



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


_lowerCamelCase    :		Dict		      =    {
    """Acehnese Arabic""": """ace_Arab""",
    """Acehnese Latin""": """ace_Latn""",
    """Mesopotamian Arabic""": """acm_Arab""",
    """Ta'izzi-Adeni Arabic""": """acq_Arab""",
    """Tunisian Arabic""": """aeb_Arab""",
    """Afrikaans""": """afr_Latn""",
    """South Levantine Arabic""": """ajp_Arab""",
    """Akan""": """aka_Latn""",
    """Amharic""": """amh_Ethi""",
    """North Levantine Arabic""": """apc_Arab""",
    """Modern Standard Arabic""": """arb_Arab""",
    """Modern Standard Arabic Romanized""": """arb_Latn""",
    """Najdi Arabic""": """ars_Arab""",
    """Moroccan Arabic""": """ary_Arab""",
    """Egyptian Arabic""": """arz_Arab""",
    """Assamese""": """asm_Beng""",
    """Asturian""": """ast_Latn""",
    """Awadhi""": """awa_Deva""",
    """Central Aymara""": """ayr_Latn""",
    """South Azerbaijani""": """azb_Arab""",
    """North Azerbaijani""": """azj_Latn""",
    """Bashkir""": """bak_Cyrl""",
    """Bambara""": """bam_Latn""",
    """Balinese""": """ban_Latn""",
    """Belarusian""": """bel_Cyrl""",
    """Bemba""": """bem_Latn""",
    """Bengali""": """ben_Beng""",
    """Bhojpuri""": """bho_Deva""",
    """Banjar Arabic""": """bjn_Arab""",
    """Banjar Latin""": """bjn_Latn""",
    """Standard Tibetan""": """bod_Tibt""",
    """Bosnian""": """bos_Latn""",
    """Buginese""": """bug_Latn""",
    """Bulgarian""": """bul_Cyrl""",
    """Catalan""": """cat_Latn""",
    """Cebuano""": """ceb_Latn""",
    """Czech""": """ces_Latn""",
    """Chokwe""": """cjk_Latn""",
    """Central Kurdish""": """ckb_Arab""",
    """Crimean Tatar""": """crh_Latn""",
    """Welsh""": """cym_Latn""",
    """Danish""": """dan_Latn""",
    """German""": """deu_Latn""",
    """Southwestern Dinka""": """dik_Latn""",
    """Dyula""": """dyu_Latn""",
    """Dzongkha""": """dzo_Tibt""",
    """Greek""": """ell_Grek""",
    """English""": """eng_Latn""",
    """Esperanto""": """epo_Latn""",
    """Estonian""": """est_Latn""",
    """Basque""": """eus_Latn""",
    """Ewe""": """ewe_Latn""",
    """Faroese""": """fao_Latn""",
    """Fijian""": """fij_Latn""",
    """Finnish""": """fin_Latn""",
    """Fon""": """fon_Latn""",
    """French""": """fra_Latn""",
    """Friulian""": """fur_Latn""",
    """Nigerian Fulfulde""": """fuv_Latn""",
    """Scottish Gaelic""": """gla_Latn""",
    """Irish""": """gle_Latn""",
    """Galician""": """glg_Latn""",
    """Guarani""": """grn_Latn""",
    """Gujarati""": """guj_Gujr""",
    """Haitian Creole""": """hat_Latn""",
    """Hausa""": """hau_Latn""",
    """Hebrew""": """heb_Hebr""",
    """Hindi""": """hin_Deva""",
    """Chhattisgarhi""": """hne_Deva""",
    """Croatian""": """hrv_Latn""",
    """Hungarian""": """hun_Latn""",
    """Armenian""": """hye_Armn""",
    """Igbo""": """ibo_Latn""",
    """Ilocano""": """ilo_Latn""",
    """Indonesian""": """ind_Latn""",
    """Icelandic""": """isl_Latn""",
    """Italian""": """ita_Latn""",
    """Javanese""": """jav_Latn""",
    """Japanese""": """jpn_Jpan""",
    """Kabyle""": """kab_Latn""",
    """Jingpho""": """kac_Latn""",
    """Kamba""": """kam_Latn""",
    """Kannada""": """kan_Knda""",
    """Kashmiri Arabic""": """kas_Arab""",
    """Kashmiri Devanagari""": """kas_Deva""",
    """Georgian""": """kat_Geor""",
    """Central Kanuri Arabic""": """knc_Arab""",
    """Central Kanuri Latin""": """knc_Latn""",
    """Kazakh""": """kaz_Cyrl""",
    """Kabiyè""": """kbp_Latn""",
    """Kabuverdianu""": """kea_Latn""",
    """Khmer""": """khm_Khmr""",
    """Kikuyu""": """kik_Latn""",
    """Kinyarwanda""": """kin_Latn""",
    """Kyrgyz""": """kir_Cyrl""",
    """Kimbundu""": """kmb_Latn""",
    """Northern Kurdish""": """kmr_Latn""",
    """Kikongo""": """kon_Latn""",
    """Korean""": """kor_Hang""",
