




"""simple docstring"""

import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin

class     lowercase (      __UpperCAmelCase       ,		unittest.TestCase):
				__lowerCAmelCase      :      Tuple					    =				SpeechaTextaTokenizer
				__lowerCAmelCase      :      List[Any]					    =				False







				def    a_					(							self				:   Dict    ):



					"""simple docstring"""

					super().setUp()

					A_					:			Tuple						=						'''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''    )
					A_					:			Any						=						['''he re</w> 123''', '''here a 1456''']
					A_					:			List[str]						=						dict(zip(_lowerCamelCase ,       range(len(_lowerCamelCase    )    )    )    )

					A_					:			Tuple						=						{'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

					A_					:			int						=						tempfile.mkdtemp()
					A_					:			List[Any]						=						os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES['''vocab_file''']    )
					A_					:			List[Any]						=						os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES['''merges_file''']    )

					with open(self.vocab_file ,       '''w''' ,       encoding='''utf-8'''    ) as fp:
						fp.write(json.dumps(_lowerCamelCase    ) + '''\n'''    )

					with open(self.merges_file ,       '''w'''    ) as fp:
						fp.write('''\n'''.join(_lowerCamelCase    )    )







				def    a_					(							self				:   List[str]    ):



					"""simple docstring"""

					A_					:			Dict						=						list(self.get_tokenizer().get_vocab().keys()    )

					self.assertEqual(vocab_keys[0] ,       '''<s>'''    )
					self.assertEqual(vocab_keys[1] ,       '''<pad>'''    )
					self.assertEqual(vocab_keys[-1] ,       '''vocab'''    )
					self.assertEqual(len(_lowerCamelCase    ) ,       14    )







				def    a_					(							self				:   Optional[int]    ):



					"""simple docstring"""

					self.assertEqual(self.get_tokenizer().vocab_size ,       14    )







				def    a_					(							self				:   Tuple    ):



					"""simple docstring"""

					A_					:			Any						=						SpeechaTextaTokenizer.from_pretrained(self.tmpdirname    )

					# make sure @@ is correctly concatenated
					A_					:			Optional[int]						=						[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
					A_					:			Dict						=						tokenizer.decode(_lowerCamelCase    )

					self.assertTrue(output_string == '''herecouple words ofthe'''    )







				def    a_					(							self				:   Tuple    ):



					"""simple docstring"""

					A_					:			Any						=						SpeechaTextaTokenizer.from_pretrained(self.tmpdirname    )

					with tempfile.TemporaryDirectory() as tmp_dirname:
						tokenizer.save_pretrained(_lowerCamelCase    )
						os.remove(os.path.join(_lowerCamelCase ,       '''merges.txt'''    )    )

						# load tokenizer without merges file should not throw an error
						A_					:			Optional[int]						=						SpeechaTextaTokenizer.from_pretrained(_lowerCamelCase    )

					with tempfile.TemporaryDirectory() as tmp_dirname:
						# save tokenizer and load again
						tokenizer.save_pretrained(_lowerCamelCase    )
						A_					:			List[str]						=						SpeechaTextaTokenizer.from_pretrained(_lowerCamelCase    )

					self.assertIsNotNone(_lowerCamelCase    )







				def    a_					(							self				:   Optional[int]    ):



					"""simple docstring"""

					if not self.test_slow_tokenizer:
						return

					A_					:			Tuple						=						inspect.signature(self.tokenizer_class.__init__    )
					A_					:			Optional[Any]						=						self.get_tokenizer()

					for parameter_name, parameter in signature.parameters.items():
						if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
							self.assertIn(_lowerCamelCase ,       tokenizer.init_kwargs    )











"""simple docstring"""

from .chunk_utils import chunk_layer
from .data_transforms import make_atomaa_masks
from .feats import atomaa_to_atomaa, frames_and_literature_positions_to_atomaa_pos, torsion_angles_to_frames
from .loss import compute_predicted_aligned_error, compute_tm
from .protein import Protein as OFProtein
from .protein import to_pdb
from .rigid_utils import Rigid, Rotation
from .tensor_utils import dict_multimap, flatten_final_dims, permute_final_dims





