forked from microsoft/BitNet
-
Notifications
You must be signed in to change notification settings - Fork 0
/
setup_env.py
201 lines (182 loc) · 9.35 KB
/
setup_env.py
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
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
import subprocess
import signal
import sys
import os
import platform
import argparse
import logging
import shutil
from pathlib import Path
logger = logging.getLogger("setup_env")
SUPPORTED_HF_MODELS = {
"1bitLLM/bitnet_b1_58-large": {
"model_name": "bitnet_b1_58-large",
},
"1bitLLM/bitnet_b1_58-3B": {
"model_name": "bitnet_b1_58-3B",
},
"HF1BitLLM/Llama3-8B-1.58-100B-tokens": {
"model_name": "Llama3-8B-1.58-100B-tokens",
}
}
SUPPORTED_QUANT_TYPES = {
"arm64": ["i2_s", "tl1"],
"x86_64": ["i2_s", "tl2"]
}
COMPILER_EXTRA_ARGS = {
"arm64": ["-DBITNET_ARM_TL1=ON"],
"x86_64": ["-DBITNET_X86_TL2=ON"]
}
OS_EXTRA_ARGS = {
"Windows":["-T", "ClangCL"],
}
ARCH_ALIAS = {
"AMD64": "x86_64",
"x86": "x86_64",
"x86_64": "x86_64",
"aarch64": "arm64",
"arm64": "arm64",
"ARM64": "arm64",
}
def system_info():
return platform.system(), ARCH_ALIAS[platform.machine()]
def get_model_name():
if args.hf_repo:
return SUPPORTED_HF_MODELS[args.hf_repo]["model_name"]
return os.path.basename(os.path.normpath(args.model_dir))
def run_command(command, shell=False, log_step=None):
"""Run a system command and ensure it succeeds."""
if log_step:
log_file = os.path.join(args.log_dir, log_step + ".log")
with open(log_file, "w") as f:
try:
subprocess.run(command, shell=shell, check=True, stdout=f, stderr=f)
except subprocess.CalledProcessError as e:
logging.error(f"Error occurred while running command: {e}, check details in {log_file}")
sys.exit(1)
else:
try:
subprocess.run(command, shell=shell, check=True)
except subprocess.CalledProcessError as e:
logging.error(f"Error occurred while running command: {e}")
sys.exit(1)
def prepare_model():
_, arch = system_info()
hf_url = args.hf_repo
model_dir = args.model_dir
quant_type = args.quant_type
quant_embd = args.quant_embd
if hf_url is not None:
# download the model
model_dir = os.path.join(model_dir, SUPPORTED_HF_MODELS[hf_url]["model_name"])
Path(model_dir).mkdir(parents=True, exist_ok=True)
logging.info(f"Downloading model {hf_url} from HuggingFace to {model_dir}...")
run_command(["huggingface-cli", "download", hf_url, "--local-dir", model_dir], log_step="download_model")
elif not os.path.exists(model_dir):
logging.error(f"Model directory {model_dir} does not exist.")
sys.exit(1)
else:
logging.info(f"Loading model from directory {model_dir}.")
gguf_path = os.path.join(model_dir, "ggml-model-" + quant_type + ".gguf")
if not os.path.exists(gguf_path) or os.path.getsize(gguf_path) == 0:
logging.info(f"Converting HF model to GGUF format...")
if quant_type.startswith("tl"):
run_command([sys.executable, "utils/convert-hf-to-gguf-bitnet.py", model_dir, "--outtype", quant_type, "--quant-embd"], log_step="convert_to_tl")
else: # i2s
# convert to f32
run_command([sys.executable, "utils/convert-hf-to-gguf-bitnet.py", model_dir, "--outtype", "f32"], log_step="convert_to_f32_gguf")
f32_model = os.path.join(model_dir, "ggml-model-f32.gguf")
i2s_model = os.path.join(model_dir, "ggml-model-i2_s.gguf")
# quantize to i2s
if platform.system() != "Windows":
if quant_embd:
run_command(["./build/bin/llama-quantize", "--token-embedding-type", "f16", f32_model, i2s_model, "I2_S", "1", "1"], log_step="quantize_to_i2s")
else:
run_command(["./build/bin/llama-quantize", f32_model, i2s_model, "I2_S", "1"], log_step="quantize_to_i2s")
else:
if quant_embd:
run_command(["./build/bin/Release/llama-quantize", "--token-embedding-type", "f16", f32_model, i2s_model, "I2_S", "1", "1"], log_step="quantize_to_i2s")
else:
run_command(["./build/bin/Release/llama-quantize", f32_model, i2s_model, "I2_S", "1"], log_step="quantize_to_i2s")
logging.info(f"GGUF model saved at {gguf_path}")
else:
logging.info(f"GGUF model already exists at {gguf_path}")
def setup_gguf():
# Install the pip package
run_command([sys.executable, "-m", "pip", "install", "3rdparty/llama.cpp/gguf-py"], log_step="install_gguf")
def gen_code():
_, arch = system_info()
if arch == "arm64":
if args.use_pretuned:
pretuned_kernels = os.path.join("preset_kernels", get_model_name())
if not os.path.exists(pretuned_kernels):
