




"""simple docstring"""



import json
import os
from datetime import date
from pathlib import Path

from tabulate import DataRow, TableFormat, tabulate


SCREAMING_SNAKE_CASE    =	TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow("", "|", "|"),
    datarow=DataRow("", "|", "|"),
    padding=1,
    with_header_hide=None,
)


SCREAMING_SNAKE_CASE    =	[]
SCREAMING_SNAKE_CASE    =	[]

SCREAMING_SNAKE_CASE    =	{"type": "section", "text": {"type": "plain_text", "text": "No failed tests! 🤗", "emoji": True}}

SCREAMING_SNAKE_CASE    =	[
    {
        "type": "header",
        "text": {
            "type": "plain_text",
            "text": f'🤗 Accelerate nightly {os.environ.get("TEST_TYPE", "")} test results',
            "emoji": True,
        },
    }
]

SCREAMING_SNAKE_CASE    =	0
for log in Path().glob("*.log"):
      SCREAMING_SNAKE_CASE    =	0
      with open(log, "r") as f:
            for line in f:
                  SCREAMING_SNAKE_CASE    =	json.loads(line)
                  if line.get("nodeid", "") != "":
                        SCREAMING_SNAKE_CASE    =	line["nodeid"]
                        if line.get("duration", None) is not None:
                              SCREAMING_SNAKE_CASE    =	f'{line["duration"]:.4f}'
                              if line.get("outcome", "") == "failed":
                                    section_num_failed += 1
                                    failed.append([test, duration, log.name.split("_")[0]])
                                    total_num_failed += 1
      group_info.append([str(log), section_num_failed, failed])
      SCREAMING_SNAKE_CASE    =	[]
      log.unlink()

SCREAMING_SNAKE_CASE    =	""
SCREAMING_SNAKE_CASE    =	[]
if total_num_failed > 0:
      for name, num_failed, failed_tests in group_info:
            if num_failed > 0:
                  if num_failed == 1:
                        message += f"*{name[1:]}: {num_failed} failed test*\n"
                  else:
                        message += f"*{name[1:]}: {num_failed} failed tests*\n"
                  SCREAMING_SNAKE_CASE    =	[]
                  SCREAMING_SNAKE_CASE    =	{}
                  for test in failed_tests:
                        SCREAMING_SNAKE_CASE    =	test[0].split("::")
                        SCREAMING_SNAKE_CASE    =	data[0].split("/")[-1]
                        if data[0] not in filesafailed:
                              SCREAMING_SNAKE_CASE    =	[data[1:]]
                        else:
                              filesafailed[data[0]] += [data[1:]]
                        failed_table.append(data)

                  SCREAMING_SNAKE_CASE    =	[test[0] for test in failed_table]
                  SCREAMING_SNAKE_CASE    =	list(set(files))
                  # Count number of instances in failed_tests
                  SCREAMING_SNAKE_CASE    =	[]
                  for file in individual_files:
                        table.append([file, len(filesafailed[file])])

                  SCREAMING_SNAKE_CASE    =	tabulate(
                      table,
                      headers=["Test Location", "Num Failed"],
                      tablefmt=hf_table_format,
                      stralign="right",
                  )
                  message += f"\n```\n{failed_table}\n```"
                  all_filesafailed.append(filesafailed)
      if len(message) > 3000:
            SCREAMING_SNAKE_CASE    =	"Too many failed tests, please see the full report in the Action results."
            SCREAMING_SNAKE_CASE    =	len(err) + 10
            SCREAMING_SNAKE_CASE    =	message[: 3000 - offset] + f'\n...\n```\n{err}'
      print(f'### {message}')
else:
      SCREAMING_SNAKE_CASE    =	"No failed tests! 🤗"
      print(f'## {message}')
      payload.append(no_error_payload)

