mirror of https://github.com/explosion/spaCy.git
42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
from thinc.api import layerize, wrap, noop, chain, concatenate
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from thinc.v2v import Model
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def concatenate_lists(*layers, **kwargs): # pragma: no cover
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"""Compose two or more models `f`, `g`, etc, such that their outputs are
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concatenated, i.e. `concatenate(f, g)(x)` computes `hstack(f(x), g(x))`
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"""
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if not layers:
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return layerize(noop())
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drop_factor = kwargs.get("drop_factor", 1.0)
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ops = layers[0].ops
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layers = [chain(layer, flatten) for layer in layers]
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concat = concatenate(*layers)
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def concatenate_lists_fwd(Xs, drop=0.0):
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if drop is not None:
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drop *= drop_factor
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lengths = ops.asarray([len(X) for X in Xs], dtype="i")
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flat_y, bp_flat_y = concat.begin_update(Xs, drop=drop)
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ys = ops.unflatten(flat_y, lengths)
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def concatenate_lists_bwd(d_ys, sgd=None):
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return bp_flat_y(ops.flatten(d_ys), sgd=sgd)
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return ys, concatenate_lists_bwd
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model = wrap(concatenate_lists_fwd, concat)
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return model
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@layerize
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def flatten(seqs, drop=0.0):
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ops = Model.ops
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lengths = ops.asarray([len(seq) for seq in seqs], dtype="i")
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def finish_update(d_X, sgd=None):
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return ops.unflatten(d_X, lengths, pad=0)
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X = ops.flatten(seqs, pad=0)
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return X, finish_update
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