
import functools
import operator

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


lowercase__	:Dict										=					logging.get_logger(__name__)

lowercase__	:Optional[int]										=					{
    "microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
    # See all WavLM models at https://huggingface.co/models?filter=wavlm
}







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							lowercase_ : Optional[int]       ='''wavlm'''




							def __init__(       self     ,A__=3_2     ,A__=7_6_8     ,A__=1_2     ,A__=1_2     ,A__=3_0_7_2     ,A__="gelu"     ,A__=0.1     ,A__=0.1     ,A__=0.1     ,A__=0.0     ,A__=0.1     ,A__=0.1     ,A__=0.02     ,A__=1E-5     ,A__="group"     ,A__="gelu"     ,A__=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)     ,A__=(5, 2, 2, 2, 2, 2, 2)     ,A__=(1_0, 3, 3, 3, 3, 2, 2)     ,A__=False     ,A__=1_2_8     ,A__=1_6     ,A__=3_2_0     ,A__=8_0_0     ,A__=False     ,A__=True     ,A__=0.05     ,A__=1_0     ,A__=2     ,A__=0.0     ,A__=1_0     ,A__=3_2_0     ,A__=2     ,A__=0.1     ,A__=1_0_0     ,A__=2_5_6     ,A__=2_5_6     ,A__=0.1     ,A__="mean"     ,A__=False     ,A__=False     ,A__=2_5_6     ,A__=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0)     ,A__=(5, 3, 3, 1, 1)     ,A__=(1, 2, 3, 1, 1)     ,A__=5_1_2     ,A__=8_0     ,A__=0     ,A__=1     ,A__=2     ,A__=False     ,A__=3     ,A__=2     ,A__=3     ,A__=None     ,**A__     ,):
												super().__init__(**A__     ,pad_token_id=A__     ,bos_token_id=A__     ,eos_token_id=A__)
												lowercase					=		hidden_size
												lowercase					=		feat_extract_norm
												lowercase					=		feat_extract_activation
												lowercase					=		list(A__)
												lowercase					=		list(A__)
												lowercase					=		list(A__)
												lowercase					=		conv_bias
												lowercase					=		num_buckets
												lowercase					=		max_bucket_distance
												lowercase					=		num_conv_pos_embeddings
												lowercase					=		num_conv_pos_embedding_groups
												lowercase					=		len(self.conv_dim)
												lowercase					=		num_hidden_layers
												lowercase					=		intermediate_size
												lowercase					=		hidden_act
												lowercase					=		num_attention_heads
												lowercase					=		hidden_dropout
												lowercase					=		attention_dropout
												lowercase					=		activation_dropout
												lowercase					=		feat_proj_dropout
												lowercase					=		final_dropout
												lowercase					=		layerdrop
												lowercase					=		layer_norm_eps
												lowercase					=		initializer_range
												lowercase					=		num_ctc_classes
												lowercase					=		vocab_size
												lowercase					=		do_stable_layer_norm
												lowercase					=		use_weighted_layer_sum
												lowercase					=		classifier_proj_size

												if (
												    (len(self.conv_stride) != self.num_feat_extract_layers)
												    or (len(self.conv_kernel) != self.num_feat_extract_layers)
												    or (len(self.conv_dim) != self.num_feat_extract_layers)
												):
																	raise ValueError(
																	    '''Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='''
																	    ''' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='''
																	    f' {len(self.conv_dim)}`, `len(config.conv_stride) = {len(self.conv_stride)}`,'
																	    f' `len(config.conv_kernel) = {len(self.conv_kernel)}`.')

												# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
												lowercase					=		apply_spec_augment
												lowercase					=		mask_time_prob
												lowercase					=		mask_time_length
												lowercase					=		mask_time_min_masks
												lowercase					=		mask_feature_prob
												lowercase					=		mask_feature_length

												# parameters for pretraining with codevector quantized representations
												lowercase					=		num_codevectors_per_group
												lowercase					=		num_codevector_groups
												lowercase					=		contrastive_logits_temperature
												lowercase					=		num_negatives
												lowercase					=		codevector_dim
												lowercase					=		proj_codevector_dim
												lowercase					=		diversity_loss_weight

												# ctc loss
												lowercase					=		ctc_loss_reduction
												lowercase					=		ctc_zero_infinity

												# adapter
												lowercase					=		add_adapter
												lowercase					=		adapter_kernel_size
												lowercase					=		adapter_stride
												lowercase					=		num_adapter_layers
												lowercase					=		output_hidden_size or hidden_size

												# SequenceClassification-specific parameter. Feel free to ignore for other classes.
												lowercase					=		classifier_proj_size

												# XVector-specific parameters. Feel free to ignore for other classes.
												lowercase					=		list(A__)
												lowercase					=		list(A__)
												lowercase					=		list(A__)
												lowercase					=		xvector_output_dim





							@property
							def 				A__   (       self):
												return functools.reduce(operator.mul     ,self.conv_stride     ,1)






import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		os.environ[key]
					except KeyError:
										# KEY isn't set, default to `default`.
										lowercase					=		default
					else:
										# KEY is set, convert it to True or False.
										try:
															lowercase					=		strtobool(lowerCAmelCase__	)
										except ValueError:
															# More values are supported, but let's keep the message simple.
															raise ValueError(f'If set, {key} must be yes or no.'	)
					return _value


lowercase__	:Dict										=					parse_flag_from_env("RUN_SLOW", default=False)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skip('''Test was skipped'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(_run_slow_tests				,    '''test is slow'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(not torch.cuda.is_available()				,    '''test requires only a CPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.is_available()				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_xpu_available()				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_mps_available()				,    '''test requires a `mps` backend support in `torch`'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(
					    is_transformers_available() and is_datasets_available()				,    '''test requires the Hugging Face suite'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_bnb_available()				,    '''test requires the bitsandbytes library'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tpu_available()				,    '''test requires TPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() == 1				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() == 1				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() > 1				,    '''test requires multiple GPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() > 1				,    '''test requires multiple XPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_safetensors_available()				,    '''test requires safetensors'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_deepspeed_available()				,    '''test requires DeepSpeed'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_torch_version('''>='''				,    '''1.12.0'''	)				,    '''test requires torch version >= 1.12.0'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__=None				,    lowerCAmelCase__=None	):
					'''simple docstring'''
					if test_case is None:
										return partial(lowerCAmelCase__				,    version=lowerCAmelCase__	)
					return unittest.skipUnless(is_torch_version('''>='''				,    lowerCAmelCase__	)				,    f'test requires torch version >= {version}'	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tensorboard_available()				,    '''test requires Tensorboard'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_wandb_available()				,    '''test requires wandb'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_comet_ml_available()				,    '''test requires comet_ml'''	)(lowerCAmelCase__	)


lowercase__	:Dict										=					(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(
					    _atleast_one_tracker_available				,    '''test requires at least one tracker to be available and for `comet_ml` to not be installed'''				,    )(lowerCAmelCase__	)







class        lowercase	(      unittest.TestCase	):
							lowercase_ : int       =True




							@classmethod
							def 				A__   (       cls):
												lowercase					=		tempfile.mkdtemp()




							@classmethod
							def 				A__   (       cls):
												if os.path.exists(cls.tmpdir):
																	shutil.rmtree(cls.tmpdir)





							def 				A__   (       self):
												if self.clear_on_setup:
																	for path in Path(self.tmpdir).glob('''**/*'''):
																						if path.is_file():
																											path.unlink()
																						elif path.is_dir():
																											shutil.rmtree(A__)







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self):
												super().tearDown()
												# Reset the state of the AcceleratorState singleton.
												AcceleratorState._reset_state()
												PartialState._reset_state()







