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Add compat for thinc.neural.optimizers.Optimizer

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This commit is contained in:
Matthew Honnibal 2017-10-27 10:23:49 +00:00
parent 75a637fa43
commit 4d048e94d3
2 changed files with 10 additions and 5 deletions
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4
spacy/compat.py
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@ -30,6 +30,10 @@ try:
except ImportError: except ImportError:
cupy = None cupy = None
try:
from thinc.optimizers import Optimizer
except ImportError:
from thinc.optimizers import Adam as Optimizer
pickle = pickle pickle = pickle
copy_reg = copy_reg copy_reg = copy_reg

11
spacy/language.py
View File

@ -3,7 +3,6 @@ from __future__ import absolute_import, unicode_literals
from contextlib import contextmanager from contextlib import contextmanager
from thinc.neural import Model from thinc.neural import Model
from thinc.neural.optimizers import Adam
import random import random
import ujson import ujson
from collections import OrderedDict from collections import OrderedDict
@ -21,6 +20,7 @@ from .syntax.parser import get_templates
from .pipeline import NeuralDependencyParser, TokenVectorEncoder, NeuralTagger from .pipeline import NeuralDependencyParser, TokenVectorEncoder, NeuralTagger
from .pipeline import NeuralEntityRecognizer, SimilarityHook, TextCategorizer from .pipeline import NeuralEntityRecognizer, SimilarityHook, TextCategorizer
from .compat import Optimizer
from .compat import json_dumps, izip, copy_reg from .compat import json_dumps, izip, copy_reg
from .scorer import Scorer from .scorer import Scorer
from ._ml import link_vectors_to_models from ._ml import link_vectors_to_models
@ -359,7 +359,8 @@ class Language(object):
return return
if sgd is None: if sgd is None:
if self._optimizer is None: if self._optimizer is None:
self._optimizer = Adam(Model.ops, 0.001) self._optimizer = Optimizer(Model.ops, 0.001,
beta1=0.9, beta2=0.0, nesterov=True)
sgd = self._optimizer sgd = self._optimizer
grads = {} grads = {}
def get_grads(W, dW, key=None): def get_grads(W, dW, key=None):
@ -400,8 +401,8 @@ class Language(object):
eps = util.env_opt('optimizer_eps', 1e-08) eps = util.env_opt('optimizer_eps', 1e-08)
L2 = util.env_opt('L2_penalty', 1e-6) L2 = util.env_opt('L2_penalty', 1e-6)
max_grad_norm = util.env_opt('grad_norm_clip', 1.) max_grad_norm = util.env_opt('grad_norm_clip', 1.)
self._optimizer = Adam(Model.ops, learn_rate, L2=L2, beta1=beta1, self._optimizer = Optimizer(Model.ops, learn_rate, L2=L2, beta1=beta1,
beta2=beta2, eps=eps) beta2=beta2, eps=eps, nesterov=True)
self._optimizer.max_grad_norm = max_grad_norm self._optimizer.max_grad_norm = max_grad_norm
self._optimizer.device = device self._optimizer.device = device
return self._optimizer return self._optimizer
@ -440,7 +441,7 @@ class Language(object):
eps = util.env_opt('optimizer_eps', 1e-08) eps = util.env_opt('optimizer_eps', 1e-08)
L2 = util.env_opt('L2_penalty', 1e-6) L2 = util.env_opt('L2_penalty', 1e-6)
max_grad_norm = util.env_opt('grad_norm_clip', 1.) max_grad_norm = util.env_opt('grad_norm_clip', 1.)
self._optimizer = Adam(Model.ops, learn_rate, L2=L2, beta1=beta1, self._optimizer = Optimizer(Model.ops, learn_rate, L2=L2, beta1=beta1,
beta2=beta2, eps=eps) beta2=beta2, eps=eps)
self._optimizer.max_grad_norm = max_grad_norm self._optimizer.max_grad_norm = max_grad_norm
self._optimizer.device = device self._optimizer.device = device