





import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase__   : Dict					  = get_tests_dir("""fixtures/test_sentencepiece.model""")


if is_torch_available():
				from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

UpperCamelCase__   : Optional[Any]					  = 25_60_47
UpperCamelCase__   : List[Any]					  = 25_61_45







@require_sentencepiece
@require_tokenizers
class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Optional[int]			    =       NllbTokenizer
					lowerCamelCase     :     Optional[Any]			    =       NllbTokenizerFast
					lowerCamelCase     :     List[str]			    =       True
					lowerCamelCase     :     Optional[int]			    =       True
					lowerCamelCase     :     Dict			    =       {}





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						super().setUp()

						# We have a SentencePiece fixture for testing
						UpperCAmelCase_								=     NllbTokenizer(__lowercase ,					keep_accents=__lowercase		)
						tokenizer.save_pretrained(self.tmpdirname		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     NllbTokenizer(__lowercase ,					keep_accents=__lowercase		)

						UpperCAmelCase_								=     tokenizer.tokenize("""This is a test"""		)
						self.assertListEqual(__lowercase ,					["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(__lowercase		) ,					[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]] ,					)

						UpperCAmelCase_								=     tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
						self.assertListEqual(
						    __lowercase ,					[
						        SPIECE_UNDERLINE + """I""",
						        SPIECE_UNDERLINE + """was""",
						        SPIECE_UNDERLINE + """b""",
						        """or""",
						        """n""",
						        SPIECE_UNDERLINE + """in""",
						        SPIECE_UNDERLINE + """""",
						        """9""",
						        """2""",
						        """0""",
						        """0""",
						        """0""",
						        """,""",
						        SPIECE_UNDERLINE + """and""",
						        SPIECE_UNDERLINE + """this""",
						        SPIECE_UNDERLINE + """is""",
						        SPIECE_UNDERLINE + """f""",
						        """al""",
						        """s""",
						        """é""",
						        """.""",
						    ] ,					)
						UpperCAmelCase_								=     tokenizer.convert_tokens_to_ids(__lowercase		)
						self.assertListEqual(
						    __lowercase ,					[
						        value + tokenizer.fairseq_offset
						        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
						    ] ,					)

						UpperCAmelCase_								=     tokenizer.convert_ids_to_tokens(__lowercase		)
						self.assertListEqual(
						    __lowercase ,					[
						        SPIECE_UNDERLINE + """I""",
						        SPIECE_UNDERLINE + """was""",
						        SPIECE_UNDERLINE + """b""",
						        """or""",
						        """n""",
						        SPIECE_UNDERLINE + """in""",
						        SPIECE_UNDERLINE + """""",
						        """<unk>""",
						        """2""",
						        """0""",
						        """0""",
						        """0""",
						        """,""",
						        SPIECE_UNDERLINE + """and""",
						        SPIECE_UNDERLINE + """this""",
						        SPIECE_UNDERLINE + """is""",
						        SPIECE_UNDERLINE + """f""",
						        """al""",
						        """s""",
						        """<unk>""",
						        """.""",
						    ] ,					)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[str]		):






						'''simple docstring'''







						UpperCAmelCase_								=     (self.rust_tokenizer_class, """hf-internal-testing/tiny-random-nllb""", {})
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
								UpperCAmelCase_								=     self.rust_tokenizer_class.from_pretrained(__lowercase ,					**__lowercase		)
								UpperCAmelCase_								=     self.tokenizer_class.from_pretrained(__lowercase ,					**__lowercase		)

								UpperCAmelCase_								=     tempfile.mkdtemp()

								UpperCAmelCase_								=     tokenizer_r.save_pretrained(__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.save_pretrained(__lowercase		)

								# Checks it save with the same files + the tokenizer.json file for the fast one
								self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)
								UpperCAmelCase_								=     tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f		)
								self.assertSequenceEqual(__lowercase ,					__lowercase		)

								# Checks everything loads correctly in the same way
								UpperCAmelCase_								=     tokenizer_r.from_pretrained(__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.from_pretrained(__lowercase		)

								# Check special tokens are set accordingly on Rust and Python
								for key in tokenizer_pp.special_tokens_map:
									self.assertTrue(hasattr(__lowercase ,					__lowercase		)		)

								shutil.rmtree(__lowercase		)

								# Save tokenizer rust, legacy_format=True
								UpperCAmelCase_								=     tempfile.mkdtemp()

								UpperCAmelCase_								=     tokenizer_r.save_pretrained(__lowercase ,					legacy_format=__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.save_pretrained(__lowercase		)

