spaCy/spacy/ml/tb_framework.py
2020-06-20 14:47:17 +02:00

87 lines
2.8 KiB
Python

from thinc.api import Model, noop, use_ops, Linear
from ..syntax._parser_model import ParserStepModel
def TransitionModel(tok2vec, lower, upper, unseen_classes=set()):
"""Set up a stepwise transition-based model"""
if upper is None:
has_upper = False
upper = noop()
else:
has_upper = True
# don't define nO for this object, because we can't dynamically change it
return Model(
name="parser_model",
forward=forward,
dims={"nI": tok2vec.get_dim("nI") if tok2vec.has_dim("nI") else None},
layers=[tok2vec, lower, upper],
refs={"tok2vec": tok2vec, "lower": lower, "upper": upper},
init=init,
attrs={
"has_upper": has_upper,
"unseen_classes": set(unseen_classes),
"resize_output": resize_output,
},
)
def forward(model, X, is_train):
step_model = ParserStepModel(
X,
model.layers,
unseen_classes=model.attrs["unseen_classes"],
train=is_train,
has_upper=model.attrs["has_upper"],
)
return step_model, step_model.finish_steps
def init(model, X=None, Y=None):
tok2vec = model.get_ref("tok2vec").initialize(X=X)
lower = model.get_ref("lower").initialize()
if model.attrs["has_upper"]:
statevecs = model.ops.alloc2f(2, lower.get_dim("nO"))
model.get_ref("upper").initialize(X=statevecs)
def resize_output(model, new_nO):
tok2vec = model.get_ref("tok2vec")
lower = model.get_ref("lower")
upper = model.get_ref("upper")
if not model.attrs["has_upper"]:
if lower.has_dim("nO") is None:
lower.set_dim("nO", new_nO)
return
elif upper.has_dim("nO") is None:
upper.set_dim("nO", new_nO)
return
elif new_nO == upper.get_dim("nO"):
return
smaller = upper
nI = None
if smaller.has_dim("nI"):
nI = smaller.get_dim("nI")
with use_ops("numpy"):
larger = Linear(nO=new_nO, nI=nI)
larger.init = smaller.init
# it could be that the model is not initialized yet, then skip this bit
if nI:
larger_W = larger.ops.alloc2f(new_nO, nI)
larger_b = larger.ops.alloc1f(new_nO)
smaller_W = smaller.get_param("W")
smaller_b = smaller.get_param("b")
# Weights are stored in (nr_out, nr_in) format, so we're basically
# just adding rows here.
if smaller.has_dim("nO"):
larger_W[: smaller.get_dim("nO")] = smaller_W
larger_b[: smaller.get_dim("nO")] = smaller_b
for i in range(smaller.get_dim("nO"), new_nO):
model.attrs["unseen_classes"].add(i)
larger.set_param("W", larger_W)
larger.set_param("b", larger_b)
model._layers[-1] = larger
model.set_ref("upper", larger)
return model