mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 02:16:32 +03:00
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
from functools import partial
|
|
from typing import Type, Callable, TYPE_CHECKING
|
|
|
|
from thinc.layers import with_nvtx_range
|
|
from thinc.model import Model, wrap_model_recursive
|
|
|
|
from ..util import registry
|
|
|
|
if TYPE_CHECKING:
|
|
# This lets us add type hints for mypy etc. without causing circular imports
|
|
from ..language import Language # noqa: F401
|
|
|
|
|
|
@registry.callbacks("spacy.models_with_nvtx_range.v1")
|
|
def create_models_with_nvtx_range(
|
|
forward_color: int = -1, backprop_color: int = -1
|
|
) -> Callable[["Language"], "Language"]:
|
|
def models_with_nvtx_range(nlp):
|
|
pipes = [
|
|
pipe
|
|
for _, pipe in nlp.components
|
|
if hasattr(pipe, "is_trainable") and pipe.is_trainable
|
|
]
|
|
|
|
# We need process all models jointly to avoid wrapping callbacks twice.
|
|
models = Model(
|
|
"wrap_with_nvtx_range",
|
|
forward=lambda model, X, is_train: ...,
|
|
layers=[pipe.model for pipe in pipes],
|
|
)
|
|
|
|
for node in models.walk():
|
|
with_nvtx_range(
|
|
node, forward_color=forward_color, backprop_color=backprop_color
|
|
)
|
|
|
|
return nlp
|
|
|
|
return models_with_nvtx_range
|