


"""simple docstring"""




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


__magic_name__						: str    =				{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 			__snake_case   (nn.Module  ):




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




							def   __a   (     self:    Dict     ,							A_:    int   ):
										# Bx3x224x224 -> Bx2048x7x7 -> Bx2048xN -> BxNx2048
										__lowerCamelCase          =      self.pool(self.model(A_   )   )
										__lowerCamelCase          =      torch.flatten(A_     ,							start_dim=2   )
										__lowerCamelCase          =      out.transpose(1     ,							2   ).contiguous()
										return out  # BxNx2048




class 			__snake_case   (lowerCamelCase  ):




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

										__lowerCamelCase          =      transforms




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




							def __getitem__(     self:    str     ,							A_:    Any   ):
										__lowerCamelCase          =      torch.LongTensor(self.tokenizer.encode(self.data[index]["""text"""]     ,							add_special_tokens=A_   )   )
										__lowerCamelCase     ,__lowerCamelCase     ,__lowerCamelCase          =      sentence[0], sentence[1:-1], sentence[-1]
										__lowerCamelCase          =      sentence[: self.max_seq_length]

										__lowerCamelCase          =      torch.zeros(self.n_classes   )
										__lowerCamelCase          =      1

										__lowerCamelCase          =      Image.open(os.path.join(self.data_dir     ,							self.data[index]["""img"""]   )   ).convert("""RGB"""   )
										__lowerCamelCase          =      self.transforms(A_   )

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




							def   __a   (     self:    Optional[int]   ):
										__lowerCamelCase          =      Counter()
										for row in self.data:
													label_freqs.update(row["""label"""]   )
										return label_freqs





def       a_ (	lowercase__ :Union[str, Any]     ):
			__lowerCamelCase          =      [len(row["""sentence"""]     ) for row in batch]
			__lowerCamelCase     ,__lowerCamelCase          =      len(lowercase__     ), max(lowercase__     )

			__lowerCamelCase          =      torch.zeros(lowercase__,			lowercase__,			dtype=torch.long     )
			__lowerCamelCase          =      torch.zeros(lowercase__,			lowercase__,			dtype=torch.long     )

			for i_batch, (input_row, length) in enumerate(zip(lowercase__,			lowercase__     )     ):
						__lowerCamelCase          =      input_row["""sentence"""]
						__lowerCamelCase          =      1

			__lowerCamelCase          =      torch.stack([row["""image"""] for row in batch]     )
			__lowerCamelCase          =      torch.stack([row["""label"""] for row in batch]     )
			__lowerCamelCase          =      torch.stack([row["""image_start_token"""] for row in batch]     )
			__lowerCamelCase          =      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_ (	):
			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_ (	):
			return transforms.Compose(
			    [
			        transforms.Resize(256     ),
			        transforms.CenterCrop(224     ),
			        transforms.ToTensor(),
			        transforms.Normalize(
			            mean=[0.46777044, 0.44531429, 0.40661017],			std=[0.12221994, 0.12145835, 0.14380469],			),
			    ]     )








"""simple docstring"""




import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


__magic_name__						: Tuple    =				'hf-internal-testing/tiny-random-bert'
__magic_name__						: Dict    =				os.path.join(TRANSFORMERS_CACHE, 'models--hf-internal-testing--tiny-random-bert')
__magic_name__						: Optional[Any]    =				'9b8c223d42b2188cb49d29af482996f9d0f3e5a6'




class 			__snake_case   (unittest.TestCase  ):




							def   __a   (     self:    List[Any]   ):
										__lowerCamelCase          =      cached_file(A_     ,							A_   )
										# Should have downloaded the file in here
										self.assertTrue(os.path.isdir(A_   )   )
										# Cache should contain at least those three subfolders:
										for subfolder in ["blobs", "refs", "snapshots"]:
													self.assertTrue(os.path.isdir(os.path.join(A_     ,							A_   )   )   )
										with open(os.path.join(A_     ,							"""refs"""     ,							"""main"""   )   ) as f:
													__lowerCamelCase          =      f.read()
										self.assertEqual(A_     ,							os.path.join(A_     ,							"""snapshots"""     ,							A_     ,							A_   )   )
										self.assertTrue(os.path.isfile(A_   )   )

