



'''simple docstring'''



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


lowerCAmelCase_  :							Dict             =    get_tests_dir('fixtures/test_sentencepiece.model')


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

lowerCAmelCase_  :							int             =    25_6047
lowerCAmelCase_  :							List[Any]             =    25_6145
@require_sentencepiece
@require_tokenizers
class 						lowerCamelCase_				(       a_     ,					unittest.TestCase      ):
						_lowerCAmelCase  : Union[str, Any]						  =					NllbTokenizer
						_lowerCAmelCase  : Optional[int]						  =					NllbTokenizerFast
						_lowerCAmelCase  : Dict						  =					True
						_lowerCAmelCase  : int						  =					True
						_lowerCAmelCase  : str						  =					{}







						def        __lowercase     (	self :   Dict					):

													"""simple docstring"""
													super().setUp()

													# We have a SentencePiece fixture for testing
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      NllbTokenizer(lowercase_					,     keep_accents=lowercase_					)
													tokenizer.save_pretrained(self.tmpdirname					)







						def        __lowercase     (	self :   str					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Dict         =      NllbTokenizer(lowercase_					,     keep_accents=lowercase_					)

													SCREAMING_SNAKE_CASE       :   List[str]         =      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]]					,     )

													SCREAMING_SNAKE_CASE       :   List[str]         =      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''',
													        '''.''',
													    ]					,     )
													SCREAMING_SNAKE_CASE       :   str         =      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]
													    ]					,     )

													SCREAMING_SNAKE_CASE       :   str         =      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        __lowercase     (	self :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[str]         =      (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})"""					):
																											SCREAMING_SNAKE_CASE       :   Tuple         =      self.rust_tokenizer_class.from_pretrained(lowercase_					,     **lowercase_					)
																											SCREAMING_SNAKE_CASE       :   Tuple         =      self.tokenizer_class.from_pretrained(lowercase_					,     **lowercase_					)

																											SCREAMING_SNAKE_CASE       :   List[str]         =      tempfile.mkdtemp()

																											SCREAMING_SNAKE_CASE       :   List[Any]         =      tokenizer_r.save_pretrained(lowercase_					)
																											SCREAMING_SNAKE_CASE       :   Tuple         =      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					)					)
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      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
																											SCREAMING_SNAKE_CASE       :   Optional[int]         =      tokenizer_r.from_pretrained(lowercase_					)
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      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
																											SCREAMING_SNAKE_CASE       :   Optional[int]         =      tempfile.mkdtemp()

																											SCREAMING_SNAKE_CASE       :   List[str]         =      tokenizer_r.save_pretrained(lowercase_					,     legacy_format=lowercase_					)
																											SCREAMING_SNAKE_CASE       :   List[Any]         =      tokenizer_p.save_pretrained(lowercase_					)

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

																											# Checks everything loads correctly in the same way
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      tokenizer_r.from_pretrained(lowercase_					)
																											SCREAMING_SNAKE_CASE       :   List[Any]         =      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
																											SCREAMING_SNAKE_CASE       :   int         =      tempfile.mkdtemp()

																											SCREAMING_SNAKE_CASE       :   Tuple         =      tokenizer_r.save_pretrained(lowercase_					,     legacy_format=lowercase_					)
																											SCREAMING_SNAKE_CASE       :   Optional[Any]         =      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
																											SCREAMING_SNAKE_CASE       :   int         =      tokenizer_r.from_pretrained(lowercase_					)
																											SCREAMING_SNAKE_CASE       :   str         =      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        __lowercase     (	self :   List[Any]					):

													"""simple docstring"""
													if not self.test_seqaseq:
																				return

													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""					):
																											# Longer text that will definitely require truncation.
																											SCREAMING_SNAKE_CASE       :   Tuple         =      [
																											    ''' 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.''',
																											]
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      [
																											    '''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:
																																		SCREAMING_SNAKE_CASE       :   List[str]         =      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
																											SCREAMING_SNAKE_CASE       :   Optional[Any]         =      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					)

