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VictorSanh commited on
Commit
89fbe42
1 Parent(s): e3e6197

final touches

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Files changed (1) hide show
  1. P3.py +9 -12
P3.py CHANGED
@@ -57,7 +57,7 @@ def load_cached_task(features_dict, tfrecord):
57
  feat: _feature_config(**desc) for feat, desc in features_dict.items()
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  }
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- ds = tf.data.TFRecordDataset(tf.io.gfile.glob([tfrecord])) #TODO handle multiple shards
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  ds = ds.map(
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  lambda pb: tf.io.parse_single_example(pb, feature_description),
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  num_parallel_calls=tf.data.experimental.AUTOTUNE
@@ -85,16 +85,13 @@ def find_task_splits_and_features_dict():
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  """Get the task available (list was pre-computed by `print_data_split_sizes.py`), and get the features for each task."""
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  task_splits_and_features = defaultdict(dict)
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- data = read_from_url(f"{_HUB_PATH}/data_split_sizes.csv")
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- data = [t.strip() for t in data.splitlines()]
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- data = data[1:]
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- data = [t.split("|") for t in data]
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- data = [(t[0], json.loads(t[1])) for t in data]
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-
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- for task_name, split_sizes in data:
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- if "adversarial_qa" not in task_name: #TODO remove
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- continue
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  for split_name in split_sizes.keys():
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  split_info = json.loads(
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  read_from_url(
@@ -102,7 +99,7 @@ def find_task_splits_and_features_dict():
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  )
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  )
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  features_dict = split_info["features"]
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- assert split_info["num_shards"] == 1 #TODO -> change to multiple shards
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  if not task_splits_and_features[task_name]:
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  task_splits_and_features[task_name] = {
@@ -119,7 +116,7 @@ _TASK_SPLITS_AND_FEATURES_DICT = find_task_splits_and_features_dict()
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  _URLs = {
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  task_name: {
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  split_name: {
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- "tfrecord": f"{_DATA_PATH}/{task_name}/{split_name}.tfrecord-00000-of-00001",
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  }
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  for split_name in splits_and_features_dict["splits"]
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  }
 
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  feat: _feature_config(**desc) for feat, desc in features_dict.items()
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  }
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+ ds = tf.data.TFRecordDataset(tf.io.gfile.glob([tfrecord])) # TODO -> handle multiple shards
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  ds = ds.map(
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  lambda pb: tf.io.parse_single_example(pb, feature_description),
63
  num_parallel_calls=tf.data.experimental.AUTOTUNE
 
85
  """Get the task available (list was pre-computed by `print_data_split_sizes.py`), and get the features for each task."""
86
  task_splits_and_features = defaultdict(dict)
87
 
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+ data_split_sizes = read_from_url(f"{_HUB_PATH}/data_split_sizes.csv")
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+ data_split_sizes = [t.strip() for t in data_split_sizes.splitlines()]
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+ data_split_sizes = data_split_sizes[1:]
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+ data_split_sizes = [t.split("|") for t in data_split_sizes]
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+ data_split_sizes = [(t[0], json.loads(t[1])) for t in data_split_sizes]
 
 
 
 
93
 
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+ for task_name, split_sizes in data_split_sizes:
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  for split_name in split_sizes.keys():
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  split_info = json.loads(
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  read_from_url(
 
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  )
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  )
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  features_dict = split_info["features"]
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+ assert split_info["num_shards"] == 1 # TODO -> handle multiple shards
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104
  if not task_splits_and_features[task_name]:
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  task_splits_and_features[task_name] = {
 
116
  _URLs = {
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  task_name: {
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  split_name: {
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+ "tfrecord": f"{_DATA_PATH}/{task_name}/{split_name}.tfrecord-00000-of-00001", # TODO -> handle multiple shards
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  }
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  for split_name in splits_and_features_dict["splits"]
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  }