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Code Issues Actions 2 Packages Projects Releases Wiki Activity

[docs] Update environment variables documentation (#3957)
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This commit is contained in:
bukejiyu
2025-09-11 12:17:06 +08:00
committed by GitHub
parent 2af0f671b1
commit 2650f58740
5 changed files with 15 additions and 4 deletions
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4
docs/usage/environment_variables.md
View File

@@ -72,7 +72,11 @@ environment_variables: dict[str, Callable[[], Any]] = {
"FD_USE_DEEP_GEMM":
lambda: bool(int(os.getenv("FD_USE_DEEP_GEMM", "0"))),
# Whether to enable model cache feature
"FD_ENABLE_MODEL_LOAD_CACHE": lambda: bool(int(os.getenv("FD_ENABLE_MODEL_LOAD_CACHE", "0"))),
# Whether to use Machete for wint4 dense GEMM.
"FD_USE_MACHETE": lambda: os.getenv("FD_USE_MACHETE", "0"),
}
```

3
docs/zh/usage/environment_variables.md
View File

@@ -72,6 +72,9 @@ environment_variables: dict[str, Callable[[], Any]] = {
"FD_USE_DEEP_GEMM":
lambda: bool(int(os.getenv("FD_USE_DEEP_GEMM", "0"))),
# 是否启用模型权重缓存功能
"FD_ENABLE_MODEL_LOAD_CACHE": lambda: bool(int(os.getenv("FD_ENABLE_MODEL_LOAD_CACHE", "0"))),
# 是否使用 Machete 后端的 wint4 GEMM.
"FD_USE_MACHETE": lambda: os.getenv("FD_USE_MACHETE", "0"),
}

2
fastdeploy/envs.py
View File

@@ -98,7 +98,7 @@ environment_variables: dict[str, Callable[[], Any]] = {
# Whether to use new get_output and save_output method (0 or 1)
"FD_USE_GET_SAVE_OUTPUT_V1": lambda: bool(int(os.getenv("FD_USE_GET_SAVE_OUTPUT_V1", "0"))),
# Whether to enable model cache feature
"FD_ENABLE_MODEL_CACHE": lambda: bool(int(os.getenv("FD_ENABLE_MODEL_CACHE", "0"))),
"FD_ENABLE_MODEL_LOAD_CACHE": lambda: bool(int(os.getenv("FD_ENABLE_MODEL_LOAD_CACHE", "0"))),
}

8
fastdeploy/model_executor/load_weight_utils.py
View File

@@ -79,7 +79,7 @@ def is_weight_cache_enabled(fd_config, weight_cache_path=".cache"):
weight_cache_context = contextlib.nullcontext()
weight_cache_dir = None
enable_cache = False
if envs.FD_ENABLE_MODEL_CACHE:
if envs.FD_ENABLE_MODEL_LOAD_CACHE:
model_weight_cache_path = os.path.join(fd_config.model_config.model, weight_cache_path)
# model_type + quantization + tp_size + ep_size
weight_cache_key = "_".join(
@@ -132,7 +132,11 @@ def save_model(model_arg_name="model", config_arg_name="fd_config"):
with context:
result = func(*args, **kwargs)
if envs.FD_ENABLE_MODEL_CACHE and weight_cache_dir is not None and not os.path.exists(weight_cache_dir):
if (
envs.FD_ENABLE_MODEL_LOAD_CACHE
and weight_cache_dir is not None
and not os.path.exists(weight_cache_dir)
):
assert fd_config.quant_config is not None and getattr(
fd_config.quant_config, "is_checkpoint_bf16", False
), "Save cache only for dynamic quantization"

2
tests/model_loader/test_model_cache.py
View File

@@ -41,7 +41,7 @@ model_param_map = {
"quantizations": [
{
"quant_type": "wint4",
"env": {"FD_ENABLE_MODEL_CACHE": "1"},
"env": {"FD_ENABLE_MODEL_LOAD_CACHE": "1"},
}
],
}