126 lines
3.3 KiB
Python
126 lines
3.3 KiB
Python
import gc
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import threading
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from logging import getLogger
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from os import environ, path
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from typing import Any, Dict, List, Optional, Sequence, Union
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import torch
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from .params import DeviceParams, SizeChart
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logger = getLogger(__name__)
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SAFE_CHARS = "._-"
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def base_join(base: str, tail: str) -> str:
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tail_path = path.relpath(path.normpath(path.join("/", tail)), "/")
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return path.join(base, tail_path)
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def is_debug() -> bool:
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return get_boolean(environ, "DEBUG", False)
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def get_boolean(args: Any, key: str, default_value: bool) -> bool:
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return args.get(key, str(default_value)).lower() in ("1", "t", "true", "y", "yes")
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def get_and_clamp_float(
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args: Any, key: str, default_value: float, max_value: float, min_value=0.0
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) -> float:
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return min(max(float(args.get(key, default_value)), min_value), max_value)
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def get_and_clamp_int(
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args: Any, key: str, default_value: int, max_value: int, min_value=1
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) -> int:
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return min(max(int(args.get(key, default_value)), min_value), max_value)
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def get_from_list(args: Any, key: str, values: Sequence[Any]) -> Optional[Any]:
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selected = args.get(key, None)
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if selected in values:
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return selected
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logger.warn("invalid selection: %s", selected)
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if len(values) > 0:
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return values[0]
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return None
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def get_from_map(args: Any, key: str, values: Dict[str, Any], default: Any) -> Any:
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selected = args.get(key, default)
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if selected in values:
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return values[selected]
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else:
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return values[default]
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def get_not_empty(args: Any, key: str, default: Any) -> Any:
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val = args.get(key, default)
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if val is None or len(val) == 0:
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val = default
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return val
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def get_size(val: Union[int, str, None]) -> Union[int, SizeChart]:
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if val is None:
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return SizeChart.auto
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if type(val) is int:
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return val
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if type(val) is str:
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for size in SizeChart:
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if val == size.name:
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return size
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return int(val)
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raise ValueError("invalid size")
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def run_gc(devices: Optional[List[DeviceParams]] = None):
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logger.debug(
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"running garbage collection with %s active threads", threading.active_count()
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)
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gc.collect()
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if torch.cuda.is_available() and devices is not None:
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for device in [d for d in devices if d.device.startswith("cuda")]:
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logger.debug("running Torch garbage collection for device: %s", device)
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with torch.cuda.device(device.torch_str()):
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torch.cuda.empty_cache()
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torch.cuda.ipc_collect()
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mem_free, mem_total = torch.cuda.mem_get_info()
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logger.debug(
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"remaining CUDA VRAM usage: %s of %s",
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(mem_total - mem_free),
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mem_total,
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)
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def sanitize_name(name):
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return "".join(x for x in name if (x.isalnum() or x in SAFE_CHARS))
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def merge(a, b, path=None):
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"merges b into a"
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if path is None:
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path = []
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for key in b:
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if key in a:
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if isinstance(a[key], dict) and isinstance(b[key], dict):
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merge(a[key], b[key], path + [str(key)])
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elif a[key] == b[key]:
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pass # same leaf value
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else:
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raise Exception("Conflict at %s" % ".".join(path + [str(key)]))
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else:
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a[key] = b[key]
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return a
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