




import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, 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__         =      get_tests_dir("""fixtures/test_sentencepiece.model""")


if is_torch_available():
					from transformers.models.mbart.modeling_mbart import shift_tokens_right

UpperCamelCase__         =      250004
UpperCamelCase__         =      250020
@require_sentencepiece
@require_tokenizers
class       a__   ( snake_case__			,    unittest.TestCase				):
						_a							:   Optional[Any] =   MBartTokenizer
						_a							:   int =   MBartTokenizerFast
						_a							:   Any =   True
						_a							:   Tuple =   True






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											super().setUp()

											# We have a SentencePiece fixture for testing
											__lowerCAmelCase           =	MBartTokenizer(_A		,      keep_accents=_A      )
											tokenizer.save_pretrained(self.tmpdirname      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	MBartTokenizer(_A		,      keep_accents=_A      )

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

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(_A      )		,      [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]		,      )

											__lowerCAmelCase           =	tokenizer.tokenize("I was born in 92000, and this is falsé."      )
											self.assertListEqual(
											    _A		,      [
											        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",
											        ".",
											    ]		,      )
											__lowerCAmelCase           =	tokenizer.convert_tokens_to_ids(_A      )
											self.assertListEqual(
											    _A		,      [
											        value + tokenizer.fairseq_offset
											        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
											        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
											    ]		,      )

											__lowerCAmelCase           =	tokenizer.convert_ids_to_tokens(_A      )
											self.assertListEqual(
											    _A		,      [
											        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      ):




											"""simple docstring"""



											if not self.test_slow_tokenizer:
																# as we don't have a slow version, we can't compare the outputs between slow and fast versions
																return

											__lowerCAmelCase           =	(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart", {})
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
																					__lowerCAmelCase           =	self.rust_tokenizer_class.from_pretrained(_A		,      **_A      )
																					__lowerCAmelCase           =	self.tokenizer_class.from_pretrained(_A		,      **_A      )

																					__lowerCAmelCase           =	tempfile.mkdtemp()

																					__lowerCAmelCase           =	tokenizer_r.save_pretrained(_A      )
																					__lowerCAmelCase           =	tokenizer_p.save_pretrained(_A      )

																					# 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      )      )
																					__lowerCAmelCase           =	tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f      )
																					self.assertSequenceEqual(_A		,      _A      )

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

																					# Check special tokens are set accordingly on Rust and Python
																					for key in tokenizer_pp.special_tokens_map:
																										self.assertTrue(hasattr(_A		,      _A      )      )
																										# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																										# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																					shutil.rmtree(_A      )

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

																					__lowerCAmelCase           =	tokenizer_r.save_pretrained(_A		,      legacy_format=_A      )
																					__lowerCAmelCase           =	tokenizer_p.save_pretrained(_A      )

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

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

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

																					shutil.rmtree(_A      )

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

																					__lowerCAmelCase           =	tokenizer_r.save_pretrained(_A		,      legacy_format=_A      )
																					__lowerCAmelCase           =	tokenizer_p.save_pretrained(_A      )

																					# 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
																					__lowerCAmelCase           =	tokenizer_r.from_pretrained(_A      )
																					__lowerCAmelCase           =	tokenizer_p.from_pretrained(_A      )

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

																					shutil.rmtree(_A      )






@require_torch
@require_sentencepiece
@require_tokenizers
class       a__   ( unittest.TestCase				):
						_a							:   str =   """facebook/mbart-large-en-ro"""
						_a							:   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.""",
						]
						_a							:   Dict =   [
						    """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.""",
						]
						_a							:   Optional[int] =   [8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2, EN_CODE]






						@classmethod
						def     __SCREAMING_SNAKE_CASE(       cls      ):




											"""simple docstring"""



											__lowerCAmelCase           =	MBartTokenizer.from_pretrained(
											    cls.checkpoint_name		,      src_lang="en_XX"		,      tgt_lang="ro_RO"      )
											__lowerCAmelCase           =	1
											return cls






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]		,      2_5_0_0_0_1      )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]		,      2_5_0_0_0_4      )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]		,      2_5_0_0_2_0      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
											self.assertListEqual(self.expected_src_tokens		,      _A      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertIn(_A		,      self.tokenizer.all_special_ids      )
											__lowerCAmelCase           =	[RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
											__lowerCAmelCase           =	self.tokenizer.decode(_A		,      skip_special_tokens=_A      )
											__lowerCAmelCase           =	self.tokenizer.decode(generated_ids[1:]		,      skip_special_tokens=_A      )
											self.assertEqual(_A		,      _A      )
											self.assertNotIn(self.tokenizer.eos_token		,      _A      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	["this is gunna be a long sentence " * 2_0]
											assert isinstance(src_text[0]		,      _A      )
											__lowerCAmelCase           =	1_0
											__lowerCAmelCase           =	self.tokenizer(_A		,      max_length=_A		,      truncation=_A      ).input_ids[0]
											self.assertEqual(ids[-2]		,      2      )
											self.assertEqual(ids[-1]		,      _A      )
											self.assertEqual(len(_A      )		,      _A      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]      )		,      [2_5_0_0_2_6, 2_5_0_0_0_1]      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	tempfile.mkdtemp()
											__lowerCAmelCase           =	self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(_A      )
											__lowerCAmelCase           =	MBartTokenizer.from_pretrained(_A      )
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,      _A      )






