Spaces:
Runtime error
Runtime error
File size: 3,766 Bytes
72ff821 82f1bf5 9279c83 966795b 87a0e23 82f1bf5 72ff821 82f1bf5 49ce4b9 87a0e23 49ce4b9 9ee06c7 883e16a 87a0e23 966795b 87a0e23 9279c83 82f1bf5 d754e91 35fba55 82f1bf5 d754e91 c15d0e4 72ff821 9279c83 |
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 |
import os
import subprocess
from typing import Any, Dict, List, Optional, Tuple, Union
from numba import cuda
import nvidia_smi
from .utils.lru_cache import LRUCache
from .lib.finetune import train
class Global:
version = None
base_model: str = ""
data_dir: str = ""
load_8bit: bool = False
loaded_tokenizer: Any = None
loaded_base_model: Any = None
# Functions
train_fn: Any = train
# Training Control
should_stop_training = False
# Generation Control
should_stop_generating = False
generation_force_stopped_at = None
# Model related
model_has_been_used = False
cached_lora_models = LRUCache(10)
# GPU Info
gpu_cc = None # GPU compute capability
gpu_sms = None # GPU total number of SMs
gpu_total_cores = None # GPU total cores
gpu_total_memory = None
# UI related
ui_title: str = "LLaMA-LoRA"
ui_emoji: str = "🦙🎛️"
ui_subtitle: str = "Toolkit for evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA)."
ui_show_sys_info: bool = True
ui_dev_mode: bool = False
ui_dev_mode_title_prefix: str = "[UI DEV MODE] "
def get_package_dir():
current_file_path = os.path.abspath(__file__)
parent_directory_path = os.path.dirname(current_file_path)
return os.path.abspath(parent_directory_path)
def get_git_commit_hash():
try:
original_cwd = os.getcwd()
project_dir = get_package_dir()
try:
os.chdir(project_dir)
commit_hash = subprocess.check_output(
['git', 'rev-parse', 'HEAD']).strip().decode('utf-8')
return commit_hash
except Exception as e:
print(f"Cannot get git commit hash: {e}")
finally:
os.chdir(original_cwd)
except Exception as e:
print(f"Cannot get git commit hash: {e}")
commit_hash = get_git_commit_hash()
if commit_hash:
Global.version = commit_hash[:8]
def load_gpu_info():
try:
cc_cores_per_SM_dict = {
(2, 0): 32,
(2, 1): 48,
(3, 0): 192,
(3, 5): 192,
(3, 7): 192,
(5, 0): 128,
(5, 2): 128,
(6, 0): 64,
(6, 1): 128,
(7, 0): 64,
(7, 5): 64,
(8, 0): 64,
(8, 6): 128,
(8, 9): 128,
(9, 0): 128
}
# the above dictionary should result in a value of "None" if a cc match
# is not found. The dictionary needs to be extended as new devices become
# available, and currently does not account for all Jetson devices
device = cuda.get_current_device()
device_sms = getattr(device, 'MULTIPROCESSOR_COUNT')
device_cc = device.compute_capability
cores_per_sm = cc_cores_per_SM_dict.get(device_cc)
total_cores = cores_per_sm*device_sms
print("GPU compute capability: ", device_cc)
print("GPU total number of SMs: ", device_sms)
print("GPU total cores: ", total_cores)
Global.gpu_cc = device_cc
Global.gpu_sms = device_sms
Global.gpu_total_cores = total_cores
nvidia_smi.nvmlInit()
handle = nvidia_smi.nvmlDeviceGetHandleByIndex(0)
info = nvidia_smi.nvmlDeviceGetMemoryInfo(handle)
total_memory = info.total
total_memory_mb = total_memory / (1024 ** 2)
total_memory_gb = total_memory / (1024 ** 3)
# Print the memory size
print(
f"GPU total memory: {total_memory} bytes ({total_memory_mb:.2f} MB) ({total_memory_gb:.2f} GB)")
Global.gpu_total_memory = total_memory
except Exception as e:
print(f"Notice: cannot get GPU info: {e}")
load_gpu_info()
|