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self     ,A__):
												lowercase					=		mocks if isinstance(A__     ,(tuple, list)) else [mocks]
												for m in self.mocks:
																	m.start()
																	self.addCleanup(m.stop)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		AcceleratorState()
					lowercase					=		tensor[None].clone().to(state.device	)
					lowercase					=		gather(lowerCAmelCase__	).cpu()
					lowercase					=		tensor[0].cpu()
					for i in range(tensors.shape[0]	):
										if not torch.equal(tensors[i]				,    lowerCAmelCase__	):
															return False
					return True







class        lowercase	:




							def __init__(       self     ,A__     ,A__     ,A__):
												lowercase					=		returncode
												lowercase					=		stdout
												lowercase					=		stderr



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					while True:
										lowercase					=		await stream.readline()
										if line:
															callback(lowerCAmelCase__	)
										else:
															break



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=False				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					if echo:
										print('''\nRunning: '''				,    ''' '''.join(lowerCAmelCase__	)	)

					lowercase					=		await asyncio.create_subprocess_exec(
					    cmd[0]				,    *cmd[1:]				,    stdin=lowerCAmelCase__				,    stdout=asyncio.subprocess.PIPE				,    stderr=asyncio.subprocess.PIPE				,    env=lowerCAmelCase__				,    )

					# note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
					# https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
					#
					# If it starts hanging, will need to switch to the following code. The problem is that no data
					# will be seen until it's done and if it hangs for example there will be no debug info.
					# out, err = await p.communicate()
					# return _RunOutput(p.returncode, out, err)

					lowercase					=		[]
					lowercase					=		[]

					def tee(lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__=""	):
										lowercase					=		line.decode('''utf-8'''	).rstrip()
										sink.append(lowerCAmelCase__	)
										if not quiet:
															print(lowerCAmelCase__				,    lowerCAmelCase__				,    file=lowerCAmelCase__	)

    # XXX: the timeout doesn't seem to make any difference here
					await asyncio.wait(
					    [
					        asyncio.create_task(_read_stream(p.stdout				,    lambda lowerCAmelCase__	: tee(lowerCAmelCase__				,    lowerCAmelCase__				,    sys.stdout				,    label='''stdout:'''	)	)	),
					        asyncio.create_task(_read_stream(p.stderr				,    lambda lowerCAmelCase__	: tee(lowerCAmelCase__				,    lowerCAmelCase__				,    sys.stderr				,    label='''stderr:'''	)	)	),
					    ]				,    timeout=lowerCAmelCase__				,    )
					return _RunOutput(await p.wait()				,    lowerCAmelCase__				,    lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=180				,    lowerCAmelCase__=False				,    lowerCAmelCase__=True	):
					'''simple docstring'''
					lowercase					=		asyncio.get_event_loop()
					lowercase					=		loop.run_until_complete(
					    _stream_subprocess(lowerCAmelCase__				,    env=lowerCAmelCase__				,    stdin=lowerCAmelCase__				,    timeout=lowerCAmelCase__				,    quiet=lowerCAmelCase__				,    echo=lowerCAmelCase__	)	)

					lowercase					=		''' '''.join(lowerCAmelCase__	)
					if result.returncode > 0:
										lowercase					=		'''\n'''.join(result.stderr	)
										raise RuntimeError(
										    f'\'{cmd_str}\' failed with returncode {result.returncode}\n\n'
										    f'The combined stderr from workers follows:\n{stderr}'	)

					return result







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							pass



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		subprocess.check_output(lowerCAmelCase__				,    stderr=subprocess.STDOUT	)
										if return_stdout:
															if hasattr(lowerCAmelCase__				,    '''decode'''	):
																				lowercase					=		output.decode('''utf-8'''	)
															return output
					except subprocess.CalledProcessError as e:
										raise SubprocessCallException(
										    f'Command `{" ".join(lowerCAmelCase__	)}` failed with the following error:\n\n{e.output.decode()}'	) from e




