





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

from tabulate import DataRow, TableFormat, tabulate


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


_snake_case           =					[]
_snake_case           =					[]

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

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

_snake_case           =					0
for log in Path().glob("""*.log"""):
  _snake_case           =					0
  with open(log, """r""") as f:
    for line in f:
      _snake_case           =					json.loads(line)
      if line.get("""nodeid""", """""") != "":
        _snake_case           =					line["nodeid"]
        if line.get("""duration""", None) is not None:
          _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])
  _snake_case           =					[]
  log.unlink()

_snake_case           =					""
_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"
      _snake_case           =					[]
      _snake_case           =					{}
      for test in failed_tests:
        _snake_case           =					test[0].split("""::""")
        _snake_case           =					data[0].split("""/""")[-1]
        if data[0] not in filesafailed:
          _snake_case           =					[data[1:]]
        else:
          filesafailed[data[0]] += [data[1:]]
        failed_table.append(data)

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

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

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

  _snake_case           =					WebClient(token=os.environ["""SLACK_API_TOKEN"""])
  if message != "No failed tests! 🤗":
    _snake_case           =					{
        "type": "section",
        "text": {
            "type": "mrkdwn",
            "text": message,
        },
    }
    payload.append(md_report)
    _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)
    _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)
  _snake_case           =					client.chat_postMessage(channel="""#accelerate-ci-daily""", text=message, blocks=payload)
  _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
      _snake_case           =					""
      for i, row in enumerate(test_failures):
        if row[0] != test_class:
          _snake_case           =					row[0]
        else:
          _snake_case           =					""

      _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"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_				:      List[Any]           =			logging.get_logger(__name__)

A_				:      Optional[int]           =			{
    "facebook/dpr-ctx_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-single-nq-base": (
        "https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-ctx_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-multiset-base": (
        "https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"
    ),
}





class  lowerCamelCase    (A__      ):
			lowerCamelCase__ :		Optional[int]       		=				'dpr'

			def __init__(       self					:    Optional[int]     ,					__UpperCAmelCase					:    List[str]=3_0_5_2_2     ,					__UpperCAmelCase					:    int=7_6_8     ,					__UpperCAmelCase					:    Optional[Any]=1_2     ,					__UpperCAmelCase					:    Dict=1_2     ,					__UpperCAmelCase					:    Any=3_0_7_2     ,					__UpperCAmelCase					:    int="gelu"     ,					__UpperCAmelCase					:    int=0.1     ,					__UpperCAmelCase					:    Optional[Any]=0.1     ,					__UpperCAmelCase					:    Any=5_1_2     ,					__UpperCAmelCase					:    Union[str, Any]=2     ,					__UpperCAmelCase					:    Any=0.02     ,					__UpperCAmelCase					:    Dict=1e-12     ,					__UpperCAmelCase					:    Optional[Any]=0     ,					__UpperCAmelCase					:    Union[str, Any]="absolute"     ,					__UpperCAmelCase					:    int = 0     ,					**__UpperCAmelCase					:    Dict     ,					) ->     Tuple:
						super().__init__(pad_token_id=__UpperCAmelCase     ,					**__UpperCAmelCase							)

						SCREAMING_SNAKE_CASE__										=   vocab_size
						SCREAMING_SNAKE_CASE__										=   hidden_size
						SCREAMING_SNAKE_CASE__										=   num_hidden_layers
						SCREAMING_SNAKE_CASE__										=   num_attention_heads
						SCREAMING_SNAKE_CASE__										=   hidden_act
						SCREAMING_SNAKE_CASE__										=   intermediate_size
						SCREAMING_SNAKE_CASE__										=   hidden_dropout_prob
						SCREAMING_SNAKE_CASE__										=   attention_probs_dropout_prob
						SCREAMING_SNAKE_CASE__										=   max_position_embeddings
						SCREAMING_SNAKE_CASE__										=   type_vocab_size
						SCREAMING_SNAKE_CASE__										=   initializer_range
						SCREAMING_SNAKE_CASE__										=   layer_norm_eps
						SCREAMING_SNAKE_CASE__										=   projection_dim
						SCREAMING_SNAKE_CASE__										=   position_embedding_type


