'''simple docstring'''




import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
      from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


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

_lowercase		:				Union[str, Any]	       =		{"""target_lang""": """fi""", """source_lang""": """en"""}
_lowercase		:				int	       =		""">>zh<<"""
_lowercase		:				List[str]	       =		"""Helsinki-NLP/"""

if is_torch_available():
      _lowercase		:				Union[str, Any]	       =		"""pt"""
elif is_tf_available():
      _lowercase		:				Dict	       =		"""tf"""
else:
      _lowercase		:				Optional[Any]	       =		"""jax"""





@require_sentencepiece
class 					__magic_name__		(					_a,  unittest.TestCase):
   UpperCamelCase__       = MarianTokenizer
   UpperCamelCase__       = False
   UpperCamelCase__       = True







   def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
          super().setUp()
          lowercase_      :    List[Any]       		= ["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
          lowercase_      :    Optional[int]       		= dict(zip(snake_case_       ,    range(len(snake_case_					)					)					)					)
          lowercase_      :    List[str]       		= Path(self.tmpdirname					)
          save_json(snake_case_       ,    save_dir / VOCAB_FILES_NAMES["""vocab"""]					)
          save_json(snake_case_       ,    save_dir / VOCAB_FILES_NAMES["""tokenizer_config_file"""]					)
          if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
                 copyfile(snake_case_       ,    save_dir / VOCAB_FILES_NAMES["""source_spm"""]					)
                 copyfile(snake_case_       ,    save_dir / VOCAB_FILES_NAMES["""target_spm"""]					)

          lowercase_      :    Union[str, Any]       		= MarianTokenizer.from_pretrained(self.tmpdirname					)
          tokenizer.save_pretrained(self.tmpdirname					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]       ,    **lowercase_       :						Optional[Any]					):
          return MarianTokenizer.from_pretrained(self.tmpdirname       ,    **snake_case_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]       ,    lowercase_       :						Tuple					):
          return (
              "This is a test",
              "This is a test",
          )







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
          lowercase_      :    Optional[int]       		= """</s>"""
          lowercase_      :    List[str]       		= 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 			SCREAMING_SNAKE_CASE_  (			self       :						str					):
          lowercase_      :    Optional[Any]       		= list(self.get_tokenizer().get_vocab().keys()					)

          self.assertEqual(vocab_keys[0]       ,    """</s>"""					)
          self.assertEqual(vocab_keys[1]       ,    """<unk>"""					)
          self.assertEqual(vocab_keys[-1]       ,    """<pad>"""					)
          self.assertEqual(len(snake_case_					)       ,    9					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
          self.assertEqual(self.get_tokenizer().vocab_size       ,    9					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
          lowercase_      :    Optional[Any]       		= MarianTokenizer.from_pretrained(f'''{ORG_NAME}opus-mt-en-de'''					)
          lowercase_      :    Optional[Any]       		= en_de_tokenizer(["""I am a small frog"""]       ,    return_tensors=snake_case_					)
          self.assertIsInstance(snake_case_       ,    snake_case_					)
          lowercase_      :    int       		= [38, 121, 14, 697, 38848, 0]
          self.assertListEqual(snake_case_       ,    batch.input_ids[0]					)

          lowercase_      :    List[str]       		= tempfile.mkdtemp()
          en_de_tokenizer.save_pretrained(snake_case_					)
          lowercase_      :    Optional[int]       		= [x.name for x in Path(snake_case_					).glob("""*"""					)]
          self.assertIn("""source.spm"""       ,    snake_case_					)
          MarianTokenizer.from_pretrained(snake_case_					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Union[str, Any]					):
          lowercase_      :    str       		= self.get_tokenizer()

          lowercase_      :    Optional[int]       		= tok(
              ["""I am a small frog""" * 1000, """I am a small frog"""]       ,    padding=snake_case_       ,    truncation=snake_case_       ,    return_tensors=snake_case_					)
          self.assertIsInstance(snake_case_       ,    snake_case_					)
          self.assertEqual(batch.input_ids.shape       ,    (2, 512)					)







   def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):
          lowercase_      :    int       		= self.get_tokenizer()
          lowercase_      :    Optional[int]       		= tok(["""I am a tiny frog""", """I am a small frog"""]       ,    padding=snake_case_       ,    return_tensors=snake_case_					)
          self.assertIsInstance(snake_case_       ,    snake_case_					)
          self.assertEqual(batch_smaller.input_ids.shape       ,    (2, 10)					)







   @slow
   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
          # fmt: off
          lowercase_      :    Union[str, Any]       		= {"""input_ids""": [[43495, 462, 20, 42164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 38999, 6, 8, 464, 132, 1703, 492, 13, 4669, 37867, 13, 7525, 27, 1593, 988, 13, 33972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 12338, 2, 13958, 387, 2, 3629, 6953, 188, 2900, 2, 13958, 8011, 11501, 23, 8460, 4073, 34009, 20, 435, 11439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 37867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 26453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10767, 6, 316, 304, 4239, 3, 0], [148, 15722, 19, 1839, 12, 1350, 13, 22327, 5082, 5418, 47567, 35938, 59, 318, 19552, 108, 2183, 54, 14976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 19088, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100], [36, 6395, 12570, 39147, 11597, 6, 266, 4, 45405, 7296, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100]], """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, 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], [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, 0]]}  # noqa: E501
          # fmt: on

          self.tokenizer_integration_test_util(
              expected_encoding=snake_case_       ,    model_name="""Helsinki-NLP/opus-mt-en-de"""       ,    revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""       ,    decode_kwargs={"""use_source_tokenizer""": True}       ,    )







   def 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
          lowercase_      :    Union[str, Any]       		= MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""					)

          lowercase_      :    Optional[int]       		= """Tämä on testi"""
          lowercase_      :    Dict       		= """This is a test"""

          lowercase_      :    int       		= [76, 7, 2047, 2]
          lowercase_      :    Optional[Any]       		= [69, 12, 11, 940, 2]

          lowercase_      :    str       		= tokenizer(snake_case_					).input_ids
          self.assertListEqual(snake_case_       ,    snake_case_					)

          lowercase_      :    Tuple       		= tokenizer(text_target=snake_case_					).input_ids
          self.assertListEqual(snake_case_       ,    snake_case_					)

          lowercase_      :    str       		= tokenizer.decode(snake_case_       ,    skip_special_tokens=snake_case_					)
          self.assertEqual(snake_case_       ,    snake_case_					)






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowercase		:				Optional[Any]	       =		{
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:				Any	       =		[
						    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SwiftFormerForImageClassification",
						    "SwiftFormerModel",
						    "SwiftFormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

						_lowercase		:				Optional[int]	       =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





