yaml ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ - backend.model=meta-llama/Llama-3.1-8B-Instruct
2
+ - backend.processor=meta-llama/Llama-3.1-8B-Instruct
runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/cli.log ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2024-10-31 22:44:28,404][launcher][INFO] - ََAllocating process launcher
2
+ [2024-10-31 22:44:28,404][process][INFO] - + Setting multiprocessing start method to spawn.
3
+ [2024-10-31 22:44:28,417][process][INFO] - + Launched benchmark in isolated process 72.
4
+ [PROC-0][2024-10-31 22:44:31,776][datasets][INFO] - PyTorch version 2.4.0 available.
5
+ [PROC-0][2024-10-31 22:44:32,632][backend][INFO] - َAllocating pytorch backend
6
+ [PROC-0][2024-10-31 22:44:32,633][backend][INFO] - + Setting random seed to 42
7
+ [PROC-0][2024-10-31 22:44:33,999][pytorch][INFO] - + Using AutoModel class AutoModelForCausalLM
8
+ [PROC-0][2024-10-31 22:44:33,999][pytorch][INFO] - + Creating backend temporary directory
9
+ [PROC-0][2024-10-31 22:44:34,000][pytorch][INFO] - + Loading model with random weights
10
+ [PROC-0][2024-10-31 22:44:34,000][pytorch][INFO] - + Creating no weights model
11
+ [PROC-0][2024-10-31 22:44:34,000][pytorch][INFO] - + Creating no weights model directory
12
+ [PROC-0][2024-10-31 22:44:34,000][pytorch][INFO] - + Creating no weights model state dict
13
+ [PROC-0][2024-10-31 22:44:34,023][pytorch][INFO] - + Saving no weights model safetensors
14
+ [PROC-0][2024-10-31 22:44:34,023][pytorch][INFO] - + Saving no weights model pretrained config
15
+ [PROC-0][2024-10-31 22:44:34,024][pytorch][INFO] - + Loading no weights AutoModel
16
+ [PROC-0][2024-10-31 22:44:34,024][pytorch][INFO] - + Loading model directly on device: cuda
17
+ [2024-10-31 22:44:35,115][experiment][ERROR] - Error during experiment
runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/error.log ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Error executing job with overrides: ['backend.model=meta-llama/Llama-3.1-8B-Instruct', 'backend.processor=meta-llama/Llama-3.1-8B-Instruct']
2
+ Traceback (most recent call last):
3
+ File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
4
+ benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
5
+ File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
6
+ raise error
7
+ File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
8
+ report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
9
+ File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
10
+ while not process_context.join():
11
+ File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
12
+ raise ProcessRaisedException(msg, error_index, failed_process.pid)
13
+ torch.multiprocessing.spawn.ProcessRaisedException:
14
+
15
+ -- Process 0 terminated with the following error:
16
+ Traceback (most recent call last):
17
+ File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
18
+ fn(i, *args)
19
+ File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
20
+ worker_output = worker(*worker_args)
21
+ File "/optimum-benchmark/optimum_benchmark/experiment.py", line 55, in run
22
+ backend: Backend = backend_factory(backend_config)
23
+ File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 81, in __init__
24
+ self.load_model_with_no_weights()
25
+ File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 246, in load_model_with_no_weights
26
+ self.load_model_from_pretrained()
27
+ File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 204, in load_model_from_pretrained
28
+ self.pretrained_model = self.automodel_class.from_pretrained(
29
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained
30
+ return model_class.from_pretrained(
31
+ File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 3810, in from_pretrained
32
+ model = cls(config, *model_args, **model_kwargs)
33
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1116, in __init__
34
+ self.model = LlamaModel(config)
35
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in __init__
36
+ [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
37
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 902, in <listcomp>
