ai-content-maker/.venv/Lib/site-packages/spacy_loggers/cupy.py

72 lines
2.4 KiB
Python

"""
A logger that queries CuPy metrics and passes that information to downstream loggers.
"""
from typing import Dict, Any, Optional, IO
import sys
from spacy import Language
from thinc.backends import context_pools
from thinc.util import has_cupy_gpu
from .util import LoggerT
def cupy_logger_v1(
prefix: str = "cupy",
) -> LoggerT:
"""Creates a logger that queries CuPy metrics and passes that information to downstream loggers.
Args:
prefix (str):
All metric names are prefixed with this string using dot notation, e.g: `<prefix>.<metric>`.
Returns:
LoggerT: Logger instance.
"""
try:
import cupy
except ImportError:
raise ImportError(
"The 'cupy' library could not be found - did you install it? "
"Alternatively, specify the 'ConsoleLogger' in the "
"'training.logger' config section, instead of the 'CuPyLogger'."
)
if not has_cupy_gpu:
raise ValueError(
"The 'cupy' library could be loaded but GPU support couldn't be initialized - "
"do you have the necessary CUDA libraries installed?"
)
def setup_logger(nlp: Language, stdout: IO = sys.stdout, stderr: IO = sys.stderr):
def to_mib(bytes: int) -> float:
return bytes / (1024.0**2)
def log_step(info: Optional[Dict[str, Any]]):
if info is None:
return
# We cannot rely on cupy.cuda.get_default_memory_pool() as thinc can
# use its own allocator/pool for interop with PyTorch/TensorFlow.
cupy_memory_pool = cupy.cuda.get_allocator().__self__
thinc_pool = context_pools.get()
if thinc_pool.get("pytorch") == cupy_memory_pool:
pool_source = "pytorch"
elif thinc_pool.get("tensorflow") == cupy_memory_pool:
pool_source = "tensorflow"
else:
pool_source = "default"
info[f"{prefix}.pool.source"] = pool_source
info[f"{prefix}.pool.acquired_mib"] = to_mib(cupy_memory_pool.total_bytes())
info[f"{prefix}.pool.used_mib"] = to_mib(cupy_memory_pool.used_bytes())
info[f"{prefix}.pool.free_mib"] = to_mib(cupy_memory_pool.free_bytes())
info[f"{prefix}.pool.num_free_blocks"] = cupy_memory_pool.n_free_blocks()
def finalize():
pass
return log_step, finalize
return setup_logger