						@require_torch
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self.tokenizer(self.src_text		,      text_target=self.tgt_text		,      padding=_A		,      return_tensors="pt"      )
											__lowerCAmelCase           =	shift_tokens_right(batch["labels"]		,      self.tokenizer.pad_token_id      )

											# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
											assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
											assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
											assert batch.decoder_input_ids[1][-1] == 2
											assert batch.labels[1][-2:].tolist() == [2, RO_CODE]






						@require_torch
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self.tokenizer(
											    self.src_text		,      text_target=self.tgt_text		,      padding=_A		,      truncation=_A		,      max_length=len(self.expected_src_tokens      )		,      return_tensors="pt"		,      )

											__lowerCAmelCase           =	shift_tokens_right(batch["labels"]		,      self.tokenizer.pad_token_id      )

											self.assertIsInstance(_A		,      _A      )

											self.assertEqual((2, 1_4)		,      batch.input_ids.shape      )
											self.assertEqual((2, 1_4)		,      batch.attention_mask.shape      )
											__lowerCAmelCase           =	batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens		,      _A      )
											self.assertEqual(2		,      batch.decoder_input_ids[0, -1]      )  # EOS
											# Test that special tokens are reset
											self.assertEqual(self.tokenizer.prefix_tokens		,      []      )
											self.assertEqual(self.tokenizer.suffix_tokens		,      [self.tokenizer.eos_token_id, EN_CODE]      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self.tokenizer(self.src_text		,      padding=_A		,      truncation=_A		,      max_length=3		,      return_tensors="pt"      )
											__lowerCAmelCase           =	self.tokenizer(
											    text_target=self.tgt_text		,      padding=_A		,      truncation=_A		,      max_length=1_0		,      return_tensors="pt"      )
											__lowerCAmelCase           =	targets["input_ids"]
											__lowerCAmelCase           =	shift_tokens_right(_A		,      self.tokenizer.pad_token_id      )

											self.assertEqual(batch.input_ids.shape[1]		,      3      )
											self.assertEqual(batch.decoder_input_ids.shape[1]		,      1_0      )






						@require_torch
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self.tokenizer._build_translation_inputs(
											    "A test"		,      return_tensors="pt"		,      src_lang="en_XX"		,      tgt_lang="ar_AR"      )

											self.assertEqual(
											    nested_simplify(_A      )		,      {
											        # A, test, EOS, en_XX
											        "input_ids": [[6_2, 3_0_3_4, 2, 2_5_0_0_0_4]],
											        "attention_mask": [[1, 1, 1, 1]],
											        # ar_AR
											        "forced_bos_token_id": 2_5_0_0_0_1,
											    }		,      )










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


UpperCamelCase__         =      logging.get_logger(__name__)

UpperCamelCase__         =      {
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class       a__   ( snake_case__				):
						_a							:   Dict =   """mgp-str"""






						def __init__(       self		,      _A=[3_2, 1_2_8]		,      _A=4		,      _A=3		,      _A=2_7		,      _A=3_8		,      _A=5_0_2_5_7		,      _A=3_0_5_2_2		,      _A=7_6_8		,      _A=1_2		,      _A=1_2		,      _A=4.0		,      _A=True		,      _A=False		,      _A=1E-5		,      _A=0.0		,      _A=0.0		,      _A=0.0		,      _A=False		,      _A=0.02		,      **_A		,      ):




											"""simple docstring"""



											super().__init__(**_A      )

											__lowerCAmelCase           =	image_size
											__lowerCAmelCase           =	patch_size
											__lowerCAmelCase           =	num_channels
											__lowerCAmelCase           =	max_token_length
											__lowerCAmelCase           =	num_character_labels
											__lowerCAmelCase           =	num_bpe_labels
											__lowerCAmelCase           =	num_wordpiece_labels
											__lowerCAmelCase           =	hidden_size
											__lowerCAmelCase           =	num_hidden_layers
											__lowerCAmelCase           =	num_attention_heads
											__lowerCAmelCase           =	mlp_ratio
											__lowerCAmelCase           =	distilled
											__lowerCAmelCase           =	layer_norm_eps
											__lowerCAmelCase           =	drop_rate
											__lowerCAmelCase           =	qkv_bias
											__lowerCAmelCase           =	attn_drop_rate
											__lowerCAmelCase           =	drop_path_rate
											__lowerCAmelCase           =	output_aa_attentions
											__lowerCAmelCase           =	initializer_range




