Unavailability of K=32 shot data

[avyavkumar]

Hi,

From https://github.com/iesl/leopard, it looks like data for K=32 is missing. Is there a workaround for this issue?

When I try to fine-tune the models, I get this result -

2022-05-07 12:15:51.681381: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2022-05-07 12:15:51.685349: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2199995000 Hz
2022-05-07 12:15:51.685615: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x2a7e100 executing computations on platform Host. Devices:
2022-05-07 12:15:51.685654: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint32 = np.dtype([("qint32", np.int32, 1)])
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  np_resource = np.dtype([("resource", np.ubyte, 1)])
run_classifier_pretrain.py:1763: UserWarning: Flag --data_dir has a non-None default value; therefore, mark_flag_as_required will pass even if flag is not specified in the command line!
  flags.mark_flag_as_required("data_dir")
run_classifier_pretrain.py:1764: UserWarning: Flag --task_train_files has a non-None default value; therefore, mark_flag_as_required will pass even if flag is not specified in the command line!
  flags.mark_flag_as_required("task_train_files")
run_classifier_pretrain.py:1765: UserWarning: Flag --vocab_file has a non-None default value; therefore, mark_flag_as_required will pass even if flag is not specified in the command line!
  flags.mark_flag_as_required("vocab_file")
run_classifier_pretrain.py:1766: UserWarning: Flag --bert_config_file has a non-None default value; therefore, mark_flag_as_required will pass even if flag is not specified in the command line!
  flags.mark_flag_as_required("bert_config_file")
run_classifier_pretrain.py:1767: UserWarning: Flag --output_dir has a non-None default value; therefore, mark_flag_as_required will pass even if flag is not specified in the command line!
  flags.mark_flag_as_required("output_dir")
INFO:tensorflow:GPU available: False
INFO:tensorflow:Device is available but not used by distribute strategy: /device:XLA_CPU:0
WARNING:tensorflow:Not all devices in `tf.distribute.Strategy` are visible to TensorFlow.
WARNING:tensorflow:From run_classifier_pretrain.py:1537: tf_record_iterator (from tensorflow.python.lib.io.tf_record) is deprecated and will be removed in a future version.
Instructions for updating:
Use eager execution and: 
`tf.data.TFRecordDataset(path)`
Traceback (most recent call last):
  File "run_classifier_pretrain.py", line 1768, in <module>
    tf.app.run()
  File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py", line 125, in run
    _sys.exit(main(argv))
  File "run_classifier_pretrain.py", line 1688, in main
    neval_examples, nexamples_per_file_eval_train = read_data_sizes_from_tfrecord([task_eval_files[0]])
  File "run_classifier_pretrain.py", line 1537, in read_data_sizes_from_tfrecord
    for record in tf.python_io.tf_record_iterator(fn):
  File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/lib/io/tf_record.py", line 174, in tf_record_iterator
    compat.as_bytes(path), 0, compat.as_bytes(compression_type), status)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
    c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.NotFoundError: data/leopard-master/data/tf_record/airline/airline_train_4_32.tf_record; No such file or directory