if os.environ.get("TEST_TYPE", "") != "":
      from slack_sdk import WebClient

      SCREAMING_SNAKE_CASE    =	WebClient(token=os.environ["SLACK_API_TOKEN"])
      if message != "No failed tests! 🤗":
            SCREAMING_SNAKE_CASE    =	{
                "type": "section",
                "text": {
                    "type": "mrkdwn",
                    "text": message,
                },
            }
            payload.append(md_report)
            SCREAMING_SNAKE_CASE    =	{
                "type": "section",
                "text": {
                    "type": "mrkdwn",
                    "text": "*For more details:*",
                },
                "accessory": {
                    "type": "button",
                    "text": {
                        "type": "plain_text",
                        "text": "Check Action results",
                        "emoji": True,
                    },
                    "url": f'https://github.com/{os.environ["GITHUB_REPOSITORY"]}/actions/runs/{os.environ["GITHUB_RUN_ID"]}',
                },
            }
            payload.append(action_button)
            SCREAMING_SNAKE_CASE    =	{
                "type": "context",
                "elements": [
                    {
                        "type": "plain_text",
                        "text": f'Nightly {os.environ.get("TEST_TYPE")} test results for {date.today()}',
                    }
                ],
            }
            payload.append(date_report)
      SCREAMING_SNAKE_CASE    =	client.chat_postMessage(channel="#accelerate-ci-daily", text=message, blocks=payload)
      SCREAMING_SNAKE_CASE    =	response.data["ts"]
      for failed_file in all_filesafailed:
            for test_location, test_failures in failed_file.items():
                  # Keep only the first instance of the test name
                  SCREAMING_SNAKE_CASE    =	""
                  for i, row in enumerate(test_failures):
                        if row[0] != test_class:
                              SCREAMING_SNAKE_CASE    =	row[0]
                        else:
                              SCREAMING_SNAKE_CASE    =	""

                  SCREAMING_SNAKE_CASE    =	{
                      "type": "section",
                      "text": {
                          "type": "mrkdwn",
                          "text": f'Test location: {test_location}\n```\n{tabulate(test_failures, headers=["Class", "Test"], tablefmt=hf_table_format, stralign="right")}\n```',
                      },
                  }

                  client.chat_postMessage(
                      channel="#accelerate-ci-daily",
                      thread_ts=ts,
                      blocks=[payload],
                  )











"""simple docstring"""



import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class      UpperCAmelCase_  (						A_							):
    lowercase__						 =				['''image_processor''', '''tokenizer''']
    lowercase__						 =				'''ViTImageProcessor'''
    lowercase__						 =				('''CLIPTokenizer''', '''CLIPTokenizerFast''')




    def __init__(   self						:	Optional[Any]     ,			snake_case_						:	Union[str, Any]=None     ,			snake_case_						:	Dict=None     ,			**snake_case_						:	Optional[Any]				)				->							List[str]:




     '''simple docstring'''

     A__	=    None
     if "feature_extractor" in kwargs:
      warnings.warn(
          "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
          " instead."     ,			snake_case_     ,			)
      A__	=    kwargs.pop("feature_extractor"				)

     A__	=    image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
      raise ValueError("You need to specify an `image_processor`."				)
     if tokenizer is None:
      raise ValueError("You need to specify a `tokenizer`."				)

     super().__init__(snake_case_     ,			snake_case_				)




    def __call__(   self						:	int     ,			snake_case_						:	Union[str, Any]=None     ,			snake_case_						:	int=None     ,			snake_case_						:	Dict=None     ,			snake_case_						:	int=None     ,			**snake_case_						:	List[str]				)				->							Union[str, Any]:




     '''simple docstring'''

     if text is None and visual_prompt is None and images is None:
      raise ValueError("You have to specify either text, visual prompt or images."				)

     if text is not None and visual_prompt is not None:
      raise ValueError("You have to specify exactly one type of prompt. Either text or visual prompt."				)

     if text is not None:
      A__	=    self.tokenizer(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if visual_prompt is not None:
      A__	=    self.image_processor(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if images is not None:
      A__	=    self.image_processor(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if visual_prompt is not None and images is not None:
      A__	=    {
          "pixel_values": image_features.pixel_values,
          "conditional_pixel_values": prompt_features.pixel_values,
      }
      return encoding
     elif text is not None and images is not None:
      A__	=    image_features.pixel_values
      return encoding
     elif text is not None:
      return encoding
     elif visual_prompt is not None:
      A__	=    {
          "conditional_pixel_values": prompt_features.pixel_values,
      }
      return encoding
     else:
      return BatchEncoding(data=dict(**snake_case_				)     ,			tensor_type=snake_case_				)




    def 							__magic_name__							(   self						:	Tuple     ,			*snake_case_						:	List[str]     ,			**snake_case_						:	Optional[int]				)				->							str:




     '''simple docstring'''

     return self.tokenizer.batch_decode(*snake_case_     ,			**snake_case_				)




    def 							__magic_name__							(   self						:	Optional[Any]     ,			*snake_case_						:	Any     ,			**snake_case_						:	List[Any]				)				->							List[str]:




     '''simple docstring'''

     return self.tokenizer.decode(*snake_case_     ,			**snake_case_				)




    @property
    def 							__magic_name__							(   self						:	int				)				->							Optional[int]:




     '''simple docstring'''

     warnings.warn(
         "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."     ,			snake_case_     ,			)
     return self.image_processor_class




    @property
    def 							__magic_name__							(   self						:	int				)				->							int:




     '''simple docstring'''

     warnings.warn(
         "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."     ,			snake_case_     ,			)
     return self.image_processor