								# Checks it save with the same files
								self.assertSequenceEqual(__lowercase ,					__lowercase		)

								# Checks everything loads correctly in the same way
								UpperCAmelCase_								=     tokenizer_r.from_pretrained(__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.from_pretrained(__lowercase		)

								# Check special tokens are set accordingly on Rust and Python
								for key in tokenizer_pp.special_tokens_map:
									self.assertTrue(hasattr(__lowercase ,					__lowercase		)		)

								shutil.rmtree(__lowercase		)

								# Save tokenizer rust, legacy_format=False
								UpperCAmelCase_								=     tempfile.mkdtemp()

								UpperCAmelCase_								=     tokenizer_r.save_pretrained(__lowercase ,					legacy_format=__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.save_pretrained(__lowercase		)

								# Checks it saved the tokenizer.json file
								self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)

								# Checks everything loads correctly in the same way
								UpperCAmelCase_								=     tokenizer_r.from_pretrained(__lowercase		)
								UpperCAmelCase_								=     tokenizer_p.from_pretrained(__lowercase		)

								# Check special tokens are set accordingly on Rust and Python
								for key in tokenizer_pp.special_tokens_map:
									self.assertTrue(hasattr(__lowercase ,					__lowercase		)		)

								shutil.rmtree(__lowercase		)





					@require_torch
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						if not self.test_seqaseq:
							return

						UpperCAmelCase_								=     self.get_tokenizers()
						for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""		):
								# Longer text that will definitely require truncation.
								UpperCAmelCase_								=     [
								    """ UN Chief Says There Is No Military Solution in Syria""",
								    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for"""
								    """ Syria is that 'there is no military solution' to the nearly five-year conflict and more weapons"""
								    """ will only worsen the violence and misery for millions of people.""",
								]
								UpperCAmelCase_								=     [
								    """Şeful ONU declară că nu există o soluţie militară în Siria""",
								    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al"""
								    """ Rusiei pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi"""
								    """ că noi arme nu vor face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
								]
								try:
									UpperCAmelCase_								=     tokenizer.prepare_seqaseq_batch(
									    src_texts=__lowercase ,					tgt_texts=__lowercase ,					max_length=3 ,					max_target_length=10 ,					return_tensors="""pt""" ,					src_lang="""eng_Latn""" ,					tgt_lang="""ron_Latn""" ,					)
								except NotImplementedError:
									return
								self.assertEqual(batch.input_ids.shape[1] ,					3		)
								self.assertEqual(batch.labels.shape[1] ,					10		)
								# max_target_length will default to max_length if not specified
								UpperCAmelCase_								=     tokenizer.prepare_seqaseq_batch(
								    __lowercase ,					tgt_texts=__lowercase ,					max_length=3 ,					return_tensors="""pt"""		)
								self.assertEqual(batch.input_ids.shape[1] ,					3		)
								self.assertEqual(batch.labels.shape[1] ,					3		)

								UpperCAmelCase_								=     tokenizer.prepare_seqaseq_batch(
								    src_texts=__lowercase ,					max_length=3 ,					max_target_length=10 ,					return_tensors="""pt"""		)
								self.assertEqual(batch_encoder_only.input_ids.shape[1] ,					3		)
								self.assertEqual(batch_encoder_only.attention_mask.shape[1] ,					3		)
								self.assertNotIn("""decoder_input_ids""" ,					__lowercase		)





					@unittest.skip("""Unfortunately way too slow to build a BPE with SentencePiece."""		)
					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						pass





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
								UpperCAmelCase_								=     [AddedToken("""<special>""" ,					lstrip=__lowercase		)]

								UpperCAmelCase_								=     self.rust_tokenizer_class.from_pretrained(
								    __lowercase ,					additional_special_tokens=__lowercase ,					**__lowercase		)
								UpperCAmelCase_								=     tokenizer_r.encode("""Hey this is a <special> token"""		)

								UpperCAmelCase_								=     tokenizer_r.encode("""<special>""" ,					add_special_tokens=__lowercase		)[0]

								self.assertTrue(special_token_id in r_output		)

								if self.test_slow_tokenizer:
									UpperCAmelCase_								=     self.rust_tokenizer_class.from_pretrained(
									    __lowercase ,					additional_special_tokens=__lowercase ,					**__lowercase ,					)
									UpperCAmelCase_								=     self.tokenizer_class.from_pretrained(
									    __lowercase ,					additional_special_tokens=__lowercase ,					**__lowercase		)

									UpperCAmelCase_								=     tokenizer_p.encode("""Hey this is a <special> token"""		)

