explosion/spaCy
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use divider inbetween steps

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This commit is contained in:
svlandeg 2020-07-31 18:06:48 +02:00
parent 51ffc4a166
commit 9b719dfb1a
1 changed files with 5 additions and 4 deletions
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9
spacy/cli/debug_model.py
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@ -84,7 +84,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
# STEP 0: Printing before training # STEP 0: Printing before training
msg.info(f"Analysing model with ID {model.id}") msg.info(f"Analysing model with ID {model.id}")
if print_settings.get("print_before_training"): if print_settings.get("print_before_training"):
msg.info(f"Before training:") msg.divider(f"STEP 0 - before training")
_print_model(model, print_settings) _print_model(model, print_settings)
# STEP 1: Initializing the model and printing again # STEP 1: Initializing the model and printing again
@ -94,7 +94,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
with data_validation(False): with data_validation(False):
model.initialize(X=_get_docs(), Y=Y) model.initialize(X=_get_docs(), Y=Y)
if print_settings.get("print_after_init"): if print_settings.get("print_after_init"):
msg.info(f"After initialization:") msg.divider(f"STEP 1 - after initialization")
_print_model(model, print_settings) _print_model(model, print_settings)
# STEP 2: Updating the model and printing again # STEP 2: Updating the model and printing again
@ -106,13 +106,14 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
get_dX(dY) get_dX(dY)
model.finish_update(optimizer) model.finish_update(optimizer)
if print_settings.get("print_after_training"): if print_settings.get("print_after_training"):
msg.info(f"After training:") msg.divider(f"STEP 2 - after training")
_print_model(model, print_settings) _print_model(model, print_settings)
# STEP 3: the final prediction # STEP 3: the final prediction
prediction = model.predict(_get_docs()) prediction = model.predict(_get_docs())
if print_settings.get("print_prediction"): if print_settings.get("print_prediction"):
msg.info(f"Prediction:", str(prediction)) msg.divider(f"STEP 3 - prediction")
msg.info(str(prediction))
def get_gradient(model, Y): def get_gradient(model, Y):