    """Lao""": """lao_Laoo""",
    """Ligurian""": """lij_Latn""",
    """Limburgish""": """lim_Latn""",
    """Lingala""": """lin_Latn""",
    """Lithuanian""": """lit_Latn""",
    """Lombard""": """lmo_Latn""",
    """Latgalian""": """ltg_Latn""",
    """Luxembourgish""": """ltz_Latn""",
    """Luba-Kasai""": """lua_Latn""",
    """Ganda""": """lug_Latn""",
    """Luo""": """luo_Latn""",
    """Mizo""": """lus_Latn""",
    """Standard Latvian""": """lvs_Latn""",
    """Magahi""": """mag_Deva""",
    """Maithili""": """mai_Deva""",
    """Malayalam""": """mal_Mlym""",
    """Marathi""": """mar_Deva""",
    """Minangkabau Arabic """: """min_Arab""",
    """Minangkabau Latin""": """min_Latn""",
    """Macedonian""": """mkd_Cyrl""",
    """Plateau Malagasy""": """plt_Latn""",
    """Maltese""": """mlt_Latn""",
    """Meitei Bengali""": """mni_Beng""",
    """Halh Mongolian""": """khk_Cyrl""",
    """Mossi""": """mos_Latn""",
    """Maori""": """mri_Latn""",
    """Burmese""": """mya_Mymr""",
    """Dutch""": """nld_Latn""",
    """Norwegian Nynorsk""": """nno_Latn""",
    """Norwegian Bokmål""": """nob_Latn""",
    """Nepali""": """npi_Deva""",
    """Northern Sotho""": """nso_Latn""",
    """Nuer""": """nus_Latn""",
    """Nyanja""": """nya_Latn""",
    """Occitan""": """oci_Latn""",
    """West Central Oromo""": """gaz_Latn""",
    """Odia""": """ory_Orya""",
    """Pangasinan""": """pag_Latn""",
    """Eastern Panjabi""": """pan_Guru""",
    """Papiamento""": """pap_Latn""",
    """Western Persian""": """pes_Arab""",
    """Polish""": """pol_Latn""",
    """Portuguese""": """por_Latn""",
    """Dari""": """prs_Arab""",
    """Southern Pashto""": """pbt_Arab""",
    """Ayacucho Quechua""": """quy_Latn""",
    """Romanian""": """ron_Latn""",
    """Rundi""": """run_Latn""",
    """Russian""": """rus_Cyrl""",
    """Sango""": """sag_Latn""",
    """Sanskrit""": """san_Deva""",
    """Santali""": """sat_Olck""",
    """Sicilian""": """scn_Latn""",
    """Shan""": """shn_Mymr""",
    """Sinhala""": """sin_Sinh""",
    """Slovak""": """slk_Latn""",
    """Slovenian""": """slv_Latn""",
    """Samoan""": """smo_Latn""",
    """Shona""": """sna_Latn""",
    """Sindhi""": """snd_Arab""",
    """Somali""": """som_Latn""",
    """Southern Sotho""": """sot_Latn""",
    """Spanish""": """spa_Latn""",
    """Tosk Albanian""": """als_Latn""",
    """Sardinian""": """srd_Latn""",
    """Serbian""": """srp_Cyrl""",
    """Swati""": """ssw_Latn""",
    """Sundanese""": """sun_Latn""",
    """Swedish""": """swe_Latn""",
    """Swahili""": """swh_Latn""",
    """Silesian""": """szl_Latn""",
    """Tamil""": """tam_Taml""",
    """Tatar""": """tat_Cyrl""",
    """Telugu""": """tel_Telu""",
    """Tajik""": """tgk_Cyrl""",
    """Tagalog""": """tgl_Latn""",
    """Thai""": """tha_Thai""",
    """Tigrinya""": """tir_Ethi""",
    """Tamasheq Latin""": """taq_Latn""",
    """Tamasheq Tifinagh""": """taq_Tfng""",
    """Tok Pisin""": """tpi_Latn""",
    """Tswana""": """tsn_Latn""",
    """Tsonga""": """tso_Latn""",
    """Turkmen""": """tuk_Latn""",
    """Tumbuka""": """tum_Latn""",
    """Turkish""": """tur_Latn""",
    """Twi""": """twi_Latn""",
    """Central Atlas Tamazight""": """tzm_Tfng""",
    """Uyghur""": """uig_Arab""",
    """Ukrainian""": """ukr_Cyrl""",
    """Umbundu""": """umb_Latn""",
    """Urdu""": """urd_Arab""",
    """Northern Uzbek""": """uzn_Latn""",
    """Venetian""": """vec_Latn""",
    """Vietnamese""": """vie_Latn""",
    """Waray""": """war_Latn""",
    """Wolof""": """wol_Latn""",
    """Xhosa""": """xho_Latn""",
    """Eastern Yiddish""": """ydd_Hebr""",
    """Yoruba""": """yor_Latn""",
    """Yue Chinese""": """yue_Hant""",
    """Chinese Simplified""": """zho_Hans""",
    """Chinese Traditional""": """zho_Hant""",
    """Standard Malay""": """zsm_Latn""",
    """Zulu""": """zul_Latn""",
}


