





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


__A       :					List[str]     					=     {
    "configuration_tvlt": ["TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP", "TvltConfig"],
    "feature_extraction_tvlt": ["TvltFeatureExtractor"],
    "processing_tvlt": ["TvltProcessor"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A       :					Union[str, Any]     					=     [
				    "TVLT_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "TvltModel",
				    "TvltForPreTraining",
				    "TvltForAudioVisualClassification",
				    "TvltPreTrainedModel",
				]

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A       :					Dict     					=     ["TvltImageProcessor"]


if TYPE_CHECKING:
				from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
				from .processing_tvlt import TvltProcessor
				from .feature_extraction_tvlt import TvltFeatureExtractor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tvlt import (
								    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TvltForAudioVisualClassification,
								    TvltForPreTraining,
								    TvltModel,
								    TvltPreTrainedModel,
								)

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_tvlt import TvltImageProcessor


else:
				import sys

				__A       :					List[str]     					=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










import numpy as np





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__    ,    UpperCamelCase__="utf-8"    ,    UpperCamelCase__="surrogatepass"				)						->       Optional[Any]:







			'''simple docstring'''

			UpperCAmelCase     	=       bin(int.from_bytes(text.encode(UpperCamelCase__    ,    UpperCamelCase__				)    ,    '''big'''				)				)[2:]
			return bits.zfill(8 * ((len(UpperCamelCase__				) + 7) // 8)				)





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__    ,    UpperCamelCase__="utf-8"    ,    UpperCamelCase__="surrogatepass"				)						->       str:







			'''simple docstring'''

			UpperCAmelCase     	=       int(UpperCamelCase__    ,    2				)
			return n.to_bytes((n.bit_length() + 7) // 8    ,    '''big'''				).decode(UpperCamelCase__    ,    UpperCamelCase__				) or "\0"





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__    ,    UpperCamelCase__				)						->       Tuple:







			'''simple docstring'''

			if size_par + len(UpperCamelCase__				) <= 2**size_par - (len(UpperCamelCase__				) - 1):
						raise ValueError('''size of parity don\'t match with size of data'''				)

			UpperCAmelCase     	=       []
			UpperCAmelCase     	=       []
			UpperCAmelCase     	=       [bin(UpperCamelCase__				)[2:] for x in range(1    ,    size_par + len(UpperCamelCase__				) + 1				)]

			# sorted information data for the size of the output data
			UpperCAmelCase     	=       []
			# data position template + parity
			UpperCAmelCase     	=       []
			# parity bit counter
			UpperCAmelCase     	=       0
			# counter position of data bits
			UpperCAmelCase     	=       0

			for x in range(1    ,    size_par + len(UpperCamelCase__				) + 1				):
						# Performs a template of bit positions - who should be given,
						# and who should be parity
						if qtd_bp < size_par:
									if (np.log(UpperCamelCase__				) / np.log(2				)).is_integer():
												data_out_gab.append('''P'''				)
												UpperCAmelCase     	=       qtd_bp + 1
									else:
												data_out_gab.append('''D'''				)
						else:
									data_out_gab.append('''D'''				)

						# Sorts the data to the new output size
						if data_out_gab[-1] == "D":
									data_ord.append(data[cont_data]				)
									cont_data += 1
						else:
									data_ord.append(UpperCamelCase__				)

    # Calculates parity
			UpperCAmelCase     	=       0  # parity bit counter
			for bp in range(1    ,    size_par + 1				):
						# Bit counter one for a given parity
						UpperCAmelCase     	=       0
						# counter to control the loop reading
						UpperCAmelCase     	=       0
						for x in data_ord:
									if x is not None:
												try:
															UpperCAmelCase     	=       (bin_pos[cont_loop])[-1 * (bp)]
												except IndexError:
															UpperCAmelCase     	=       '''0'''
												if aux == "1" and x == "1":
															cont_bo += 1
									cont_loop += 1
						parity.append(cont_bo % 2				)

						qtd_bp += 1

			# Mount the message
			UpperCAmelCase     	=       0  # parity bit counter
			for x in range(0    ,    size_par + len(UpperCamelCase__				)				):
						if data_ord[x] is None:
									data_out.append(str(parity[cont_bp]				)				)
									cont_bp += 1
						else:
									data_out.append(data_ord[x]				)

			return data_out





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__    ,    UpperCamelCase__				)						->       Optional[int]:







			'''simple docstring'''

			UpperCAmelCase     	=       []
			# Parity bit counter
			UpperCAmelCase     	=       0
			# Counter p data bit reading
			UpperCAmelCase     	=       0
			# list of parity received
			UpperCAmelCase     	=       []
			UpperCAmelCase     	=       []

			for x in range(1    ,    len(UpperCamelCase__				) + 1				):
						# Performs a template of bit positions - who should be given,
						#  and who should be parity
						if qtd_bp < size_par and (np.log(UpperCamelCase__				) / np.log(2				)).is_integer():
									data_out_gab.append('''P'''				)
									UpperCAmelCase     	=       qtd_bp + 1
						else:
									data_out_gab.append('''D'''				)

						# Sorts the data to the new output size
						if data_out_gab[-1] == "D":
									data_output.append(data[cont_data]				)
						else:
									parity_received.append(data[cont_data]				)
						cont_data += 1

			# -----------calculates the parity with the data
			UpperCAmelCase     	=       []
			UpperCAmelCase     	=       []
			UpperCAmelCase     	=       [bin(UpperCamelCase__				)[2:] for x in range(1    ,    size_par + len(UpperCamelCase__				) + 1				)]

			#  sorted information data for the size of the output data
			UpperCAmelCase     	=       []
			# Data position feedback + parity
			UpperCAmelCase     	=       []
			# Parity bit counter
			UpperCAmelCase     	=       0
			# Counter p data bit reading
			UpperCAmelCase     	=       0

			for x in range(1    ,    size_par + len(UpperCamelCase__				) + 1				):
						# Performs a template position of bits - who should be given,
						# and who should be parity
						if qtd_bp < size_par and (np.log(UpperCamelCase__				) / np.log(2				)).is_integer():
									data_out_gab.append('''P'''				)
									UpperCAmelCase     	=       qtd_bp + 1
						else:
									data_out_gab.append('''D'''				)

						# Sorts the data to the new output size
						if data_out_gab[-1] == "D":
									data_ord.append(data_output[cont_data]				)
									cont_data += 1
						else:
									data_ord.append(UpperCamelCase__				)

    # Calculates parity
			UpperCAmelCase     	=       0  # parity bit counter
			for bp in range(1    ,    size_par + 1				):
						# Bit counter one for a certain parity
						UpperCAmelCase     	=       0
						# Counter to control loop reading
						UpperCAmelCase     	=       0
						for x in data_ord:
									if x is not None:
												try:
															UpperCAmelCase     	=       (bin_pos[cont_loop])[-1 * (bp)]
												except IndexError:
															UpperCAmelCase     	=       '''0'''
												if aux == "1" and x == "1":
															cont_bo += 1
									cont_loop += 1
						parity.append(str(cont_bo % 2				)				)

						qtd_bp += 1

			# Mount the message
			UpperCAmelCase     	=       0  # Parity bit counter
			for x in range(0    ,    size_par + len(UpperCamelCase__				)				):
						if data_ord[x] is None:
									data_out.append(str(parity[cont_bp]				)				)
									cont_bp += 1
						else:
									data_out.append(data_ord[x]				)

			UpperCAmelCase     	=       parity_received == parity
			return data_output, ack



