



import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase   :							int							 =get_tests_dir("""fixtures/spiece.model""")


@require_sentencepiece
@require_tokenizers
class       _lowercase   (a_      ,   unittest.TestCase      ):
				'''simple docstring'''







				lowercase__   						=						AlbertTokenizer
				lowercase__   						=						AlbertTokenizerFast
				lowercase__   						=						True
				lowercase__   						=						True
				lowercase__   						=						True

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									super().setUp()

									# We have a SentencePiece fixture for testing
									UpperCamelCase_		  =   AlbertTokenizer(snake_case__    )
									tokenizer.save_pretrained(self.tmpdirname    )

				def       _lowerCamelCase					( self     , snake_case__    ):

									'''simple docstring'''


									UpperCamelCase_		  =   "this is a test"
									UpperCamelCase_		  =   "this is a test"
									return input_text, output_text

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   "<pad>"
									UpperCamelCase_		  =   0

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(snake_case__    )     , snake_case__    )
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(snake_case__    )     , snake_case__    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   list(self.get_tokenizer().get_vocab().keys()    )

									self.assertEqual(vocab_keys[0]     , "<pad>"    )
									self.assertEqual(vocab_keys[1]     , "<unk>"    )
									self.assertEqual(vocab_keys[-1]     , "▁eloquent"    )
									self.assertEqual(len(snake_case__    )     , 3_0000    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									self.assertEqual(self.get_tokenizer().vocab_size     , 3_0000    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									if not self.test_rust_tokenizer:
														return

									UpperCamelCase_		  =   self.get_tokenizer()
									UpperCamelCase_		  =   self.get_rust_tokenizer()

									UpperCamelCase_		  =   "I was born in 92000, and this is falsé."

									UpperCamelCase_		  =   tokenizer.tokenize(snake_case__    )
									UpperCamelCase_		  =   rust_tokenizer.tokenize(snake_case__    )
									self.assertListEqual(snake_case__     , snake_case__    )

									UpperCamelCase_		  =   tokenizer.encode(snake_case__     , add_special_tokens=snake_case__    )
									UpperCamelCase_		  =   rust_tokenizer.encode(snake_case__     , add_special_tokens=snake_case__    )
									self.assertListEqual(snake_case__     , snake_case__    )

									UpperCamelCase_		  =   self.get_rust_tokenizer()
									UpperCamelCase_		  =   tokenizer.encode(snake_case__    )
									UpperCamelCase_		  =   rust_tokenizer.encode(snake_case__    )
									self.assertListEqual(snake_case__     , snake_case__    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   AlbertTokenizer(snake_case__     , keep_accents=snake_case__    )

									UpperCamelCase_		  =   tokenizer.tokenize("This is a test"    )
									self.assertListEqual(snake_case__     , ["▁this", "▁is", "▁a", "▁test"]    )

									self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__    )     , [48, 25, 21, 1289]    )

									UpperCamelCase_		  =   tokenizer.tokenize("I was born in 92000, and this is falsé."    )
									self.assertListEqual(
									    snake_case__     , ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]    )
									UpperCamelCase_		  =   tokenizer.convert_tokens_to_ids(snake_case__    )
									self.assertListEqual(snake_case__     , [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]    )

									UpperCamelCase_		  =   tokenizer.convert_ids_to_tokens(snake_case__    )
									self.assertListEqual(
									    snake_case__     , ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]     , )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   AlbertTokenizer(snake_case__    )

									UpperCamelCase_		  =   tokenizer.encode("sequence builders"    )
									UpperCamelCase_		  =   tokenizer.encode("multi-sequence build"    )

									UpperCamelCase_		  =   tokenizer.build_inputs_with_special_tokens(snake_case__    )
									UpperCamelCase_		  =   tokenizer.build_inputs_with_special_tokens(snake_case__     , snake_case__    )

									assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
									assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
									    tokenizer.sep_token_id
									]

				@slow
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   {"attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "input_ids": [[2, 2_1970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 1_2051, 18, 17, 7103, 2153, 673, 8, 3515, 1_8684, 8, 4461, 6, 1927, 297, 8, 1_2060, 2607, 18, 13, 5, 4461, 15, 1_0538, 38, 8, 135, 15, 822, 58, 15, 993, 1_0363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 1_0641, 6, 29, 84, 2512, 2430, 782, 1_8684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 1_1712, 15, 7103, 2153, 673, 17, 2_4883, 9990, 9, 3], [2, 1_1502, 25, 1006, 20, 782, 8, 1_1809, 855, 1732, 1_9393, 1_8667, 37, 367, 2_1018, 69, 1854, 34, 1_1860, 1_9124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 2231, 886, 2385, 1_7659, 84, 14, 1_6792, 1952, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=snake_case__     , model_name="albert-base-v2"     , revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"     , )





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


UpperCAmelCase   :							str							 =logging.get_logger(__name__)

UpperCAmelCase   :							Tuple							 ={
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class       _lowercase   (a_      ):
				'''simple docstring'''







				lowercase__   						=						"""pegasus"""
				lowercase__   						=						["""past_key_values"""]
				lowercase__   						=						{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

				def __init__( self     , snake_case__=5_0265     , snake_case__=1024     , snake_case__=12     , snake_case__=4096     , snake_case__=16     , snake_case__=12     , snake_case__=4096     , snake_case__=16     , snake_case__=0.0     , snake_case__=0.0     , snake_case__=True     , snake_case__=True     , snake_case__="gelu"     , snake_case__=1024     , snake_case__=0.1     , snake_case__=0.0     , snake_case__=0.0     , snake_case__=0.02     , snake_case__=0     , snake_case__=False     , snake_case__=0     , snake_case__=1     , snake_case__=1     , **snake_case__     , ):

									'''simple docstring'''


									UpperCamelCase_		  =   vocab_size
									UpperCamelCase_		  =   max_position_embeddings
									UpperCamelCase_		  =   d_model
									UpperCamelCase_		  =   encoder_ffn_dim
									UpperCamelCase_		  =   encoder_layers
									UpperCamelCase_		  =   encoder_attention_heads
									UpperCamelCase_		  =   decoder_ffn_dim
									UpperCamelCase_		  =   decoder_layers
									UpperCamelCase_		  =   decoder_attention_heads
									UpperCamelCase_		  =   dropout
									UpperCamelCase_		  =   attention_dropout
									UpperCamelCase_		  =   activation_dropout
									UpperCamelCase_		  =   activation_function
									UpperCamelCase_		  =   init_std
									UpperCamelCase_		  =   encoder_layerdrop
									UpperCamelCase_		  =   decoder_layerdrop
									UpperCamelCase_		  =   use_cache
									UpperCamelCase_		  =   encoder_layers
									UpperCamelCase_		  =   scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=snake_case__     , eos_token_id=snake_case__     , is_encoder_decoder=snake_case__     , decoder_start_token_id=snake_case__     , forced_eos_token_id=snake_case__     , **snake_case__     , )

				@property
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									return self.encoder_attention_heads

				@property
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									return self.d_model
