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#12789 Replace assert statements with exceptions (#13909)

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* #12789 Replace assert statements with exceptions

* fix-copies: made copy changes to utils_qa.py in examples/pytorch/question-answering and examples/tensorflow/question-answering

* minor refactor for clarity
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Dhananjay Shettigar 2021-10-07 18:39:01 +05:30 committed by GitHub
parent 279ce5b705
commit 319beb64eb
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3 changed files with 36 additions and 24 deletions
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20
examples/flax/question-answering/utils_qa.py
View File

@ -73,10 +73,12 @@ def postprocess_qa_predictions(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 2, "`predictions` should be a tuple with two elements (start_logits, end_logits)." if len(predictions) != 2:
raise ValueError("`predictions` should be a tuple with two elements (start_logits, end_logits).")
all_start_logits, all_end_logits = predictions all_start_logits, all_end_logits = predictions
assert len(predictions[0]) == len(features), f"Got {len(predictions[0])} predictions and {len(features)} features." if len(predictions[0]) != len(features):
raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -212,7 +214,8 @@ def postprocess_qa_predictions(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"
@ -283,12 +286,12 @@ def postprocess_qa_predictions_with_beam_search(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 5, "`predictions` should be a tuple with five elements." if len(predictions) != 5:
raise ValueError("`predictions` should be a tuple with five elements.")
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions
assert len(predictions[0]) == len( if len(predictions[0]) != len(features):
features raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
), f"Got {len(predictions[0])} predicitions and {len(features)} features."
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -400,7 +403,8 @@ def postprocess_qa_predictions_with_beam_search(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"

20
examples/pytorch/question-answering/utils_qa.py
View File

@ -73,10 +73,12 @@ def postprocess_qa_predictions(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 2, "`predictions` should be a tuple with two elements (start_logits, end_logits)." if len(predictions) != 2:
raise ValueError("`predictions` should be a tuple with two elements (start_logits, end_logits).")
all_start_logits, all_end_logits = predictions all_start_logits, all_end_logits = predictions
assert len(predictions[0]) == len(features), f"Got {len(predictions[0])} predictions and {len(features)} features." if len(predictions[0]) != len(features):
raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -212,7 +214,8 @@ def postprocess_qa_predictions(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"
@ -283,12 +286,12 @@ def postprocess_qa_predictions_with_beam_search(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 5, "`predictions` should be a tuple with five elements." if len(predictions) != 5:
raise ValueError("`predictions` should be a tuple with five elements.")
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions
assert len(predictions[0]) == len( if len(predictions[0]) != len(features):
features raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
), f"Got {len(predictions[0])} predicitions and {len(features)} features."
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -400,7 +403,8 @@ def postprocess_qa_predictions_with_beam_search(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"

20
examples/tensorflow/question-answering/utils_qa.py
View File

@ -73,10 +73,12 @@ def postprocess_qa_predictions(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 2, "`predictions` should be a tuple with two elements (start_logits, end_logits)." if len(predictions) != 2:
raise ValueError("`predictions` should be a tuple with two elements (start_logits, end_logits).")
all_start_logits, all_end_logits = predictions all_start_logits, all_end_logits = predictions
assert len(predictions[0]) == len(features), f"Got {len(predictions[0])} predictions and {len(features)} features." if len(predictions[0]) != len(features):
raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -212,7 +214,8 @@ def postprocess_qa_predictions(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"
@ -283,12 +286,12 @@ def postprocess_qa_predictions_with_beam_search(
log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``): log_level (:obj:`int`, `optional`, defaults to ``logging.WARNING``):
``logging`` log level (e.g., ``logging.WARNING``) ``logging`` log level (e.g., ``logging.WARNING``)
""" """
assert len(predictions) == 5, "`predictions` should be a tuple with five elements." if len(predictions) != 5:
raise ValueError("`predictions` should be a tuple with five elements.")
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = predictions
assert len(predictions[0]) == len( if len(predictions[0]) != len(features):
features raise ValueError(f"Got {len(predictions[0])} predictions and {len(features)} features.")
), f"Got {len(predictions[0])} predicitions and {len(features)} features."
# Build a map example to its corresponding features. # Build a map example to its corresponding features.
example_id_to_index = {k: i for i, k in enumerate(examples["id"])} example_id_to_index = {k: i for i, k in enumerate(examples["id"])}
@ -400,7 +403,8 @@ def postprocess_qa_predictions_with_beam_search(
# If we have an output_dir, let's save all those dicts. # If we have an output_dir, let's save all those dicts.
if output_dir is not None: if output_dir is not None:
assert os.path.isdir(output_dir), f"{output_dir} is not a directory." if not os.path.isdir(output_dir):
raise EnvironmentError(f"{output_dir} is not a directory.")
prediction_file = os.path.join( prediction_file = os.path.join(
output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json" output_dir, "predictions.json" if prefix is None else f"{prefix}_predictions.json"