






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


A__           =							{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   _lowerCAmelCase		(     nn.Module				):







							def __init__(				self     :    List[Any]	,					__snake_case     :    List[Any]		):
										super().__init__()
										lowerCamelCase						:Any						  =     torchvision.models.resnetaaa(pretrained=__lowercase		)
										lowerCamelCase						:str						  =     list(model.children()		)[:-2]
										lowerCamelCase						:Any						  =     nn.Sequential(*__lowercase		)
										lowerCamelCase						:str						  =     nn.AdaptiveAvgPoolad(POOLING_BREAKDOWN[args.num_image_embeds]		)







							def 				snake_case  (				self     :    Union[str, Any]	,					__snake_case     :    Dict		):
										# Bx3x224x224 -> Bx2048x7x7 -> Bx2048xN -> BxNx2048
										lowerCamelCase						:Union[str, Any]						  =     self.pool(self.model(__lowercase		)		)
										lowerCamelCase						:Tuple						  =     torch.flatten(__lowercase	,					start_dim=2		)
										lowerCamelCase						:List[Any]						  =     out.transpose(1	,					2		).contiguous()
										return out  # BxNx2048


class   _lowerCAmelCase		(     lowercase__				):







							def __init__(				self     :    Any	,					__snake_case     :    List[Any]	,					__snake_case     :    Optional[Any]	,					__snake_case     :    Tuple	,					__snake_case     :    Optional[Any]	,					__snake_case     :    Optional[int]		):
										lowerCamelCase						:Tuple						  =     [json.loads(__lowercase		) for l in open(__lowercase		)]
										lowerCamelCase						:List[Any]						  =     os.path.dirname(__lowercase		)
										lowerCamelCase						:Optional[int]						  =     tokenizer
										lowerCamelCase						:int						  =     labels
										lowerCamelCase						:str						  =     len(__lowercase		)
										lowerCamelCase						:Any						  =     max_seq_length

										lowerCamelCase						:Dict						  =     transforms







							def __len__(				self     :    str		):
										return len(self.data		)







							def __getitem__(				self     :    List[str]	,					__snake_case     :    Tuple		):
										lowerCamelCase						:Dict						  =     torch.LongTensor(self.tokenizer.encode(self.data[index]['''text''']	,					add_special_tokens=__lowercase		)		)
										lowerCamelCase  ,    lowerCamelCase  ,    lowerCamelCase						:int						  =     sentence[0], sentence[1:-1], sentence[-1]
										lowerCamelCase						:Tuple						  =     sentence[: self.max_seq_length]

										lowerCamelCase						:Optional[int]						  =     torch.zeros(self.n_classes		)
										lowerCamelCase						:Tuple						  =     1

										lowerCamelCase						:List[str]						  =     Image.open(os.path.join(self.data_dir	,					self.data[index]['''img''']		)		).convert('''RGB'''		)
										lowerCamelCase						:int						  =     self.transforms(__lowercase		)

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







							def 				snake_case  (				self     :    Any		):
										lowerCamelCase						:Any						  =     Counter()
										for row in self.data:
													label_freqs.update(row['''label''']		)
										return label_freqs





def  _lowerCamelCase					(   a_				: Optional[Any]):
			lowerCamelCase						:str						  =     [len(row['''sentence''']) for row in batch]
			lowerCamelCase  ,    lowerCamelCase						:Optional[Any]						  =     len(SCREAMING_SNAKE_CASE_), max(SCREAMING_SNAKE_CASE_)

			lowerCamelCase						:int						  =     torch.zeros(SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_						,			dtype=torch.long)
			lowerCamelCase						:Dict						  =     torch.zeros(SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_						,			dtype=torch.long)

			for i_batch, (input_row, length) in enumerate(zip(SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_)):
						lowerCamelCase						:Any						  =     input_row['''sentence''']
						lowerCamelCase						:Union[str, Any]						  =     1

			lowerCamelCase						:List[str]						  =     torch.stack([row['''image'''] for row in batch])
			lowerCamelCase						:Tuple						  =     torch.stack([row['''label'''] for row in batch])
			lowerCamelCase						:int						  =     torch.stack([row['''image_start_token'''] for row in batch])
			lowerCamelCase						:Union[str, 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  _lowerCamelCase					(   ):
			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  _lowerCamelCase					(   ):
			return transforms.Compose(
			    [
			        transforms.Resize(2_56),
			        transforms.CenterCrop(2_24),
			        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]						,			),
			    ])




import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     ''
							_UpperCAmelCase						    =     (
							    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
							)
							_UpperCAmelCase						    =     None  # compression type in fsspec. ex: "gzip"
							_UpperCAmelCase						    =     None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz







