





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import CLIPImageProcessor, CLIPProcessor
@require_vision
class        SCREAMING_SNAKE_CASE     (unittest.TestCase   ):


			def  SCREAMING_SNAKE_CASE_							(					self    :       List[str] )->     Optional[int]:





					"""simple docstring"""







					lowercase__			    =						tempfile.mkdtemp()

					# fmt: off
					lowercase__			    =						['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
					# fmt: on
					lowercase__			    =						dict(zip(_A    ,  range(len(_A ) ) ) )
					lowercase__			    =						['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
					lowercase__			    =						{'unk_token': '<unk>'}

					lowercase__			    =						os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES['vocab_file'] )
					lowercase__			    =						os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES['merges_file'] )
					with open(self.vocab_file    ,  'w'    ,  encoding='utf-8' ) as fp:
							fp.write(json.dumps(_A ) + '\n' )
					with open(self.merges_file    ,  'w'    ,  encoding='utf-8' ) as fp:
							fp.write('\n'.join(_A ) )

					lowercase__			    =						{
					    'do_resize': True,
					    'size': 20,
					    'do_center_crop': True,
					    'crop_size': 18,
					    'do_normalize': True,
					    'image_mean': [0.48145466, 0.4578275, 0.40821073],
					    'image_std': [0.26862954, 0.26130258, 0.27577711],
					}
					lowercase__			    =						os.path.join(self.tmpdirname    ,  _A )
					with open(self.image_processor_file    ,  'w'    ,  encoding='utf-8' ) as fp:
							json.dump(_A    ,  _A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       str    ,  **a    :       Union[str, Any] )->     Any:





					"""simple docstring"""







					return CLIPTokenizer.from_pretrained(self.tmpdirname    ,  **_A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any]    ,  **a    :       int )->     Optional[int]:





					"""simple docstring"""







					return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,  **_A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any]    ,  **a    :       int )->     Dict:





					"""simple docstring"""







					return CLIPImageProcessor.from_pretrained(self.tmpdirname    ,  **_A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     Union[str, Any]:





					"""simple docstring"""







					shutil.rmtree(self.tmpdirname )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     List[str]:





					"""simple docstring"""







					lowercase__			    =						[np.random.randint(255    ,  size=(3, 30, 400)    ,  dtype=np.uinta )]

					lowercase__			    =						[Image.fromarray(np.moveaxis(_A    ,  0    ,  -1 ) ) for x in image_inputs]

					return image_inputs


			def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     str:





					"""simple docstring"""







					lowercase__			    =						self.get_tokenizer()
					lowercase__			    =						self.get_rust_tokenizer()
					lowercase__			    =						self.get_image_processor()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )
					processor_slow.save_pretrained(self.tmpdirname )
					lowercase__			    =						CLIPProcessor.from_pretrained(self.tmpdirname    ,  use_fast=_A )

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )
					processor_fast.save_pretrained(self.tmpdirname )
					lowercase__			    =						CLIPProcessor.from_pretrained(self.tmpdirname )

					self.assertEqual(processor_slow.tokenizer.get_vocab()    ,  tokenizer_slow.get_vocab() )
					self.assertEqual(processor_fast.tokenizer.get_vocab()    ,  tokenizer_fast.get_vocab() )
					self.assertEqual(tokenizer_slow.get_vocab()    ,  tokenizer_fast.get_vocab() )
					self.assertIsInstance(processor_slow.tokenizer    ,  _A )
					self.assertIsInstance(processor_fast.tokenizer    ,  _A )

					self.assertEqual(processor_slow.image_processor.to_json_string()    ,  image_processor.to_json_string() )
					self.assertEqual(processor_fast.image_processor.to_json_string()    ,  image_processor.to_json_string() )
					self.assertIsInstance(processor_slow.image_processor    ,  _A )
					self.assertIsInstance(processor_fast.image_processor    ,  _A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     int:





					"""simple docstring"""







					lowercase__			    =						CLIPProcessor(tokenizer=self.get_tokenizer()    ,  image_processor=self.get_image_processor() )
					processor.save_pretrained(self.tmpdirname )

					lowercase__			    =						self.get_tokenizer(bos_token='(BOS)'    ,  eos_token='(EOS)' )
					lowercase__			    =						self.get_image_processor(do_normalize=_A    ,  padding_value=1.0 )

					lowercase__			    =						CLIPProcessor.from_pretrained(
					    self.tmpdirname    ,  bos_token='(BOS)'    ,  eos_token='(EOS)'    ,  do_normalize=_A    ,  padding_value=1.0 )

					self.assertEqual(processor.tokenizer.get_vocab()    ,  tokenizer_add_kwargs.get_vocab() )
					self.assertIsInstance(processor.tokenizer    ,  _A )

					self.assertEqual(processor.image_processor.to_json_string()    ,  image_processor_add_kwargs.to_json_string() )
					self.assertIsInstance(processor.image_processor    ,  _A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Optional[int]:





