






'''simple docstring'''

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


UpperCamelCase      					=logging.get_logger(__name__)

UpperCamelCase      					={
    "google/realm-cc-news-pretrained-embedder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-encoder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-scorer": (
        "https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-openqa": (
        "https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"
    ),
    "google/realm-orqa-nq-openqa": "https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json",
    "google/realm-orqa-nq-reader": "https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json",
    "google/realm-orqa-wq-openqa": "https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json",
    "google/realm-orqa-wq-reader": "https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json",
    # See all REALM models at https://huggingface.co/models?filter=realm
}




class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    str			  =    '''realm'''
 def __init__(				self      ,  __lowerCAmelCase=3_05_22      ,  __lowerCAmelCase=7_68      ,  __lowerCAmelCase=1_28      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=8      ,  __lowerCAmelCase=30_72      ,  __lowerCAmelCase="gelu_new"      ,  __lowerCAmelCase=0.1      ,  __lowerCAmelCase=0.1      ,  __lowerCAmelCase=5_12      ,  __lowerCAmelCase=2      ,  __lowerCAmelCase=0.02      ,  __lowerCAmelCase=1E-12      ,  __lowerCAmelCase=2_56      ,  __lowerCAmelCase=10      ,  __lowerCAmelCase=1E-3      ,  __lowerCAmelCase=5      ,  __lowerCAmelCase=3_20      ,  __lowerCAmelCase=13_35_37_18      ,  __lowerCAmelCase=50_00      ,  __lowerCAmelCase=1      ,  __lowerCAmelCase=0      ,  __lowerCAmelCase=2      ,  **__lowerCAmelCase      ,  ):
       super().__init__(pad_token_id=__lowerCAmelCase      ,  bos_token_id=__lowerCAmelCase      ,  eos_token_id=__lowerCAmelCase      ,  **__lowerCAmelCase			)

       # Common config
       UpperCamelCase_					: Optional[int]            =				vocab_size
       UpperCamelCase_					: List[Any]            =				max_position_embeddings
       UpperCamelCase_					: str            =				hidden_size
       UpperCamelCase_					: str            =				retriever_proj_size
       UpperCamelCase_					: int            =				num_hidden_layers
       UpperCamelCase_					: int            =				num_attention_heads
       UpperCamelCase_					: str            =				num_candidates
       UpperCamelCase_					: Any            =				intermediate_size
       UpperCamelCase_					: int            =				hidden_act
       UpperCamelCase_					: List[str]            =				hidden_dropout_prob
       UpperCamelCase_					: List[Any]            =				attention_probs_dropout_prob
       UpperCamelCase_					: Union[str, Any]            =				initializer_range
       UpperCamelCase_					: str            =				type_vocab_size
       UpperCamelCase_					: Tuple            =				layer_norm_eps

       # Reader config
       UpperCamelCase_					: List[Any]            =				span_hidden_size
       UpperCamelCase_					: int            =				max_span_width
       UpperCamelCase_					: List[str]            =				reader_layer_norm_eps
       UpperCamelCase_					: Optional[int]            =				reader_beam_size
       UpperCamelCase_					: Any            =				reader_seq_len

       # Retrieval config
       UpperCamelCase_					: Tuple            =				num_block_records
       UpperCamelCase_					: str            =				searcher_beam_size














'''simple docstring'''

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

from tabulate import DataRow, TableFormat, tabulate


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


UpperCamelCase      					=[]
UpperCamelCase      					=[]

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

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

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

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

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

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

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

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

                  UpperCamelCase      					={
                      "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],
                  )






