|
|
|
|
|
import functools |
|
import seqio |
|
import tensorflow_datasets as tfds |
|
from t5.evaluation import metrics |
|
import my_metrics |
|
from t5.data import preprocessors |
|
import t5 |
|
import tensorflow.compat.v1 as tf |
|
|
|
tsv_path = { |
|
"train": "gs://eu-jav-t5x/corpus/labeled/datasetA_train_3categories.tsv", |
|
"validation": "gs://eu-jav-t5x/corpus/labeled/datasetA_test_3categories.tsv", |
|
"test": "gs://eu-jav-t5x/corpus/labeled/ datasetA_test_3categories.tsv" |
|
} |
|
|
|
vocabulary = seqio.SentencePieceVocabulary( |
|
'gs://t5-data/vocabs/mc4.250000.100extra/sentencepiece.model', extra_ids=0) |
|
|
|
DEFAULT_OUTPUT_FEATURES = { |
|
"inputs": |
|
seqio.Feature( |
|
vocabulary=vocabulary, add_eos=True), |
|
"targets": |
|
seqio.Feature( |
|
vocabulary=vocabulary, add_eos=True) |
|
} |
|
|
|
def categorise_preprocessor(ds): |
|
def normalize_text(text): |
|
"""Lowercase and remove quotes from a TensorFlow string.""" |
|
text = tf.strings.regex_replace(text,"'(.*)'", r"\1") |
|
return text |
|
|
|
def to_inputs_and_targets(ex): |
|
"""Map {"source": ..., "source": ...}->{"target": ..., "target": ...}.""" |
|
return { |
|
"inputs": |
|
tf.strings.join( |
|
[normalize_text(ex["source"])]), |
|
"targets": |
|
tf.strings.join( |
|
[normalize_text(ex["target"])]), |
|
} |
|
return ds.map(to_inputs_and_targets, |
|
num_parallel_calls=tf.data.experimental.AUTOTUNE) |
|
|
|
|
|
seqio.TaskRegistry.add( |
|
"classify_tweets", |
|
source=seqio.TextLineDataSource( |
|
split_to_filepattern=tsv_path, |
|
|
|
), |
|
preprocessors=[ |
|
functools.partial( |
|
t5.data.preprocessors.parse_tsv, |
|
field_names=["annotator1","annotator2","annotator3","target","source","id"]), |
|
categorise_preprocessor, |
|
seqio.preprocessors.tokenize_and_append_eos, |
|
], |
|
metric_fns=[metrics.accuracy,my_metrics.f1_macro], |
|
output_features=DEFAULT_OUTPUT_FEATURES, |
|
) |
|
|
|
seqio.TaskRegistry.add( |
|
"classify_tweets_a1", |
|
source=seqio.TextLineDataSource( |
|
split_to_filepattern=tsv_path, |
|
|
|
), |
|
preprocessors=[ |
|
functools.partial( |
|
t5.data.preprocessors.parse_tsv, |
|
field_names=["target","annotator2","annotator3","placeholder","source","id"]), |
|
categorise_preprocessor, |
|
seqio.preprocessors.tokenize_and_append_eos, |
|
], |
|
metric_fns=[metrics.accuracy,my_metrics.f1_macro], |
|
output_features=DEFAULT_OUTPUT_FEATURES, |
|
) |
|
|
|
seqio.TaskRegistry.add( |
|
"classify_tweets_a2", |
|
source=seqio.TextLineDataSource( |
|
split_to_filepattern=tsv_path, |
|
|
|
), |
|
preprocessors=[ |
|
functools.partial( |
|
t5.data.preprocessors.parse_tsv, |
|
field_names=["annotator1","target","annotator3","placeholder","source","id"]), |
|
categorise_preprocessor, |
|
seqio.preprocessors.tokenize_and_append_eos, |
|
], |
|
metric_fns=[metrics.accuracy,my_metrics.f1_macro], |
|
output_features=DEFAULT_OUTPUT_FEATURES, |
|
) |
|
|
|
seqio.TaskRegistry.add( |
|
"classify_tweets_a3", |
|
source=seqio.TextLineDataSource( |
|
split_to_filepattern=tsv_path, |
|
|
|
), |
|
preprocessors=[ |
|
functools.partial( |
|
t5.data.preprocessors.parse_tsv, |
|
field_names=["annotator1","annotator2","target","placeholder","source","id"]), |
|
categorise_preprocessor, |
|
seqio.preprocessors.tokenize_and_append_eos, |
|
], |
|
metric_fns=[metrics.accuracy,my_metrics.f1_macro], |
|
output_features=DEFAULT_OUTPUT_FEATURES, |
|
) |
|
|