																											SCREAMING_SNAKE_CASE       :   Optional[Any]         =      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        __lowercase     (	self :   Optional[Any]					):

													"""simple docstring"""
													pass







						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																				with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
																											SCREAMING_SNAKE_CASE       :   Optional[int]         =      [AddedToken('''<special>'''					,     lstrip=lowercase_					)]

																											SCREAMING_SNAKE_CASE       :   int         =      self.rust_tokenizer_class.from_pretrained(
																											    lowercase_					,     additional_special_tokens=lowercase_					,     **lowercase_					)
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      tokenizer_r.encode('''Hey this is a <special> token'''					)

																											SCREAMING_SNAKE_CASE       :   int         =      tokenizer_r.encode('''<special>'''					,     add_special_tokens=lowercase_					)[0]

																											self.assertTrue(special_token_id in r_output					)

																											if self.test_slow_tokenizer:
																																		SCREAMING_SNAKE_CASE       :   Tuple         =      self.rust_tokenizer_class.from_pretrained(
																																		    lowercase_					,     additional_special_tokens=lowercase_					,     **lowercase_					,     )
																																		SCREAMING_SNAKE_CASE       :   Dict         =      self.tokenizer_class.from_pretrained(
																																		    lowercase_					,     additional_special_tokens=lowercase_					,     **lowercase_					)

																																		SCREAMING_SNAKE_CASE       :   Optional[Any]         =      tokenizer_p.encode('''Hey this is a <special> token'''					)

																																		SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      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 						lowerCamelCase_				(       unittest.TestCase      ):
						_lowerCAmelCase  : Optional[Any]						  =					'facebook/nllb-200-distilled-600M'
						_lowerCAmelCase  : Union[str, 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  : Any						  =					[
						    '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  : List[str]						  =					[
						    2_5_6_0_4_7,
						    1_6_2_9_7,
						    1_3_4_4_0_8,
						    8_1_6_5,
						    2_4_8_0_6_6,
						    1_4_7_3_4,
						    9_5_0,
						    1_1_3_5,
						    1_0_5_7_2_1,
						    3_5_7_3,
						    8_3,
						    2_7_3_5_2,
						    1_0_8,
						    4_9_4_8_6,
						    2,
						]







						@classmethod
						def        __lowercase     (	cls :   Any					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   NllbTokenizer         =      NllbTokenizer.from_pretrained(
													    cls.checkpoint_name					,     src_lang='''eng_Latn'''					,     tgt_lang='''ron_Latn'''					)
													SCREAMING_SNAKE_CASE       :   Any         =      1
													return cls







						def        __lowercase     (	self :   Any					):

													"""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        __lowercase     (	self :   Optional[Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   int         =      self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
													self.assertListEqual(self.expected_src_tokens					,     lowercase_					)







						def        __lowercase     (	self :   Dict					):

													"""simple docstring"""
													self.assertIn(lowercase_					,     self.tokenizer.all_special_ids					)
													# fmt: off
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      [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

													SCREAMING_SNAKE_CASE       :   List[str]         =      self.tokenizer.decode(lowercase_					,     skip_special_tokens=lowercase_					)
													SCREAMING_SNAKE_CASE       :   Dict         =      self.tokenizer.decode(generated_ids[1:]					,     skip_special_tokens=lowercase_					)
													self.assertEqual(lowercase_					,     lowercase_					)
													self.assertNotIn(self.tokenizer.eos_token					,     lowercase_					)







						def        __lowercase     (	self :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      ['''this is gunna be a long sentence ''' * 20]
													assert isinstance(src_text[0]					,     lowercase_					)
													SCREAMING_SNAKE_CASE       :   int         =      10
													SCREAMING_SNAKE_CASE       :   Any         =      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        __lowercase     (	self :   Optional[Any]					):