38
+ [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
39
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 691, in __init__
40
+ self.mlp = LlamaMLP(config)
41
+ File "/opt/conda/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 286, in __init__
42
+ self.gate_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=config.mlp_bias)
43
+ File "/opt/conda/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 99, in __init__
44
+ self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
45
+ File "/opt/conda/lib/python3.9/site-packages/torch/utils/_device.py", line 79, in __torch_function__
46
+ return func(*args, **kwargs)
47
+ torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 21.96 GiB of which 135.06 MiB is free. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 21.61 GiB is allocated by PyTorch, and 1.24 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
48
+
49
+
50
+ Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
runs/text_generation/l4x4/meta-llama/Llama-3.1-8B-Instruct/2024-10-31-22-44-24/experiment_config.json ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "experiment_name": "text_generation",
3
+ "backend": {
4
+ "name": "pytorch",
5
+ "version": "2.4.0",
6
+ "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
7
+ "task": "text-generation",
8
+ "model": "meta-llama/Llama-3.1-8B-Instruct",
9
+ "processor": "meta-llama/Llama-3.1-8B-Instruct",
10
+ "library": "transformers",
11
+ "device": "cuda",
12
+ "device_ids": "0",
13
+ "seed": 42,
14
+ "inter_op_num_threads": null,
15
+ "intra_op_num_threads": null,
16
+ "hub_kwargs": {
17
+ "revision": "main",
18
+ "force_download": false,
19
+ "local_files_only": false,
20
+ "trust_remote_code": true
21
+ },
22
+ "no_weights": true,
23
+ "device_map": null,
24
+ "torch_dtype": null,
25
+ "amp_autocast": false,
26
+ "amp_dtype": null,
27
+ "eval_mode": true,
28
+ "to_bettertransformer": false,
29
+ "low_cpu_mem_usage": null,
30
+ "attn_implementation": null,
31
+ "cache_implementation": null,
32
+ "torch_compile": false,
33
+ "torch_compile_config": {},
34
+ "quantization_scheme": null,
35
+ "quantization_config": {},
36
+ "deepspeed_inference": false,
37
+ "deepspeed_inference_config": {},
38
+ "peft_type": null,
39
+ "peft_config": {}
40
+ },
41
+ "launcher": {
42
+ "name": "process",
43
+ "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
44
+ "device_isolation": false,
45
+ "device_isolation_action": "warn",
46
+ "start_method": "spawn"
47
+ },
48
+ "benchmark": {
49
+ "name": "energy_star",
50
+ "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
51
+ "dataset_name": "EnergyStarAI/text_generation",
52
+ "dataset_config": "",
53
+ "dataset_split": "train",
54
+ "num_samples": 1000,
55
+ "input_shapes": {
56
+ "batch_size": 1
57
+ },
58
+ "text_column_name": "text",
59
+ "truncation": true,
60
+ "max_length": -1,
61
+ "dataset_prefix1": "",
62
+ "dataset_prefix2": "",
63
+ "t5_task": "",
64
+ "image_column_name": "image",
65
+ "resize": false,
66
+ "question_column_name": "question",
67
+ "context_column_name": "context",
68
+ "sentence1_column_name": "sentence1",
69
+ "sentence2_column_name": "sentence2",
70
+ "audio_column_name": "audio",
71
+ "iterations": 10,
72
+ "warmup_runs": 10,
73
+ "energy": true,
74
+ "forward_kwargs": {},
75
+ "generate_kwargs": {
76
+ "max_new_tokens": 10,
77
+ "min_new_tokens": 10
78
+ },
79
+ "call_kwargs": {}
80
+ },
81
+ "environment": {
82
+ "cpu": " AMD EPYC 7R13 Processor",
83
+ "cpu_count": 48,
84
+ "cpu_ram_mb": 195171.078144,
85
+ "system": "Linux",
86
+ "machine": "x86_64",
87
+ "platform": "Linux-5.10.214-202.855.amzn2.x86_64-x86_64-with-glibc2.35",
88
+ "processor": "x86_64",
89
+ "python_version": "3.9.20",
90
+ "gpu": [
91
+ "NVIDIA L4",
92
+ "NVIDIA L4",
93
+ "NVIDIA L4",
94
+ "NVIDIA L4"
95
+ ],
96
+ "gpu_count": 4,
97
+ "gpu_vram_mb": 96611598336,
98
+ "optimum_benchmark_version": "0.2.0",
99
+ "optimum_benchmark_commit": null,
100
+ "transformers_version": "4.44.0",
101
+ "transformers_commit": null,
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