							def __init__(				self     :    str	,					__snake_case     :    str = ""	,					__snake_case     :    Optional[str] = None	,					__snake_case     :    Optional[dict] = None	,					**__snake_case     :    Dict		):
										super().__init__(self	,					**__snake_case		)
										# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
										lowerCamelCase						:Optional[Any]						  =     fsspec.open(
										    __snake_case	,					mode='''rb'''	,					protocol=__snake_case	,					compression=self.compression	,					client_kwargs={
										        '''requote_redirect_url''': False,  # see https://github.com/huggingface/datasets/pull/5459
										        '''trust_env''': True,  # Enable reading proxy env variables.
										        **(target_options or {}).pop('''client_kwargs'''	,					{}		),  # To avoid issues if it was already passed.
										    }	,					**(target_options or {})	,					)
										lowerCamelCase						:List[str]						  =     os.path.basename(self.file.path.split('''::'''		)[0]		)
										lowerCamelCase						:Dict						  =     (
										    self.compressed_name[: self.compressed_name.rindex('''.'''		)]
										    if '''.''' in self.compressed_name
										    else self.compressed_name
										)
										lowerCamelCase						:List[str]						  =     None







							@classmethod
							def 				snake_case  (				cls     :    Any	,					__snake_case     :    Any		):
										# compressed file paths are always relative to the archive root
										return super()._strip_protocol(__snake_case		).lstrip('''/'''		)







							def 				snake_case  (				self     :    Any		):
										if self.dir_cache is None:
													lowerCamelCase						:Optional[Any]						  =     {**self.file.fs.info(self.file.path		), '''name''': self.uncompressed_name}
													lowerCamelCase						:Optional[Any]						  =     {f['''name''']: f}







							def 				snake_case  (				self     :    Union[str, Any]	,					__snake_case     :    str		):
										return self.file.open().read()







							def 				snake_case  (				self     :    Optional[int]	,					__snake_case     :    str	,					__snake_case     :    str = "rb"	,					__snake_case     :    int=None	,					__snake_case     :    Optional[int]=True	,					__snake_case     :    str=None	,					**__snake_case     :    str	,					):
										lowerCamelCase						:List[str]						  =     self._strip_protocol(__snake_case		)
										if mode != "rb":
													raise ValueError(F"Tried to read with mode {mode} on file {self.file.path} opened with mode 'rb'"		)
										return self.file.open()


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'bz2'
							_UpperCAmelCase						    =     'bz2'
							_UpperCAmelCase						    =     '.bz2'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'gzip'
							_UpperCAmelCase						    =     'gzip'
							_UpperCAmelCase						    =     '.gz'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'lz4'
							_UpperCAmelCase						    =     'lz4'
							_UpperCAmelCase						    =     '.lz4'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'xz'
							_UpperCAmelCase						    =     'xz'
							_UpperCAmelCase						    =     '.xz'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'zstd'
							_UpperCAmelCase						    =     'zstd'
							_UpperCAmelCase						    =     '.zst'







							def __init__(				self     :    str	,					__snake_case     :    str	,					__snake_case     :    str = "rb"	,					__snake_case     :    Optional[str] = None	,					__snake_case     :    Optional[dict] = None	,					__snake_case     :    int = DEFAULT_BLOCK_SIZE	,					**__snake_case     :    int	,					):
										super().__init__(
										    fo=__snake_case	,					mode=__snake_case	,					target_protocol=__snake_case	,					target_options=__snake_case	,					block_size=__snake_case	,					**__snake_case	,					)
										# We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
										#
										# File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
										#     out.close = close
										# AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
										#
										# see https://github.com/intake/filesystem_spec/issues/725
										lowerCamelCase						:Tuple						  =     self.file.__enter__
										class   _lowerCAmelCase		:







																	def __init__(				self     :    Dict	,					__snake_case     :    Tuple		):
																				lowerCamelCase						:Optional[int]						  =     file_







																	def __enter__(				self     :    Optional[int]		):
																				self._file.__enter__()
																				return self







																	def __exit__(				self     :    str	,					*__snake_case     :    Optional[Any]	,					**__snake_case     :    List[Any]		):
																				self._file.__exit__(*__snake_case	,					**__snake_case		)







																	def __iter__(				self     :    Optional[Any]		):
																				return iter(self._file		)







																	def 				snake_case  (				self     :    List[Any]		):
																				return next(self._file		)







																	def __getattr__(				self     :    Any	,					__snake_case     :    str		):
																				return getattr(self._file	,					__snake_case		)

										def fixed_enter(*__snake_case     :    Optional[int]	,					**__snake_case     :    str		):
													return WrappedFile(_enter(*__snake_case	,					**__snake_case		)		)

										lowerCamelCase						:Dict						  =     fixed_enter



