


'''simple docstring'''





import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__  ):
					lowercase_  							=			F'''{sampling_rate}'''
					lowercase_  							=			"""1"""
					lowercase_  							=			"""f32le"""
					lowercase_  							=			[
					    """ffmpeg""",
					    """-i""",
					    """pipe:0""",
					    """-ac""",
					    ac,
					    """-ar""",
					    ar,
					    """-f""",
					    format_for_conversion,
					    """-hide_banner""",
					    """-loglevel""",
					    """quiet""",
					    """pipe:1""",
					]

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


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__ = "f32le"						,							):
					lowercase_  							=			F'''{sampling_rate}'''
					lowercase_  							=			"""1"""
					if format_for_conversion == "s16le":
										lowercase_  							=			2
					elif format_for_conversion == "f32le":
										lowercase_  							=			4
					else:
										raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''  )

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

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


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__ = None						,							UpperCAmelCase__ = None						,							UpperCAmelCase__ = "f32le"						,							):






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

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

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

					lowercase_  							=			int(round(sampling_rate * stride_length_s[0]  )  ) * size_of_sample
					lowercase_  							=			int(round(sampling_rate * stride_length_s[1]  )  ) * size_of_sample
					lowercase_  							=			datetime.datetime.now()
					lowercase_  							=			datetime.timedelta(seconds=a__  )
					for item in chunk_bytes_iter(a__						,							a__						,							stride=(stride_left, stride_right)						,							stream=a__  ):
										# Put everything back in numpy scale
										lowercase_  							=			np.frombuffer(item["""raw"""]						,							dtype=a__  )
										lowercase_  							=			(
										    item["""stride"""][0] // size_of_sample,
										    item["""stride"""][1] // size_of_sample,
										)
										lowercase_  							=			sampling_rate
										audio_time += delta
										if datetime.datetime.now() > audio_time + 1_0 * delta:
															# We're late !! SKIP
															continue
										yield item


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__ = False  ):
					lowercase_  							=			B""""""
					lowercase_							,					lowercase_  							=			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}'''  )
					lowercase_  							=			0
					for raw in iterator:
										acc += raw
										if stream and len(a__  ) < chunk_len:
															lowercase_  							=			(_stride_left, 0)
															yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
										else:
															while len(a__  ) >= chunk_len:
																				# We are flushing the accumulator
																				lowercase_  							=			(_stride_left, stride_right)
																				lowercase_  							=			{"""raw""": acc[:chunk_len], """stride""": stride}
																				if stream:
																									lowercase_  							=			False
																				yield item
																				lowercase_  							=			stride_left
																				lowercase_  							=			acc[chunk_len - stride_left - stride_right :]
    # Last chunk
					if len(a__  ) > stride_left:
										lowercase_  							=			{"""raw""": acc, """stride""": (_stride_left, 0)}
										if stream:
															lowercase_  							=			False
										yield item



def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__  ):
					lowercase_  							=			2**2_4  # 16Mo
					try:
										with subprocess.Popen(a__						,							stdout=subprocess.PIPE						,							bufsize=a__  ) as ffmpeg_process:
															while True:
																				lowercase_  							=			ffmpeg_process.stdout.read(a__  )
																				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






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


a					  =     {
    'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'],
    'processing_trocr': ['TrOCRProcessor'],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a					  =     [
							    'TROCR_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'TrOCRForCausalLM',
							    'TrOCRPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
							from .processing_trocr import TrOCRProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
							import sys

							a					  =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


