Delete ag4masses/alphageometry/lm_inference_test.py

ag4masses/alphageometry/lm_inference_test.py

@@ -1,89 +0,0 @@
-# Copyright 2023 DeepMind Technologies Limited
-#
-# 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.
-# ==============================================================================
-
-"""Unit tests for lm_inference.py."""
-import os
-import unittest
-
-from absl import flags
-from absl.testing import absltest
-import lm_inference as lm
-
-
-_DATA_PATH = flags.DEFINE_string('data_path', '', 'path to ckpt and vocab.')
-_MELIAD_PATH = flags.DEFINE_string(
-    'meliad_path', '', 'path to meliad repository.'
-)  # pylint: disable=line-too-long
-
-
-class LmInferenceTest(unittest.TestCase):
-
-  @classmethod
-  def setUpClass(cls):
-    super().setUpClass()
-    gin_file = [
-        'base_htrans.gin',
-        'size/medium_150M.gin',
-        'options/positions_t5.gin',
-        'options/lr_cosine_decay.gin',
-        'options/seq_1024_nocache.gin',
-        'geometry_150M_generate.gin',
-    ]
-
-    gin_param = [
-        'DecoderOnlyLanguageModelGenerate.output_token_losses=True',
-        'TransformerTaskConfig.batch_size=2',
-        'TransformerTaskConfig.sequence_length=128',
-        'Trainer.restore_state_variables=False',
-    ]
-
-    gin_search_paths = [
-        os.path.join(_MELIAD_PATH.value, 'transformer/configs'),
-        os.getcwd(),
-    ]
-
-    vocab_path = os.path.join(_DATA_PATH.value, 'geometry.757.model')
-
-    lm.parse_gin_configuration(gin_file, gin_param, gin_paths=gin_search_paths)
-
-    cls.loaded_lm = lm.LanguageModelInference(
-        vocab_path, _DATA_PATH.value, mode='beam_search'
-    )
-
-  def test_lm_decode(self):
-    outputs = LmInferenceTest.loaded_lm.beam_decode(
-        '{S} a : ; b : ; c : ; d : T a b c d 00 T a c b d 01 ? T a d b c'
-        ' {F1} x00',
-        eos_tokens=[';'],
-    )
-    self.assertEqual(
-        outputs['seqs_str'],
-        ['e : D a b c e 02 D a c b e 03 ;', 'e : C a c e 02 C b d e 03 ;'],
-    )
-
-  def test_lm_score_may_fail_numerically_for_external_meliad(self):
-    outputs = LmInferenceTest.loaded_lm.beam_decode(
-        '{S} a : ; b : ; c : ; d : T a b c d 00 T a c b d 01 ? T a d b c'
-        ' {F1} x00',
-        eos_tokens=[';'],
-    )
-    self.assertEqual(
-        outputs['scores'],
-        [-1.18607294559478759765625, -1.10228693485260009765625],
-    )
-
-
-if __name__ == '__main__':
-  absltest.main()