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removing unused imports
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910026582d
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04b55bf054
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@ -2,19 +2,11 @@ from dataclasses import dataclass
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from thinc.api import Model, Linear, Relu, Dropout, chain, noop
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from thinc.types import Floats2d, Floats1d, Ints2d, Ragged
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from typing import List, Callable, Tuple, Any
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from typing import List, Callable, Tuple, Any
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from ...tokens import Doc
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from ...util import registry
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from .coref_util import (
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get_predicted_clusters,
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get_candidate_mentions,
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select_non_crossing_spans,
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make_clean_doc,
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create_gold_scores,
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logsumexp,
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topk,
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)
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from .coref_util import get_candidate_mentions, select_non_crossing_spans, topk
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@registry.architectures("spacy.Coref.v1")
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@ -172,8 +164,8 @@ def span_embeddings_forward(
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# first and last token embeds
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# XXX probably would be faster to get these at once
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#starts = [tokvecs[ii] for ii in mentions[:, 0]]
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#ends = [tokvecs[jj] for jj in mentions[:, 1]]
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# starts = [tokvecs[ii] for ii in mentions[:, 0]]
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# ends = [tokvecs[jj] for jj in mentions[:, 1]]
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starts, ends = zip(*[(tokvecs[ii], tokvecs[jj]) for ii, jj in mentions])
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starts = ops.asarray2f(starts)
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@ -44,6 +44,7 @@ def topk(xp, arr, k, axis=None):
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def logsumexp(xp, arr, axis=None):
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"""Emulate torch.logsumexp by returning the log of summed exponentials
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along each row in the given dimension.
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TODO: currently not used?
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Reduces a 2d array to 1d."""
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# from slide 5 here:
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@ -217,6 +218,7 @@ def get_clusters_from_doc(doc) -> List[List[Tuple[int, int]]]:
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def make_clean_doc(nlp, doc):
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"""Return a doc with raw data but not span annotations."""
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# Surely there is a better way to do this?
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# TODO: currently not used?
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sents = [tok.is_sent_start for tok in doc]
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words = [tok.text for tok in doc]
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@ -17,7 +17,6 @@ from ..ml.models.coref_util import (
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create_gold_scores,
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MentionClusters,
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get_clusters_from_doc,
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logsumexp,
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get_predicted_clusters,
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DEFAULT_CLUSTER_PREFIX,
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doc2clusters,
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