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oobabooga 2023-03-16 13:34:23 -03:00
parent 83cb20aad8
commit e085cb4333
1 changed files with 8 additions and 10 deletions
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18
modules/models.py
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@ -7,8 +7,9 @@ from pathlib import Path
import numpy as np import numpy as np
import torch import torch
import transformers import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, AutoConfig from accelerate import infer_auto_device_map, init_empty_weights
from accelerate import infer_auto_device_map, init_empty_weights, load_checkpoint_and_dispatch from transformers import (AutoConfig, AutoModelForCausalLM, AutoTokenizer,
BitsAndBytesConfig)
import modules.shared as shared import modules.shared as shared
@ -113,23 +114,20 @@ def load_model(model_name):
if shared.args.gpu_memory: if shared.args.gpu_memory:
memory_map = shared.args.gpu_memory memory_map = shared.args.gpu_memory
max_memory = { 0: f'{memory_map[0]}GiB' } max_memory = {}
for i in range(1, len(memory_map)): for i in range(len(memory_map)):
max_memory[i] = f'{memory_map[i]}GiB' max_memory[i] = f'{memory_map[i]}GiB'
max_memory['cpu'] = f'{shared.args.cpu_memory or 99}GiB' max_memory['cpu'] = f'{shared.args.cpu_memory or 99}GiB'
params['max_memory'] = max_memory params['max_memory'] = max_memory
else: else:
total_mem = (torch.cuda.get_device_properties(0).total_memory / (1024 * 1024)) total_mem = (torch.cuda.get_device_properties(0).total_memory / (1024*1024))
suggestion = round((total_mem - 1000) / 1000) * 1000 suggestion = round((total_mem-1000) / 1000) * 1000
if total_mem - suggestion < 800: if total_mem - suggestion < 800:
suggestion -= 1000 suggestion -= 1000
suggestion = int(round(suggestion/1000)) suggestion = int(round(suggestion/1000))
print(f"\033[1;32;1mAuto-assiging --gpu-memory {suggestion} for your GPU to try to prevent out-of-memory errors.\nYou can manually set other values.\033[0;37;0m") print(f"\033[1;32;1mAuto-assiging --gpu-memory {suggestion} for your GPU to try to prevent out-of-memory errors.\nYou can manually set other values.\033[0;37;0m")
max_memory = { max_memory = {0: f'{suggestion}GiB', 'cpu': f'{shared.args.cpu_memory or 99}GiB'}
0: f'{suggestion}GiB',
'cpu': f'{shared.args.cpu_memory or 99}GiB'
}
params['max_memory'] = max_memory params['max_memory'] = max_memory
if shared.args.disk: if shared.args.disk: