explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-01-26 17:24:41 +03:00
Code Issues Packages Projects Releases Wiki Activity

hack for tok2vec listener

Browse Source
This commit is contained in:
svlandeg 2020-09-18 16:43:15 +02:00
parent e4fc7e0222
commit 73ff52b9ec
2 changed files with 19 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
spacy/cli/debug_model.py
View File

@ -66,10 +66,12 @@ def debug_model_cli(
exits=1,
)
model = pipe.model
debug_model(model, print_settings=print_settings)
# call _link_components directly as we won't call nlp.begin_training
nlp._link_components()
debug_model(nlp, model, print_settings=print_settings)
def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None):
def debug_model(nlp, model: Model, *, print_settings: Optional[Dict[str, Any]] = None):
if not isinstance(model, Model):
msg.fail(
f"Requires a Thinc Model to be analysed, but found {type(model)} instead.",
@ -86,10 +88,10 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
# STEP 1: Initializing the model and printing again
X = _get_docs()
Y = _get_output(model.ops)
goldY = _get_output(model.ops)
# The output vector might differ from the official type of the output layer
with data_validation(False):
model.initialize(X=X, Y=Y)
model.initialize(X=X, Y=goldY)
if print_settings.get("print_after_init"):
msg.divider(f"STEP 1 - after initialization")
_print_model(model, print_settings)
@ -97,9 +99,16 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
# STEP 2: Updating the model and printing again
optimizer = Adam(0.001)
set_dropout_rate(model, 0.2)
# ugly hack to deal with Tok2Vec listeners
tok2vec = None
if model.has_ref("tok2vec") and model.get_ref("tok2vec").name == "tok2vec-listener":
tok2vec = nlp.get_pipe("tok2vec")
tok2vec.model.initialize(X=X)
for e in range(3):
Y, get_dX = model.begin_update(_get_docs())
dY = get_gradient(model, Y)
if tok2vec:
tok2vec.predict(X)
Y, get_dX = model.begin_update(X)
dY = get_gradient(goldY, Y)
get_dX(dY)
model.finish_update(optimizer)
if print_settings.get("print_after_training"):
@ -107,7 +116,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
_print_model(model, print_settings)
# STEP 3: the final prediction
prediction = model.predict(_get_docs())
prediction = model.predict(X)
if print_settings.get("print_prediction"):
msg.divider(f"STEP 3 - prediction")
msg.info(str(prediction))
@ -115,8 +124,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
msg.good(f"Succesfully ended analysis - model looks good!")
def get_gradient(model, Y):
goldY = _get_output(model.ops)
def get_gradient(goldY, Y):
return Y - goldY

3
spacy/errors.py
View File

@ -545,7 +545,8 @@ class Errors:
E949 = ("Can only create an alignment when the texts are the same.")
E952 = ("The section '{name}' is not a valid section in the provided config.")
E953 = ("Mismatched IDs received by the Tok2Vec listener: {id1} vs. {id2}")
E954 = ("The Tok2Vec listener did not receive a valid input.")
E954 = ("The Tok2Vec listener did not receive any valid input from an upstream "
"component.")
E955 = ("Can't find table(s) '{table}' for language '{lang}' in spacy-lookups-data.")
E956 = ("Can't find component '{name}' in [components] block in the config. "
"Available components: {opts}")