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# Copyright 2022 The MT3 Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Simple debugging utility for printing out task contents."""
import re
from absl import app
from absl import flags
import mt3.tasks # pylint: disable=unused-import
import seqio
import tensorflow as tf
FLAGS = flags.FLAGS
flags.DEFINE_string("task", None, "A registered Task.")
flags.DEFINE_string("task_cache_dir", None, "Directory to use for task cache.")
flags.DEFINE_integer("max_examples", 10,
"Maximum number of examples (-1 for no limit).")
flags.DEFINE_string("format_string", "targets = {targets}",
"Format for printing examples.")
flags.DEFINE_string("split", "train",
"Which split of the dataset, e.g. train or validation.")
flags.DEFINE_integer("sequence_length_inputs", 256,
"Sequence length for inputs.")
flags.DEFINE_integer("sequence_length_targets", 1024,
"Sequence length for targets.")
def main(_):
if FLAGS.task_cache_dir:
seqio.add_global_cache_dirs([FLAGS.task_cache_dir])
task = seqio.get_mixture_or_task(FLAGS.task)
ds = task.get_dataset(
sequence_length={
"inputs": FLAGS.sequence_length_inputs,
"targets": FLAGS.sequence_length_targets,
},
split=FLAGS.split,
use_cached=bool(FLAGS.task_cache_dir),
shuffle=False)
keys = re.findall(r"{([\w+]+)}", FLAGS.format_string)
def _example_to_string(ex):
key_to_string = {}
for k in keys:
if k in ex:
v = ex[k].numpy().tolist()
key_to_string[k] = task.output_features[k].vocabulary.decode(v)
else:
key_to_string[k] = ""
return FLAGS.format_string.format(**key_to_string)
for ex in ds.take(FLAGS.max_examples):
for k, v in ex.items():
print(f"{k}: {tf.shape(v)}")
print(_example_to_string(ex))
print()
if __name__ == "__main__":
flags.mark_flags_as_required(["task"])
app.run(main)
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