									UpperCAmelCase_								=     tokenizer_cr.encode("""Hey this is a <special> token"""		)

									self.assertEqual(__lowercase ,					__lowercase		)
									self.assertEqual(__lowercase ,					__lowercase		)
									self.assertTrue(special_token_id in p_output		)
									self.assertTrue(special_token_id in cr_output		)







@require_torch
@require_sentencepiece
@require_tokenizers
class   _UpperCamelCase  (       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Dict			    =       'facebook/nllb-200-distilled-600M'
					lowerCamelCase     :     Optional[Any]			    =       [
					    ' UN Chief Says There Is No Military Solution in Syria',
					    ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
					]
					lowerCamelCase     :     int			    =       [
					    'Şeful ONU declară că nu există o soluţie militară în Siria',
					    'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
					    ' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'
					    ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
					]
					lowerCamelCase     :     Dict			    =       [
					    256_047,
					    16_297,
					    134_408,
					    8_165,
					    248_066,
					    14_734,
					    950,
					    1_135,
					    105_721,
					    3_573,
					    83,
					    27_352,
					    108,
					    49_486,
					    2,
					]





					@classmethod
					def        SCREAMING_SNAKE_CASE							(						cls    :  Union[str, Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     NllbTokenizer.from_pretrained(
						    cls.checkpoint_name ,					src_lang="""eng_Latn""" ,					tgt_lang="""ron_Latn"""		)
						UpperCAmelCase_								=     1
						return cls





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Arab"""] ,					25_60_01		)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Latn"""] ,					25_60_02		)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""fra_Latn"""] ,					25_60_57		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
						self.assertListEqual(self.expected_src_tokens ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						self.assertIn(__lowercase ,					self.tokenizer.all_special_ids		)
						# fmt: off
						UpperCAmelCase_								=     [RO_CODE, 42_54, 9_80_68, 11_29_23, 3_90_72, 39_09, 7_13, 10_27_67, 26, 1_73_14, 3_56_42, 1_46_83, 3_31_18, 20_22, 6_69_87, 2, 25_60_47]
						# fmt: on

						UpperCAmelCase_								=     self.tokenizer.decode(__lowercase ,					skip_special_tokens=__lowercase		)
						UpperCAmelCase_								=     self.tokenizer.decode(generated_ids[1:] ,					skip_special_tokens=__lowercase		)
						self.assertEqual(__lowercase ,					__lowercase		)
						self.assertNotIn(self.tokenizer.eos_token ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[str]		):






						'''simple docstring'''







						UpperCAmelCase_								=     ["""this is gunna be a long sentence """ * 20]
						assert isinstance(src_text[0] ,					__lowercase		)
						UpperCAmelCase_								=     10
						UpperCAmelCase_								=     self.tokenizer(__lowercase ,					max_length=__lowercase ,					truncation=__lowercase		).input_ids[0]
						self.assertEqual(ids[-1] ,					2		)
						self.assertEqual(ids[0] ,					__lowercase		)
						self.assertEqual(len(__lowercase		) ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]		) ,					[25_62_03, 3]		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     tempfile.mkdtemp()
						UpperCAmelCase_								=     self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(__lowercase		)
						UpperCAmelCase_								=     NllbTokenizer.from_pretrained(__lowercase		)
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,					__lowercase		)





					@require_torch
					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.tokenizer(
						    self.src_text ,					text_target=self.tgt_text ,					padding=__lowercase ,					truncation=__lowercase ,					max_length=len(self.expected_src_tokens		) ,					return_tensors="""pt""" ,					)
						UpperCAmelCase_								=     shift_tokens_right(
						    batch["""labels"""] ,					self.tokenizer.pad_token_id ,					self.tokenizer.lang_code_to_id["""ron_Latn"""]		)

						self.assertIsInstance(__lowercase ,					__lowercase		)

						self.assertEqual((2, 15) ,					batch.input_ids.shape		)
						self.assertEqual((2, 15) ,					batch.attention_mask.shape		)
						UpperCAmelCase_								=     batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens ,					__lowercase		)
						self.assertEqual(__lowercase ,					batch.decoder_input_ids[0, 0]		)  # EOS
						# Test that special tokens are reset
						self.assertEqual(self.tokenizer.prefix_tokens ,					[EN_CODE]		)
						self.assertEqual(self.tokenizer.suffix_tokens ,					[self.tokenizer.eos_token_id]		)





