



'''simple docstring'''



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

from tabulate import DataRow, TableFormat, tabulate


lowerCAmelCase	:		str				=   TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow('''''', '''|''', '''|'''),
    datarow=DataRow('''''', '''|''', '''|'''),
    padding=1,
    with_header_hide=None,
)


lowerCAmelCase	:		Optional[int]				=   []
lowerCAmelCase	:		str				=   []

lowerCAmelCase	:		str				=   {'''type''': '''section''', '''text''': {'''type''': '''plain_text''', '''text''': '''No failed tests! 🤗''', '''emoji''': True}}

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

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

lowerCAmelCase	:		Optional[int]				=   ''''''
lowerCAmelCase	:		Optional[Any]				=   []
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"
			lowerCAmelCase	:		Any				=   []
			lowerCAmelCase	:		str				=   {}
			for test in failed_tests:
				lowerCAmelCase	:		Optional[int]				=   test[0].split('''::''')
				lowerCAmelCase	:		Optional[Any]				=   data[0].split('''/''')[-1]
				if data[0] not in filesafailed:
					lowerCAmelCase	:		List[str]				=   [data[1:]]
				else:
					filesafailed[data[0]] += [data[1:]]
				failed_table.append(data)

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

			lowerCAmelCase	:		List[str]				=   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_0_0_0:
		lowerCAmelCase	:		List[Any]				=   '''Too many failed tests, please see the full report in the Action results.'''
		lowerCAmelCase	:		Tuple				=   len(err) + 1_0
		lowerCAmelCase	:		List[Any]				=   message[: 3_0_0_0 - offset] + f'\n...\n```\n{err}'
	print(f'### {message}')
else:
	lowerCAmelCase	:		List[Any]				=   '''No failed tests! 🤗'''
	print(f'## {message}')
	payload.append(no_error_payload)

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

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

			lowerCAmelCase	:		Tuple				=   {
			    '''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 datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np



def   __lowerCAmelCase					(							lowerCamelCase   :						bytes				,		lowerCamelCase   :						int					):






	'''simple docstring'''




	__lowerCAmelCase												=  f'''{sampling_rate}'''
	__lowerCAmelCase												=  "1"
	__lowerCAmelCase												=  "f32le"
	__lowerCAmelCase												=  [
	    "ffmpeg",
	    "-i",
	    "pipe:0",
	    "-ac",
	    ac,
	    "-ar",
	    ar,
	    "-f",
	    format_for_conversion,
	    "-hide_banner",
	    "-loglevel",
	    "quiet",
	    "pipe:1",
	]

	try:
		with subprocess.Popen(lowerCamelCase				,		stdin=subprocess.PIPE				,		stdout=subprocess.PIPE					) as ffmpeg_process:
			__lowerCAmelCase												=  ffmpeg_process.communicate(lowerCamelCase					)
	except FileNotFoundError as error:
		raise ValueError("ffmpeg was not found but is required to load audio files from filename"					) from error
	__lowerCAmelCase												=  output_stream[0]
	__lowerCAmelCase												=  np.frombuffer(lowerCamelCase				,		np.floataa					)
	if audio.shape[0] == 0:
		raise ValueError("Malformed soundfile"					)
	return audio



def   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						float				,		lowerCamelCase   :						str = "f32le"				,		):






	'''simple docstring'''




	__lowerCAmelCase												=  f'''{sampling_rate}'''
	__lowerCAmelCase												=  "1"
	if format_for_conversion == "s16le":
		__lowerCAmelCase												=  2
	elif format_for_conversion == "f32le":
		__lowerCAmelCase												=  4
	else:
		raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''					)

	__lowerCAmelCase												=  platform.system()
	if system == "Linux":
		__lowerCAmelCase												=  "alsa"
		__lowerCAmelCase												=  "default"
	elif system == "Darwin":
		__lowerCAmelCase												=  "avfoundation"
		__lowerCAmelCase												=  ":0"
	elif system == "Windows":
		__lowerCAmelCase												=  "dshow"
		__lowerCAmelCase												=  "default"

