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