class 						lowercase    (							SCREAMING_SNAKE_CASE_):
						'''simple docstring'''


						UpperCAmelCase			:		Union[str, Any]		=		'facebook/nllb-200-distilled-600M'
						UpperCAmelCase			:		Union[str, Any]		=		(
						    'This is a tool that translates text from a language to another. It takes three inputs: `text`, which should '
						    'be the text to translate, `src_lang`, which should be the language of the text to translate and `tgt_lang`, '
						    'which should be the language for the desired ouput language. Both `src_lang` and `tgt_lang` are written in '
						    'plain English, such as \'Romanian\', or \'Albanian\'. It returns the text translated in `tgt_lang`.'
						)
						UpperCAmelCase			:		int		=		'translator'
						UpperCAmelCase			:		Any		=		AutoTokenizer
						UpperCAmelCase			:		Optional[int]		=		AutoModelForSeqaSeqLM
						UpperCAmelCase			:		int		=		LANGUAGE_CODES

						UpperCAmelCase			:		Union[str, Any]		=		['text', 'text', 'text']
						UpperCAmelCase			:		str		=		['text']







						def       lowerCamelCase_				(  self    :				Any       ,	snake_case    :				List[Any]       ,	snake_case    :				Any       ,	snake_case    :				Optional[Any]	):



											'''simple docstring'''


											if src_lang not in self.lang_to_code:
																raise ValueError(f'''{src_lang} is not a supported language.'''	)
											if tgt_lang not in self.lang_to_code:
																raise ValueError(f'''{tgt_lang} is not a supported language.'''	)
											SCREAMING_SNAKE_CASE							:     List[str]						=				self.lang_to_code[src_lang]
											SCREAMING_SNAKE_CASE							:     Tuple						=				self.lang_to_code[tgt_lang]
											return self.pre_processor._build_translation_inputs(
											    snake_case       ,	return_tensors='pt'       ,	src_lang=snake_case       ,	tgt_lang=snake_case	)







						def       lowerCamelCase_				(  self    :				Tuple       ,	snake_case    :				Optional[int]	):



											'''simple docstring'''


											return self.model.generate(**snake_case	)







						def       lowerCamelCase_				(  self    :				Optional[Any]       ,	snake_case    :				List[str]	):



											'''simple docstring'''


											return self.post_processor.decode(outputs[0].tolist()       ,	skip_special_tokens=snake_case	)




import json
import os
from collections import Counter

import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset


_lowerCamelCase    :		Dict		      =    {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3, 2), 7: (7, 1), 8: (4, 2), 9: (3, 3)}


class 						lowercase    (							nn.Module):
						'''simple docstring'''


						def __init__(  self    :				Optional[Any]       ,	snake_case    :				int	):



											'''simple docstring'''


											super().__init__()
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				torchvision.models.resnetaaa(pretrained=snake_case	)
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				list(model.children()	)[:-2]
											SCREAMING_SNAKE_CASE							:     List[str]						=				nn.Sequential(*snake_case	)
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				nn.AdaptiveAvgPoolad(POOLING_BREAKDOWN[args.num_image_embeds]	)







						def       lowerCamelCase_				(  self    :				Any       ,	snake_case    :				Optional[Any]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Optional[int]						=				self.pool(self.model(snake_case	)	)
											SCREAMING_SNAKE_CASE							:     Any						=				torch.flatten(snake_case       ,	start_dim=2	)
											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				out.transpose(1       ,	2	).contiguous()
											return out  # BxNx2048