										# File is cached at the same place the second time.
										__lowerCamelCase          =      cached_file(A_     ,							A_   )
										self.assertEqual(A_     ,							A_   )

										# Using a specific revision to test the full commit hash.
										__lowerCamelCase          =      cached_file(A_     ,							A_     ,							revision="""9b8c223"""   )
										self.assertEqual(A_     ,							os.path.join(A_     ,							"""snapshots"""     ,							A_     ,							A_   )   )




							def   __a   (     self:    int   ):
										with self.assertRaisesRegex(A_     ,							"""is not a valid model identifier"""   ):
													__lowerCamelCase          =      cached_file("""tiny-random-bert"""     ,							A_   )

										with self.assertRaisesRegex(A_     ,							"""is not a valid git identifier"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							A_     ,							revision="""aaaa"""   )

										with self.assertRaisesRegex(A_     ,							"""does not appear to have a file named"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""   )




							def   __a   (     self:    Optional[int]   ):
										with self.assertRaisesRegex(A_     ,							"""does not appear to have a file named"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""   )

										with open(os.path.join(A_     ,							"""refs"""     ,							"""main"""   )   ) as f:
													__lowerCamelCase          =      f.read()
										self.assertTrue(os.path.isfile(os.path.join(A_     ,							""".no_exist"""     ,							A_     ,							"""conf"""   )   )   )

										__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							_raise_exceptions_for_missing_entries=A_   )
										self.assertIsNone(A_   )

										__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							local_files_only=A_     ,							_raise_exceptions_for_missing_entries=A_   )
										self.assertIsNone(A_   )

										__lowerCamelCase          =      mock.Mock()
										__lowerCamelCase          =      5_00
										__lowerCamelCase          =      {}
										__lowerCamelCase          =      HTTPError
										__lowerCamelCase          =      {}

										# Under the mock environment we get a 500 error when trying to reach the tokenizer.
										with mock.patch("""requests.Session.request"""     ,							return_value=A_   ) as mock_head:
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							_raise_exceptions_for_connection_errors=A_   )
													self.assertIsNone(A_   )
													# This check we did call the fake head request
													mock_head.assert_called()




							def   __a   (     self:    str   ):
										self.assertTrue(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )




							def   __a   (     self:    str   ):
										# `get_file_from_repo` returns None if the file does not exist
										self.assertIsNone(get_file_from_repo("""bert-base-cased"""     ,							"""ahah.txt"""   )   )

										# The function raises if the repository does not exist.
										with self.assertRaisesRegex(A_     ,							"""is not a valid model identifier"""   ):
													get_file_from_repo("""bert-base-case"""     ,							A_   )

										# The function raises if the revision does not exist.
										with self.assertRaisesRegex(A_     ,							"""is not a valid git identifier"""   ):
													get_file_from_repo("""bert-base-cased"""     ,							A_     ,							revision="""ahaha"""   )

										__lowerCamelCase          =      get_file_from_repo("""bert-base-cased"""     ,							A_   )
										# The name is the cached name which is not very easy to test, so instead we load the content.
										__lowerCamelCase          =      json.loads(open(A_     ,							"""r"""   ).read()   )
										self.assertEqual(config["""hidden_size"""]     ,							7_68   )




							def   __a   (     self:    Union[str, Any]   ):
										with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCamelCase          =      Path(A_   ) / """a.txt"""
													filename.touch()
													self.assertEqual(get_file_from_repo(A_     ,							"""a.txt"""   )     ,							str(A_   )   )

													self.assertIsNone(get_file_from_repo(A_     ,							"""b.txt"""   )   )




