'''simple docstring'''




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

from tabulate import DataRow, TableFormat, tabulate


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


_a   :	Union[str, Any] 							=   []
_a   :	str 							=   []

_a   :	List[Any] 							=   {"type": "section", "text": {"type": "plain_text", "text": "No failed tests! 🤗", "emoji": True}}

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

_a   :	str 							=   0
for log in Path().glob("*.log"):
   _a   :	Union[str, Any] 							=   0
   with open(log, "r") as f:
      for line in f:
         _a   :	Tuple 							=   json.loads(line)
         if line.get("nodeid", "") != "":
            _a   :	str 							=   line["nodeid"]
            if line.get("duration", None) is not None:
               _a   :	Tuple 							=   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])
   _a   :	Optional[int] 							=   []
   log.unlink()

_a   :	Tuple 							=   ""
_a   :	str 							=   []
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"
         _a   :	Tuple 							=   []
         _a   :	Dict 							=   {}
         for test in failed_tests:
            _a   :	Union[str, Any] 							=   test[0].split("::")
            _a   :	Any 							=   data[0].split("/")[-1]
            if data[0] not in filesafailed:
               _a   :	Optional[Any] 							=   [data[1:]]
            else:
               filesafailed[data[0]] += [data[1:]]
            failed_table.append(data)

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

         _a   :	int 							=   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:
      _a   :	Tuple 							=   "Too many failed tests, please see the full report in the Action results."
      _a   :	Dict 							=   len(err) + 10
      _a   :	Optional[Any] 							=   message[: 3000 - offset] + f"""\n...\n```\n{err}"""
   print(f"""### {message}""")
else:
   _a   :	Optional[Any] 							=   "No failed tests! 🤗"
   print(f"""## {message}""")
   payload.append(no_error_payload)

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

   _a   :	str 							=   WebClient(token=os.environ["SLACK_API_TOKEN"])
   if message != "No failed tests! 🤗":
      _a   :	Union[str, Any] 							=   {
          "type": "section",
          "text": {
              "type": "mrkdwn",
              "text": message,
          },
      }
      payload.append(md_report)
      _a   :	Dict 							=   {
          "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)
      _a   :	Tuple 							=   {
          "type": "context",
          "elements": [
              {
                  "type": "plain_text",
                  "text": f"""Nightly {os.environ.get('TEST_TYPE')} test results for {date.today()}""",
              }
          ],
      }
      payload.append(date_report)
   _a   :	Optional[Any] 							=   client.chat_postMessage(channel="#accelerate-ci-daily", text=message, blocks=payload)
   _a   :	int 							=   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
         _a   :	List[Any] 							=   ""
         for i, row in enumerate(test_failures):
            if row[0] != test_class:
               _a   :	Union[str, Any] 							=   row[0]
            else:
               _a   :	List[Any] 							=   ""

         _a   :	Union[str, Any] 							=   {
             "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'''




from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def _lowercase	(      )					->       Dict:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		HfArgumentParser(lowerCamelCase__						)
       __UpperCAmelCase  :				Optional[Any]       				=		parser.parse_args_into_dataclasses()[0]
       __UpperCAmelCase  :				Any       				=		TensorFlowBenchmark(args=lowerCamelCase__						)
       try:
              __UpperCAmelCase  :				List[Any]       				=		parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              __UpperCAmelCase  :				str       				=		"Arg --no_{0} is no longer used, please use --no-{0} instead."
              __UpperCAmelCase  :				Tuple       				=		" ".join(str(lowerCamelCase__						).split(" "						)[:-1]						)
              __UpperCAmelCase  :				Any       				=		""
              __UpperCAmelCase  :				List[Any]       				=		eval(str(lowerCamelCase__						).split(" "						)[-1]						)
              __UpperCAmelCase  :				Optional[int]       				=		[]
              for arg in depreciated_args:
                     # arg[2:] removes '--'
                     if arg[2:] in TensorFlowBenchmark.deprecated_args:
                            # arg[5:] removes '--no_'
                            full_error_msg += arg_error_msg.format(arg[5:]						)
                     else:
                            wrong_args.append(lowerCamelCase__						)
              if len(lowerCamelCase__						) > 0:
                     __UpperCAmelCase  :				Union[str, Any]       				=		full_error_msg + begin_error_msg + str(lowerCamelCase__						)
              raise ValueError(lowerCamelCase__						)
       benchmark.run()


if __name__ == "__main__":
   main()