logging.error(f"Pretuned kernels not found for model {args.hf_repo}")
sys.exit(1)
if args.quant_type == "tl1":
shutil.copyfile(os.path.join(pretuned_kernels, "bitnet-lut-kernels-tl1.h"), "include/bitnet-lut-kernels.h")
shutil.copyfile(os.path.join(pretuned_kernels, "kernel_config_tl1.ini"), "include/kernel_config.ini")
elif args.quant_type == "tl2":
shutil.copyfile(os.path.join(pretuned_kernels, "bitnet-lut-kernels-tl2.h"), "include/bitnet-lut-kernels.h")
shutil.copyfile(os.path.join(pretuned_kernels, "kernel_config_tl2.ini"), "include/kernel_config.ini")
if get_model_name() == "bitnet_b1_58-large":
run_command([sys.executable, "utils/codegen_tl1.py", "--model", "bitnet_b1_58-large", "--BM", "256,128,256", "--BK", "128,64,128", "--bm", "32,64,32"], log_step="codegen")
elif get_model_name() == "Llama3-8B-1.58-100B-tokens":
run_command([sys.executable, "utils/codegen_tl1.py", "--model", "Llama3-8B-1.58-100B-tokens", "--BM", "256,128,256,128", "--BK", "128,64,128,64", "--bm", "32,64,32,64"], log_step="codegen")
elif get_model_name() == "bitnet_b1_58-3B":
run_command([sys.executable, "utils/codegen_tl1.py", "--model", "bitnet_b1_58-3B", "--BM", "160,320,320", "--BK", "64,128,64", "--bm", "32,64,32"], log_step="codegen")
else:
raise NotImplementedError()
else:
if args.use_pretuned:
# cp preset_kernels/model_name/bitnet-lut-kernels_tl1.h to include/bitnet-lut-kernels.h
pretuned_kernels = os.path.join("preset_kernels", get_model_name())
if not os.path.exists(pretuned_kernels):
logging.error(f"Pretuned kernels not found for model {args.hf_repo}")
sys.exit(1)
shutil.copyfile(os.path.join(pretuned_kernels, "bitnet-lut-kernels-tl2.h"), "include/bitnet-lut-kernels.h")
if get_model_name() == "bitnet_b1_58-large":
run_command([sys.executable, "utils/codegen_tl2.py", "--model", "bitnet_b1_58-large", "--BM", "256,128,256", "--BK", "96,192,96", "--bm", "32,32,32"], log_step="codegen")
elif get_model_name() == "Llama3-8B-1.58-100B-tokens":
run_command([sys.executable, "utils/codegen_tl2.py", "--model", "Llama3-8B-1.58-100B-tokens", "--BM", "256,128,256,128", "--BK", "96,96,96,96", "--bm", "32,32,32,32"], log_step="codegen")
elif get_model_name() == "bitnet_b1_58-3B":
run_command([sys.executable, "utils/codegen_tl2.py", "--model", "bitnet_b1_58-3B", "--BM", "160,320,320", "--BK", "96,96,96", "--bm", "32,32,32"], log_step="codegen")
else:
raise NotImplementedError()
def compile():
# Check if cmake is installed
cmake_exists = subprocess.run(["cmake", "--version"], capture_output=True)
if cmake_exists.returncode != 0:
logging.error("Cmake is not available. Please install CMake and try again.")
sys.exit(1)
_, arch = system_info()
if arch not in COMPILER_EXTRA_ARGS.keys():
logging.error(f"Arch {arch} is not supported yet")
exit(0)
logging.info("Compiling the code using CMake.")
run_command(["cmake", "-B", "build", *COMPILER_EXTRA_ARGS[arch], *OS_EXTRA_ARGS.get(platform.system(), [])], log_step="generate_build_files")
# run_command(["cmake", "--build", "build", "--target", "llama-cli", "--config", "Release"])
run_command(["cmake", "--build", "build", "--config", "Release"], log_step="compile")
def main():
setup_gguf()
gen_code()
compile()
prepare_model()
def parse_args():
_, arch = system_info()
parser = argparse.ArgumentParser(description='Setup the environment for running the inference')
parser.add_argument("--hf-repo", "-hr", type=str, help="Model used for inference", choices=SUPPORTED_HF_MODELS.keys())
parser.add_argument("--model-dir", "-md", type=str, help="Directory to save/load the model", default="models")
parser.add_argument("--log-dir", "-ld", type=str, help="Directory to save the logging info", default="logs")
parser.add_argument("--quant-type", "-q", type=str, help="Quantization type", choices=SUPPORTED_QUANT_TYPES[arch], default="i2_s")
parser.add_argument("--quant-embd", action="store_true", help="Quantize the embeddings to f16")
parser.add_argument("--use-pretuned", "-p", action="store_true", help="Use the pretuned kernel parameters")
return parser.parse_args()
def signal_handler(sig, frame):
logging.info("Ctrl+C pressed, exiting...")
sys.exit(0)
if __name__ == "__main__":
signal.signal(signal.SIGINT, signal_handler)
args = parse_args()
Path(args.log_dir).mkdir(parents=True, exist_ok=True)
logging.basicConfig(level=logging.INFO)
main()