mirror of
https://github.com/huggingface/text-generation-inference.git
synced 2025-04-21 14:52:20 +00:00
* feat: add ruff and resolve issue * fix: update client exports and adjust after rebase * fix: adjust syntax to avoid circular import * fix: adjust client ruff settings * fix: lint and refactor import check and avoid model enum as global names * fix: improve fbgemm_gpu check and lints * fix: update lints * fix: prefer comparing model enum over str * fix: adjust lints and ignore specific rules * fix: avoid unneeded quantize check
74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
import torch
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from loguru import logger
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import os
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import importlib.util
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def is_ipex_available():
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return importlib.util.find_spec("intel_extension_for_pytorch") is not None
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def get_cuda_free_memory(device, memory_fraction):
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total_free_memory, _ = torch.cuda.mem_get_info(device)
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total_gpu_memory = torch.cuda.get_device_properties(device).total_memory
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free_memory = max(0, total_free_memory - (1 - memory_fraction) * total_gpu_memory)
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return free_memory
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def get_xpu_free_memory(device, memory_fraction):
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total_memory = torch.xpu.get_device_properties(device).total_memory
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device_id = device.index
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memory_fraction = float(os.getenv("XPU_MEMORY_FRACTION", "1.0"))
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free_memory = max(
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0,
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int(
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total_memory * 0.9 * memory_fraction - torch.xpu.memory_reserved(device_id)
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),
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)
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return free_memory
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def get_cpu_free_memory(device, memory_fraction):
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import psutil
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from text_generation_server.utils.dist import WORLD_SIZE
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mem = psutil.virtual_memory()
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free_memory = int(mem.available * 0.95 / WORLD_SIZE)
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return free_memory
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def noop(*args, **kwargs):
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pass
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SYSTEM = None
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if torch.version.hip is not None:
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SYSTEM = "rocm"
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empty_cache = torch.cuda.empty_cache
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synchronize = torch.cuda.synchronize
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get_free_memory = get_cuda_free_memory
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elif torch.version.cuda is not None and torch.cuda.is_available():
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SYSTEM = "cuda"
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empty_cache = torch.cuda.empty_cache
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synchronize = torch.cuda.synchronize
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get_free_memory = get_cuda_free_memory
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elif is_ipex_available():
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SYSTEM = "ipex"
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if hasattr(torch, "xpu") and torch.xpu.is_available():
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empty_cache = torch.xpu.empty_cache
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synchronize = torch.xpu.synchronize
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get_free_memory = get_xpu_free_memory
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else:
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empty_cache = noop
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synchronize = noop
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get_free_memory = get_cpu_free_memory
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else:
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SYSTEM = "cpu"
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empty_cache = noop
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synchronize = noop
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get_free_memory = get_cpu_free_memory
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logger.info(f"Detected system {SYSTEM}")
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