

"""simple docstring"""




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

from tabulate import DataRow, TableFormat, tabulate


A_				:      Union[str, Any]           =			TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow("", "|", "|"),
    datarow=DataRow("", "|", "|"),
    padding=1,
    with_header_hide=None,
)


A_				:      List[str]           =			[]
A_				:      List[Any]           =			[]

A_				:      Optional[int]           =			{"type": "section", "text": {"type": "plain_text", "text": "No failed tests! 🤗", "emoji": True}}

A_				:      List[str]           =			[
    {
        "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_				:      List[Any]           =			0
						with open(log, "r") as f:
												for line in f:
																		A_				:      Union[str, Any]           =			json.loads(line)
																		if line.get("nodeid", "") != "":
																								A_				:      Dict           =			line["nodeid"]
																								if line.get("duration", None) is not None:
																														A_				:      List[str]           =			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_				:      Dict           =			[]
						log.unlink()

A_				:      int           =			""
A_				:      Tuple           =			[]
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_				:      List[str]           =			[]
																		A_				:      Dict           =			{}
																		for test in failed_tests:
																								A_				:      List[str]           =			test[0].split("::")
																								A_				:      Optional[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[int]           =			[test[0] for test in failed_table]
																		A_				:      Optional[Any]           =			list(set(files))
																		# Count number of instances in failed_tests
																		A_				:      Tuple           =			[]
																		for file in individual_files:
																								table.append([file, len(filesafailed[file])])

																		A_				:      Dict           =			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) > 3_000:
												A_				:      Any           =			"Too many failed tests, please see the full report in the Action results."
												A_				:      Dict           =			len(err) + 10
												A_				:      Tuple           =			message[: 3_000 - offset] + F'\n...\n```\n{err}'
						print(F'### {message}')
else:
						A_				:      Tuple           =			"No failed tests! 🤗"
						print(F'## {message}')
						payload.append(no_error_payload)

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

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

																		A_				:      Optional[int]           =			{
																		    "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 logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


A_				:      Optional[Any]           =			logging.getLogger(__name__)





@dataclass
class  lowerCamelCase    (A__      ):
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=0.0      ,metadata={'help': 'The label smoothing epsilon to apply (if not zero).'}      )
			lowerCamelCase__ :		bool       		=				field(default=A__      ,metadata={'help': 'Whether to SortishSamler or not.'}      )
			lowerCamelCase__ :		bool       		=				field(
			    default=A__      ,metadata={'help': 'Whether to use generate to calculate generative metrics (ROUGE, BLEU).'}      )
			lowerCamelCase__ :		bool       		=				field(default=A__      ,metadata={'help': 'whether to use adafactor'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Encoder layer dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Decoder layer dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(default=A__      ,metadata={'help': 'Dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[float]       		=				field(
			    default=A__      ,metadata={'help': 'Attention dropout probability. Goes into model.config.'}      )
			lowerCamelCase__ :		Optional[str]       		=				field(
			    default='linear'      ,metadata={'help': f"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()      )}"}      ,)