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.tokenizer(self.src_text ,					padding=__lowercase ,					truncation=__lowercase ,					max_length=3 ,					return_tensors="""pt"""		)
						UpperCAmelCase_								=     self.tokenizer(
						    text_target=self.tgt_text ,					padding=__lowercase ,					truncation=__lowercase ,					max_length=10 ,					return_tensors="""pt"""		)
						UpperCAmelCase_								=     targets["""input_ids"""]
						UpperCAmelCase_								=     shift_tokens_right(
						    __lowercase ,					self.tokenizer.pad_token_id ,					decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang] ,					)

						self.assertEqual(batch.input_ids.shape[1] ,					3		)
						self.assertEqual(batch.decoder_input_ids.shape[1] ,					10		)





					@require_torch
					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.tokenizer._build_translation_inputs(
						    """A test""" ,					return_tensors="""pt""" ,					src_lang="""eng_Latn""" ,					tgt_lang="""fra_Latn"""		)

						self.assertEqual(
						    nested_simplify(__lowercase		) ,					{
						        # A, test, EOS, en_XX
						        """input_ids""": [[25_60_47, 70, 73_56, 2]],
						        """attention_mask""": [[1, 1, 1, 1]],
						        # ar_AR
						        """forced_bos_token_id""": 25_60_57,
						    } ,					)





					@require_torch
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     True
						UpperCAmelCase_								=     self.tokenizer(
						    """UN Chief says there is no military solution in Syria""" ,					src_lang="""eng_Latn""" ,					tgt_lang="""fra_Latn"""		)
						self.assertEqual(
						    inputs.input_ids ,					[1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2, 25_60_47]		)

						UpperCAmelCase_								=     False
						UpperCAmelCase_								=     self.tokenizer(
						    """UN Chief says there is no military solution in Syria""" ,					src_lang="""eng_Latn""" ,					tgt_lang="""fra_Latn"""		)
						self.assertEqual(
						    inputs.input_ids ,					[25_60_47, 1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2]		)









from ....configuration_utils import PretrainedConfig
from ....utils import logging


UpperCamelCase__   : Any					  = logging.get_logger(__name__)

UpperCamelCase__   : int					  = {
    """CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
        """https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"""
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					lowerCamelCase     :     Tuple			    =       'trajectory_transformer'
					lowerCamelCase     :     Optional[Any]			    =       ['past_key_values']
					lowerCamelCase     :     Tuple			    =       {
					    'hidden_size': 'n_embd',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}





					def __init__(						self    :  Union[str, Any] ,					__lowercase    :  Optional[Any]=1_00 ,					__lowercase    :  int=5 ,					__lowercase    :  str=1 ,					__lowercase    :  Union[str, Any]=1 ,					__lowercase    :  Optional[Any]=2_49 ,					__lowercase    :  Tuple=6 ,					__lowercase    :  Tuple=17 ,					__lowercase    :  List[str]=25 ,					__lowercase    :  Tuple=4 ,					__lowercase    :  Dict=4 ,					__lowercase    :  int=1_28 ,					__lowercase    :  List[str]=0.1 ,					__lowercase    :  Optional[Any]=0.1 ,					__lowercase    :  Union[str, Any]=0.1 ,					__lowercase    :  Tuple=0.0006 ,					__lowercase    :  Optional[int]=5_12 ,					__lowercase    :  Any=0.02 ,					__lowercase    :  Tuple=1e-12 ,					__lowercase    :  Optional[Any]=1 ,					__lowercase    :  Dict=True ,					__lowercase    :  Optional[Any]=1 ,					__lowercase    :  str=5_02_56 ,					__lowercase    :  Any=5_02_56 ,					**__lowercase    :  str ,					):






						'''simple docstring'''







						UpperCAmelCase_								=     vocab_size
						UpperCAmelCase_								=     action_weight
						UpperCAmelCase_								=     reward_weight
						UpperCAmelCase_								=     value_weight
						UpperCAmelCase_								=     max_position_embeddings
						UpperCAmelCase_								=     block_size
						UpperCAmelCase_								=     action_dim
						UpperCAmelCase_								=     observation_dim
						UpperCAmelCase_								=     transition_dim
						UpperCAmelCase_								=     learning_rate
						UpperCAmelCase_								=     n_layer
						UpperCAmelCase_								=     n_head
						UpperCAmelCase_								=     n_embd
						UpperCAmelCase_								=     embd_pdrop
						UpperCAmelCase_								=     attn_pdrop
						UpperCAmelCase_								=     resid_pdrop
						UpperCAmelCase_								=     initializer_range
						UpperCAmelCase_								=     layer_norm_eps
						UpperCAmelCase_								=     kaiming_initializer_range
						UpperCAmelCase_								=     use_cache
						super().__init__(pad_token_id=__lowercase ,					bos_token_id=__lowercase ,					eos_token_id=__lowercase ,					**__lowercase		)