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







						def        __lowercase     (	self :   List[Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   int         =      tempfile.mkdtemp()
													SCREAMING_SNAKE_CASE       :   Tuple         =      self.tokenizer.fairseq_tokens_to_ids
													self.tokenizer.save_pretrained(lowercase_					)
													SCREAMING_SNAKE_CASE       :   Tuple         =      NllbTokenizer.from_pretrained(lowercase_					)
													self.assertDictEqual(new_tok.fairseq_tokens_to_ids					,     lowercase_					)







						@require_torch
						def        __lowercase     (	self :   Dict					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Any         =      self.tokenizer(
													    self.src_text					,     text_target=self.tgt_text					,     padding=lowercase_					,     truncation=lowercase_					,     max_length=len(self.expected_src_tokens					)					,     return_tensors='''pt'''					,     )
													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      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					)
													SCREAMING_SNAKE_CASE       :   Dict         =      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        __lowercase     (	self :   List[Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[Any]         =      self.tokenizer(self.src_text					,     padding=lowercase_					,     truncation=lowercase_					,     max_length=3					,     return_tensors='''pt'''					)
													SCREAMING_SNAKE_CASE       :   int         =      self.tokenizer(
													    text_target=self.tgt_text					,     padding=lowercase_					,     truncation=lowercase_					,     max_length=10					,     return_tensors='''pt'''					)
													SCREAMING_SNAKE_CASE       :   List[str]         =      targets['''input_ids''']
													SCREAMING_SNAKE_CASE       :   Tuple         =      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        __lowercase     (	self :   str					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      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        __lowercase     (	self :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      True
													SCREAMING_SNAKE_CASE       :   Tuple         =      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]					)

													SCREAMING_SNAKE_CASE       :   Optional[int]         =      False
													SCREAMING_SNAKE_CASE       :   str         =      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]					)







"""simple docstring"""





import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
							import onnxruntime as ort


__UpperCamelCase    : int				 =						logging.get_logger(__name__)

__UpperCamelCase    : Optional[Any]				 =						{
    '''tensor(bool)''': np.bool_,
    '''tensor(int8)''': np.inta,
    '''tensor(uint8)''': np.uinta,
    '''tensor(int16)''': np.intaa,
    '''tensor(uint16)''': np.uintaa,
    '''tensor(int32)''': np.intaa,
    '''tensor(uint32)''': np.uintaa,
    '''tensor(int64)''': np.intaa,
    '''tensor(uint64)''': np.uintaa,
    '''tensor(float16)''': np.floataa,
    '''tensor(float)''': np.floataa,
    '''tensor(double)''': np.floataa,
}







class 							SCREAMING_SNAKE_CASE   :






					"""simple docstring"""



					def __init__(			self     :							Optional[Any]  ,lowercase_     :							Union[str, Any]=None  ,**lowercase_     :							List[str]						):
						logger.info('''`diffusers.OnnxRuntimeModel` is experimental and might change in the future.'''						)
						lowerCAmelCase__      :		List[str]    							=      model
						lowerCAmelCase__      :		Optional[Any]    							=      kwargs.get('''model_save_dir'''  ,lowercase_						)
						lowerCAmelCase__      :		str    							=      kwargs.get('''latest_model_name'''  ,lowercase_						)







					def __call__(			self     :							Any  ,**lowercase_     :							Dict						):
						lowerCAmelCase__      :		List[Any]    							=      {k: np.array(lowercase_						) for k, v in kwargs.items()}
						return self.model.run(lowercase_  ,lowercase_						)







					@staticmethod
					def 			__lowerCAmelCase					(			lowercase_     :							Union[str, Path]  ,lowercase_     :							str=None  ,lowercase_     :							str=None						):
						if provider is None:
							logger.info('''No onnxruntime provider specified, using CPUExecutionProvider'''						)
							lowerCAmelCase__      :		Optional[Any]    							=      '''CPUExecutionProvider'''

						return ort.InferenceSession(lowercase_  ,providers=[provider]  ,sess_options=lowercase_						)







					def 			__lowerCAmelCase					(			self     :							Dict  ,lowercase_     :							Union[str, Path]  ,lowercase_     :							Optional[str] = None  ,**lowercase_     :							str						):
						lowerCAmelCase__      :		Any    							=      file_name if file_name is not None else ONNX_WEIGHTS_NAME

						lowerCAmelCase__      :		Tuple    							=      self.model_save_dir.joinpath(self.latest_model_name						)
						lowerCAmelCase__      :		List[Any]    							=      Path(lowercase_						).joinpath(lowercase_						)
						try:
							shutil.copyfile(lowercase_  ,lowercase_						)
						except shutil.SameFileError:
							pass