	__lowerCAmelCase												=  [
	    "ffmpeg",
	    "-f",
	    format_,
	    "-i",
	    input_,
	    "-ac",
	    ac,
	    "-ar",
	    ar,
	    "-f",
	    format_for_conversion,
	    "-fflags",
	    "nobuffer",
	    "-hide_banner",
	    "-loglevel",
	    "quiet",
	    "pipe:1",
	]
	__lowerCAmelCase												=  int(round(sampling_rate * chunk_length_s					)					) * size_of_sample
	__lowerCAmelCase												=  _ffmpeg_stream(lowerCamelCase				,		lowerCamelCase					)
	for item in iterator:
		yield item



def   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						float				,		lowerCamelCase   :						Optional[int] = None				,		lowerCamelCase   :						Optional[Union[Tuple[float, float], float]] = None				,		lowerCamelCase   :						str = "f32le"				,		):






	'''simple docstring'''




	if stream_chunk_s is not None:
		__lowerCAmelCase												=  stream_chunk_s
	else:
		__lowerCAmelCase												=  chunk_length_s

	__lowerCAmelCase												=  ffmpeg_microphone(lowerCamelCase				,		lowerCamelCase				,		format_for_conversion=lowerCamelCase					)
	if format_for_conversion == "s16le":
		__lowerCAmelCase												=  np.intaa
		__lowerCAmelCase												=  2
	elif format_for_conversion == "f32le":
		__lowerCAmelCase												=  np.floataa
		__lowerCAmelCase												=  4
	else:
		raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''					)

	if stride_length_s is None:
		__lowerCAmelCase												=  chunk_length_s / 6
	__lowerCAmelCase												=  int(round(sampling_rate * chunk_length_s					)					) * size_of_sample
	if isinstance(lowerCamelCase				,		(int, float)					):
		__lowerCAmelCase												=  [stride_length_s, stride_length_s]

	__lowerCAmelCase												=  int(round(sampling_rate * stride_length_s[0]					)					) * size_of_sample
	__lowerCAmelCase												=  int(round(sampling_rate * stride_length_s[1]					)					) * size_of_sample
	__lowerCAmelCase												=  datetime.datetime.now()
	__lowerCAmelCase												=  datetime.timedelta(seconds=lowerCamelCase					)
	for item in chunk_bytes_iter(lowerCamelCase				,		lowerCamelCase				,		stride=(stride_left, stride_right)				,		stream=lowerCamelCase					):
		# Put everything back in numpy scale
		__lowerCAmelCase												=  np.frombuffer(item["raw"]				,		dtype=lowerCamelCase					)
		__lowerCAmelCase												=  (
		    item["stride"][0] // size_of_sample,
		    item["stride"][1] // size_of_sample,
		)
		__lowerCAmelCase												=  sampling_rate
		audio_time += delta
		if datetime.datetime.now() > audio_time + 10 * delta:
			# We're late !! SKIP
			continue
		yield item



def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[Any]				,		lowerCamelCase   :						int				,		lowerCamelCase   :						Tuple[int, int]				,		lowerCamelCase   :						bool = False					):






	'''simple docstring'''




	__lowerCAmelCase												=  B""
	__lowerCAmelCase							,       __lowerCAmelCase												=  stride
	if stride_left + stride_right >= chunk_len:
		raise ValueError(
		    f'''Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}'''					)
	__lowerCAmelCase												=  0
	for raw in iterator:
		acc += raw
		if stream and len(lowerCamelCase					) < chunk_len:
			__lowerCAmelCase												=  (_stride_left, 0)
			yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
		else:
			while len(lowerCamelCase					) >= chunk_len:
				# We are flushing the accumulator
				__lowerCAmelCase												=  (_stride_left, stride_right)
				__lowerCAmelCase												=  {"raw": acc[:chunk_len], "stride": stride}
				if stream:
					__lowerCAmelCase												=  False
				yield item
				__lowerCAmelCase												=  stride_left
				__lowerCAmelCase												=  acc[chunk_len - stride_left - stride_right :]
    # Last chunk
	if len(lowerCamelCase					) > stride_left:
		__lowerCAmelCase												=  {"raw": acc, "stride": (_stride_left, 0)}
		if stream:
			__lowerCAmelCase												=  False
		yield item




def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						int					):






	'''simple docstring'''




	__lowerCAmelCase												=  2**24  # 16Mo
	try:
		with subprocess.Popen(lowerCamelCase				,		stdout=subprocess.PIPE				,		bufsize=lowerCamelCase					) as ffmpeg_process:
			while True:
				__lowerCAmelCase												=  ffmpeg_process.stdout.read(lowerCamelCase					)
				if raw == b"":
					break
				yield raw
	except FileNotFoundError as error:
		raise ValueError("ffmpeg was not found but is required to stream audio files from filename"					) from error