					"""simple docstring"""







					lowercase__			    =						self.get_image_processor()
					lowercase__			    =						self.get_tokenizer()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )

					lowercase__			    =						self.prepare_image_inputs()

					lowercase__			    =						image_processor(_A    ,  return_tensors='np' )
					lowercase__			    =						processor(images=_A    ,  return_tensors='np' )

					for key in input_image_proc.keys():
							self.assertAlmostEqual(input_image_proc[key].sum()    ,  input_processor[key].sum()    ,  delta=1E-2 )


			def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     Union[str, Any]:





					"""simple docstring"""







					lowercase__			    =						self.get_image_processor()
					lowercase__			    =						self.get_tokenizer()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )

					lowercase__			    =						'lower newer'

					lowercase__			    =						processor(text=_A )

					lowercase__			    =						tokenizer(_A )

					for key in encoded_tok.keys():
							self.assertListEqual(encoded_tok[key]    ,  encoded_processor[key] )


			def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     Any:





					"""simple docstring"""







					lowercase__			    =						self.get_image_processor()
					lowercase__			    =						self.get_tokenizer()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )

					lowercase__			    =						'lower newer'
					lowercase__			    =						self.prepare_image_inputs()

					lowercase__			    =						processor(text=_A    ,  images=_A )

					self.assertListEqual(list(inputs.keys() )    ,  ['input_ids', 'attention_mask', 'pixel_values'] )

					# test if it raises when no input is passed
					with pytest.raises(_A ):
							processor()


			def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     Optional[Any]:





					"""simple docstring"""







					lowercase__			    =						self.get_image_processor()
					lowercase__			    =						self.get_tokenizer()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )

					lowercase__			    =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					lowercase__			    =						processor.batch_decode(_A )
					lowercase__			    =						tokenizer.batch_decode(_A )

					self.assertListEqual(_A    ,  _A )


			def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     int:





					"""simple docstring"""







					lowercase__			    =						self.get_image_processor()
					lowercase__			    =						self.get_tokenizer()

					lowercase__			    =						CLIPProcessor(tokenizer=_A    ,  image_processor=_A )

					lowercase__			    =						'lower newer'
					lowercase__			    =						self.prepare_image_inputs()

					lowercase__			    =						processor(text=_A    ,  images=_A )

					self.assertListEqual(list(inputs.keys() )    ,  processor.model_input_names )









import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE=7	)       ->     List[Any]:
  lowercase__			    =						None
  if token is not None:
    lowercase__			    =						{'Accept': 'application/vnd.github+json', 'Authorization': F"""Bearer {token}"""}

  # The id of a workflow (not of a workflow run)
  lowercase__			    =						'636036'

  lowercase__			    =						F"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
  # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
  url += F"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

  lowercase__			    =						requests.get(_SCREAMING_SNAKE_CASE	,		headers=_SCREAMING_SNAKE_CASE	).json()

  return result["workflow_runs"]




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     Union[str, Any]:
  lowercase__			    =						get_daily_ci_runs(_SCREAMING_SNAKE_CASE	)
  lowercase__			    =						None
  for workflow_run in workflow_runs:
    if workflow_run["status"] == "completed":
      lowercase__			    =						workflow_run['id']
      break

  return workflow_run_id




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     Tuple:
  lowercase__			    =						get_last_daily_ci_runs(_SCREAMING_SNAKE_CASE	)
  if workflow_run_id is not None:
    lowercase__			    =						get_artifacts_links(worflow_run_id=_SCREAMING_SNAKE_CASE	,		token=_SCREAMING_SNAKE_CASE	)
    for artifact_name in artifact_names:
      if artifact_name in artifacts_links:
        lowercase__			    =						artifacts_links[artifact_name]
        download_artifact(
            artifact_name=_SCREAMING_SNAKE_CASE	,		artifact_url=_SCREAMING_SNAKE_CASE	,		output_dir=_SCREAMING_SNAKE_CASE	,		token=_SCREAMING_SNAKE_CASE	)




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     Dict:
  get_last_daily_ci_artifacts(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)

  lowercase__			    =						{}
  for artifact_name in artifact_names:
    lowercase__			    =						os.path.join(_SCREAMING_SNAKE_CASE	,		F"""{artifact_name}.zip"""	)
    if os.path.isfile(_SCREAMING_SNAKE_CASE	):
      lowercase__			    =						{}
      with zipfile.ZipFile(_SCREAMING_SNAKE_CASE	) as z:
        for filename in z.namelist():
          if not os.path.isdir(_SCREAMING_SNAKE_CASE	):
            # read the file
            with z.open(_SCREAMING_SNAKE_CASE	) as f:
              lowercase__			    =						f.read().decode('UTF-8'	)

  return results