						# copy external weights (for models >2GB)
						lowerCAmelCase__      :		Dict    							=      self.model_save_dir.joinpath(lowercase_						)
						if src_path.exists():
							lowerCAmelCase__      :		Union[str, Any]    							=      Path(lowercase_						).joinpath(lowercase_						)
							try:
								shutil.copyfile(lowercase_  ,lowercase_						)
							except shutil.SameFileError:
								pass







					def 			__lowerCAmelCase					(			self     :							Optional[int]  ,lowercase_     :							Union[str, os.PathLike]  ,**lowercase_     :							Union[str, Any]  ,):
						if os.path.isfile(lowercase_						):
							logger.error(F'Provided path ({save_directory}) should be a directory, not a file'						)
							return

						os.makedirs(lowercase_  ,exist_ok=lowercase_						)

						# saving model weights/files
						self._save_pretrained(lowercase_  ,**lowercase_						)







					@classmethod
					def 			__lowerCAmelCase					(			cls     :							Dict  ,lowercase_     :							Union[str, Path]  ,lowercase_     :							Optional[Union[bool, str, None]] = None  ,lowercase_     :							Optional[Union[str, None]] = None  ,lowercase_     :							bool = False  ,lowercase_     :							Optional[str] = None  ,lowercase_     :							Optional[str] = None  ,lowercase_     :							Optional[str] = None  ,lowercase_     :							Optional["ort.SessionOptions"] = None  ,**lowercase_     :							Optional[int]  ,):
						lowerCAmelCase__      :		Optional[Any]    							=      file_name if file_name is not None else ONNX_WEIGHTS_NAME
						# load model from local directory
						if os.path.isdir(lowercase_						):
							lowerCAmelCase__      :		str    							=      OnnxRuntimeModel.load_model(
							    os.path.join(lowercase_  ,lowercase_						)  ,provider=lowercase_  ,sess_options=lowercase_						)
							lowerCAmelCase__      :		Any    							=      Path(lowercase_						)
						# load model from hub
						else:
							# download model
							lowerCAmelCase__      :		Optional[Any]    							=      hf_hub_download(
							    repo_id=lowercase_  ,filename=lowercase_  ,use_auth_token=lowercase_  ,revision=lowercase_  ,cache_dir=lowercase_  ,force_download=lowercase_  ,)
							lowerCAmelCase__      :		str    							=      Path(lowercase_						).parent
							lowerCAmelCase__      :		Union[str, Any]    							=      Path(lowercase_						).name
							lowerCAmelCase__      :		Optional[Any]    							=      OnnxRuntimeModel.load_model(lowercase_  ,provider=lowercase_  ,sess_options=lowercase_						)
						return cls(model=lowercase_  ,**lowercase_						)







					@classmethod
					def 			__lowerCAmelCase					(			cls     :							Any  ,lowercase_     :							Union[str, Path]  ,lowercase_     :							bool = True  ,lowercase_     :							Optional[str] = None  ,lowercase_     :							Optional[str] = None  ,**lowercase_     :							Any  ,):
						lowerCAmelCase__      :		Union[str, Any]    							=      None
						if len(str(lowercase_						).split('''@'''						)						) == 2:
							lowerCAmelCase__							,lowerCAmelCase__      :		str    							=      model_id.split('''@'''						)

						return cls._from_pretrained(
						    model_id=lowercase_  ,revision=lowercase_  ,cache_dir=lowercase_  ,force_download=lowercase_  ,use_auth_token=lowercase_  ,**lowercase_  ,)




