mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 20:02:53 +08:00
240d6236bc
Some checks failed
Deploy GitHub Pages / deploy (push) Has been cancelled
* fix topk-topp * update * add base_non_truncated
77 lines
2.4 KiB
Markdown
77 lines
2.4 KiB
Markdown
# FastDeploy Environment Variables
|
|
|
|
FastDeploy's environment variables are defined in `fastdeploy/envs.py` at the root of the repository. Below is the documentation:
|
|
|
|
```python
|
|
environment_variables: dict[str, Callable[[], Any]] = {
|
|
# CUDA architecture versions used when building FastDeploy (string list, e.g. [80,90])
|
|
"FD_BUILDING_ARCS":
|
|
lambda: os.getenv("FD_BUILDING_ARCS", "[]"),
|
|
|
|
# Log directory
|
|
"FD_LOG_DIR":
|
|
lambda: os.getenv("FD_LOG_DIR", "log"),
|
|
|
|
# Enable debug mode (0 or 1)
|
|
"FD_DEBUG":
|
|
lambda: os.getenv("FD_DEBUG", "0"),
|
|
|
|
# FastDeploy log retention days
|
|
"FD_LOG_BACKUP_COUNT":
|
|
lambda: os.getenv("FD_LOG_BACKUP_COUNT", "7"),
|
|
|
|
# Model download cache directory
|
|
"FD_MODEL_CACHE":
|
|
lambda: os.getenv("FD_MODEL_CACHE", None),
|
|
|
|
# Maximum number of stop sequences
|
|
"FD_MAX_STOP_SEQS_NUM":
|
|
lambda: os.getenv("FD_MAX_STOP_SEQS_NUM", "5"),
|
|
|
|
# Maximum length of stop sequences
|
|
"FD_STOP_SEQS_MAX_LEN":
|
|
lambda: os.getenv("FD_STOP_SEQS_MAX_LEN", "8"),
|
|
|
|
# GPU devices to use (comma-separated string, e.g. 0,1,2)
|
|
"CUDA_VISIBLE_DEVICES":
|
|
lambda: os.getenv("CUDA_VISIBLE_DEVICES", None),
|
|
|
|
# Whether to use HuggingFace tokenizer (0 or 1)
|
|
"FD_USE_HF_TOKENIZER":
|
|
lambda: os.getenv("FD_USE_HF_TOKENIZER", 0),
|
|
|
|
# ZMQ send high-water mark (HWM) during initialization
|
|
"FD_ZMQ_SNDHWM":
|
|
lambda: os.getenv("FD_ZMQ_SNDHWM", 10000),
|
|
|
|
# Directory for caching KV quantization parameters
|
|
"FD_CACHE_PARAMS":
|
|
lambda: os.getenv("FD_CACHE_PARAMS", "none"),
|
|
|
|
# Attention backend ("NATIVE_ATTN", "APPEND_ATTN", or "MLA_ATTN")
|
|
"FD_ATTENTION_BACKEND":
|
|
lambda: os.getenv("FD_ATTENTION_BACKEND", "APPEND_ATTN"),
|
|
|
|
# Sampling class ("base", "base_non_truncated", "air", or "rejection")
|
|
"FD_SAMPLING_CLASS":
|
|
lambda: os.getenv("FD_SAMPLING_CLASS", "base"),
|
|
|
|
# MoE backend ("cutlass", "marlin", or "triton")
|
|
"FD_MOE_BACKEND":
|
|
lambda: os.getenv("FD_MOE_BACKEND", "cutlass"),
|
|
|
|
# Triton kernel JIT compilation directory
|
|
"FD_TRITON_KERNEL_CACHE_DIR":
|
|
lambda: os.getenv("FD_TRITON_KERNEL_CACHE_DIR", None),
|
|
|
|
# Switch from standalone PD to centralized inference (0 or 1)
|
|
"FD_PD_CHANGEABLE":
|
|
lambda: os.getenv("FD_PD_CHANGEABLE", "1"),
|
|
|
|
# Whether to use DeepGemm for FP8 blockwise MoE.
|
|
"FD_USE_DEEP_GEMM":
|
|
lambda: bool(int(os.getenv("FD_USE_DEEP_GEMM", "1"))),
|
|
|
|
}
|
|
```
|