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def label _ vectorizer ( labels , tag _ map ) : Convert list of label strings to padded label IDs using

def label_vectorizer(labels, tag_map):
"""
Convert list of label strings to padded label IDs using a tag mapping.
Parameters:
labels (list of str): List of label strings.
tag_map (dict): Dictionary mapping tags to IDs.
Returns:
label_ids (numpy.ndarray): Padded array of label IDs.
"""
label_ids =[] # It can't be a numpy array yet, since each sentence has a different size
### START CODE HERE ###
# Each element in labels is a string of tags so for each of them:
for element in labels:
# Split it into single tokens. You may use .split function for strings. Be aware to split it by a blank space!
tokens = None
# Use the dictionaty tag_map passed as an argument to the label_vectorizer function
# to make the correspondence between tags and numbers.
element_ids = None
for token in tokens:
element_ids.append(None)
# Append the found ids to corresponding to the current element to label_ids list
label_ids.append(None)
label_ids = np.array(element_ids)
# Pad the elements
label_ids = None
### END CODE HERE ###
return label_ids

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