Francisco Castillo commited on
Commit
695bec7
·
1 Parent(s): a8b61e4

Update loading script

Browse files
ecommerce_reviews_language_drift.py CHANGED
@@ -89,7 +89,7 @@ class ReviewsWithDrift(datasets.GeneratorBasedBuilder):
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  DEFAULT_CONFIG_NAME = "default" # It's not mandatory to have a default configuration. Just use one if it make sense.
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  def _info(self):
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- class_names = ["negative", "positive"]
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  # This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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  features = datasets.Features(
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  # These are the features of your dataset like images, labels ...
@@ -156,18 +156,18 @@ class ReviewsWithDrift(datasets.GeneratorBasedBuilder):
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  def _generate_examples(self, filepath):
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  # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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  # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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- label_mapping = {"positive": 1, "negative": 0}
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  with open(filepath) as csv_file:
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  csv_reader = csv.reader(csv_file)
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  for id_, row in enumerate(csv_reader):
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- prediction_ts,age,gender,context,text,label = row
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  if id_==0:
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  continue
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  yield id_, {
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  "prediction_ts":prediction_ts,
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- "age":age,
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- "gender":gender,
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- "context":context,
 
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  "text": text,
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  "label":label,
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  }
 
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  DEFAULT_CONFIG_NAME = "default" # It's not mandatory to have a default configuration. Just use one if it make sense.
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  def _info(self):
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+ class_names = ["very negative", "negative", "neutral", "positive", "very positive"]
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  # This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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  features = datasets.Features(
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  # These are the features of your dataset like images, labels ...
 
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  def _generate_examples(self, filepath):
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  # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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  # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
 
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  with open(filepath) as csv_file:
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  csv_reader = csv.reader(csv_file)
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  for id_, row in enumerate(csv_reader):
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+ prediction_ts,age,gender,category,language,text,label = row
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  if id_==0:
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  continue
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  yield id_, {
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  "prediction_ts":prediction_ts,
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+ "reviewer_age":age,
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+ "reviewer_gender":gender,
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+ "product_category":category,
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+ "language":language,
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  "text": text,
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  "label":label,
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  }