explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-01-27 09:44:36 +03:00
Code Issues Packages Projects Releases Wiki Activity

fixing output sample to proper 2D array

Browse Source
This commit is contained in:
svlandeg 2020-09-17 22:34:36 +02:00
parent 35a3931064
commit e4fc7e0222
1 changed files with 14 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
spacy/cli/debug_model.py
View File

@ -60,13 +60,12 @@ def debug_model_cli(
msg.info(f"Fixing random seed: {seed}") msg.info(f"Fixing random seed: {seed}")
fix_random_seed(seed) fix_random_seed(seed)
pipe = nlp.get_pipe(component) pipe = nlp.get_pipe(component)
if hasattr(pipe, "model"): if not hasattr(pipe, "model"):
model = pipe.model
else:
msg.fail( msg.fail(
f"The component '{component}' does not specify an object that holds a Model.", f"The component '{component}' does not specify an object that holds a Model.",
exits=1, exits=1,
) )
model = pipe.model
debug_model(model, print_settings=print_settings) debug_model(model, print_settings=print_settings)
@ -87,7 +86,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
# STEP 1: Initializing the model and printing again # STEP 1: Initializing the model and printing again
X = _get_docs() X = _get_docs()
Y = _get_output(model.ops.xp) Y = _get_output(model.ops)
# The output vector might differ from the official type of the output layer # The output vector might differ from the official type of the output layer
with data_validation(False): with data_validation(False):
model.initialize(X=X, Y=Y) model.initialize(X=X, Y=Y)
@ -113,9 +112,11 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
msg.divider(f"STEP 3 - prediction") msg.divider(f"STEP 3 - prediction")
msg.info(str(prediction)) msg.info(str(prediction))
msg.good(f"Succesfully ended analysis - model looks good!")
def get_gradient(model, Y): def get_gradient(model, Y):
goldY = _get_output(model.ops.xp) goldY = _get_output(model.ops)
return Y - goldY return Y - goldY
@ -133,8 +134,14 @@ def _get_docs(lang: str = "en"):
return list(nlp.pipe(_sentences())) return list(nlp.pipe(_sentences()))
def _get_output(xp): def _get_output(ops):
return xp.asarray([i + 10 for i, _ in enumerate(_get_docs())], dtype="float32") docs = len(_get_docs())
labels = 6
output = ops.alloc2f(d0=docs, d1=labels)
for i in range(docs):
for j in range(labels):
output[i, j] = 1 / (i+j+0.01)
return ops.xp.asarray(output)
def _print_model(model, print_settings): def _print_model(model, print_settings):