class 						lowercase    (							SCREAMING_SNAKE_CASE_):
						'''simple docstring'''


						def __init__(  self    :				str       ,	snake_case    :				Optional[Any]       ,	snake_case    :				Union[str, Any]       ,	snake_case    :				Optional[int]       ,	snake_case    :				int       ,	snake_case    :				Optional[Any]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				[json.loads(snake_case	) for l in open(snake_case	)]
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				os.path.dirname(snake_case	)
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				tokenizer
											SCREAMING_SNAKE_CASE							:     Dict						=				labels
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				len(snake_case	)
											SCREAMING_SNAKE_CASE							:     int						=				max_seq_length

											SCREAMING_SNAKE_CASE							:     List[Any]						=				transforms







						def __len__(  self    :				str	):



											'''simple docstring'''


											return len(self.data	)







						def __getitem__(  self    :				Dict       ,	snake_case    :				int	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Optional[int]						=				torch.LongTensor(self.tokenizer.encode(self.data[index]['text']       ,	add_special_tokens=snake_case	)	)
											SCREAMING_SNAKE_CASE					,  SCREAMING_SNAKE_CASE					,  SCREAMING_SNAKE_CASE							:     Optional[Any]						=				sentence[0], sentence[1:-1], sentence[-1]
											SCREAMING_SNAKE_CASE							:     str						=				sentence[: self.max_seq_length]

											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				torch.zeros(self.n_classes	)
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				1

											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				Image.open(os.path.join(self.data_dir       ,	self.data[index]['img']	)	).convert('RGB'	)
											SCREAMING_SNAKE_CASE							:     Tuple						=				self.transforms(snake_case	)

											return {
											    "image_start_token": start_token,
											    "image_end_token": end_token,
											    "sentence": sentence,
											    "image": image,
											    "label": label,
											}







						def       lowerCamelCase_				(  self    :				Any	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     int						=				Counter()
											for row in self.data:
																label_freqs.update(row['label']	)
											return label_freqs


def        __a			(   __lowerCAmelCase   )     ->     Union[str, Any]:
					SCREAMING_SNAKE_CASE							:     str						=				[len(row['sentence']   ) for row in batch]
					SCREAMING_SNAKE_CASE					,  SCREAMING_SNAKE_CASE							:     Dict						=				len(__lowerCAmelCase   ), max(__lowerCAmelCase   )

					SCREAMING_SNAKE_CASE							:     List[Any]						=				torch.zeros(__lowerCAmelCase      ,	__lowerCAmelCase      ,	dtype=torch.long   )
					SCREAMING_SNAKE_CASE							:     List[str]						=				torch.zeros(__lowerCAmelCase      ,	__lowerCAmelCase      ,	dtype=torch.long   )

					for i_batch, (input_row, length) in enumerate(zip(__lowerCAmelCase      ,	__lowerCAmelCase   )   ):
										SCREAMING_SNAKE_CASE							:     Optional[Any]						=				input_row['sentence']
										SCREAMING_SNAKE_CASE							:     Optional[Any]						=				1

					SCREAMING_SNAKE_CASE							:     List[str]						=				torch.stack([row['image'] for row in batch]   )
					SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				torch.stack([row['label'] for row in batch]   )
					SCREAMING_SNAKE_CASE							:     Tuple						=				torch.stack([row['image_start_token'] for row in batch]   )
					SCREAMING_SNAKE_CASE							:     Any						=				torch.stack([row['image_end_token'] for row in batch]   )

					return text_tensor, mask_tensor, img_tensor, img_start_token, img_end_token, tgt_tensor

def        __a			(   )     ->     str:
					return [
					    "Crime",
					    "Drama",
					    "Thriller",
					    "Action",
					    "Comedy",
					    "Romance",
					    "Documentary",
					    "Short",
					    "Mystery",
					    "History",
					    "Family",
					    "Adventure",
					    "Fantasy",
					    "Sci-Fi",
					    "Western",
					    "Horror",
					    "Sport",
					    "War",
					    "Music",
					    "Musical",
					    "Animation",
					    "Biography",
					    "Film-Noir",
					]



def        __a			(   )     ->     Union[str, Any]:
					return transforms.Compose(
					    [
					        transforms.Resize(256   ),
					        transforms.CenterCrop(224   ),
					        transforms.ToTensor(),
					        transforms.Normalize(
					            mean=[0.46_777_044, 0.44_531_429, 0.40_661_017]      ,	std=[0.12_221_994, 0.12_145_835, 0.14_380_469]      ,	),
					    ]   )