






def 				snake_case__							(							UpperCAmelCase							:  list[list]       ):
    lowerCAmelCase__   :Tuple      							=				current_set.copy()
    for row_index, row in enumerate(UpperCAmelCase       ):
        lowerCAmelCase__   :Tuple      							=				row[0]
        for column_index, column in enumerate(UpperCAmelCase       ):
            if magnitude == 0:
                lowerCAmelCase__   :int      							=				column
                continue
            lowerCAmelCase__   :List[str]      							=				column / magnitude
    # Subtract to cancel term
    lowerCAmelCase__   :List[str]      							=				current_set[0]
    lowerCAmelCase__   :Union[str, Any]      							=				[first_row]
    lowerCAmelCase__   :Optional[Any]      							=				current_set[1::]
    for row in current_set:
        lowerCAmelCase__   :Optional[Any]      							=				[]
        # If first term is 0, it is already in form we want, so we preserve it
        if row[0] == 0:
            final_set.append(UpperCAmelCase       )
            continue
        for column_index in range(len(UpperCAmelCase       )       ):
            temp_row.append(first_row[column_index] - row[column_index]       )
        final_set.append(UpperCAmelCase       )
    # Create next recursion iteration set
    if len(final_set[0]       ) != 3:
        lowerCAmelCase__   :List[Any]      							=				final_set[0]
        lowerCAmelCase__   :int      							=				[]
        lowerCAmelCase__   :Optional[Any]      							=				[]
        for row in final_set[1::]:
            current_first_column.append(row[0]       )
            next_iteration.append(row[1::]       )
        lowerCAmelCase__   :Any      							=				simplify(UpperCAmelCase       )
        for i in range(len(UpperCAmelCase       )       ):
            resultant[i].insert(0    ,			current_first_column[i]       )
        resultant.insert(0    ,			UpperCAmelCase       )
        lowerCAmelCase__   :List[Any]      							=				resultant
    return final_set


def 				snake_case__							(							UpperCAmelCase							:  list[list]       ):
    if len(UpperCAmelCase       ) == 0:
        raise IndexError("solve_simultaneous() requires n lists of length n+1"       )
    lowerCAmelCase__   :Tuple      							=				len(UpperCAmelCase       ) + 1
    if any(len(UpperCAmelCase       ) != _length for item in equations       ):
        raise IndexError("solve_simultaneous() requires n lists of length n+1"       )
    for row in equations:
        if any(not isinstance(UpperCAmelCase    ,			(int, float)       ) for column in row       ):
            raise ValueError("solve_simultaneous() requires lists of integers"       )
    if len(UpperCAmelCase       ) == 1:
        return [equations[0][-1] / equations[0][0]]
    lowerCAmelCase__   :Optional[int]      							=				equations.copy()
    if any(0 in row for row in data_set       ):
        lowerCAmelCase__   :Union[str, Any]      							=				data_set.copy()
        lowerCAmelCase__   :Dict      							=				[]
        for row_index, row in enumerate(UpperCAmelCase       ):
            if 0 not in row:
                lowerCAmelCase__   :Optional[int]      							=				data_set.pop(UpperCAmelCase       )
                break
        if not full_row:
            raise ValueError("solve_simultaneous() requires at least 1 full equation"       )
        data_set.insert(0    ,			UpperCAmelCase       )
    lowerCAmelCase__   :int      							=				data_set.copy()
    lowerCAmelCase__   :Any      							=				simplify(UpperCAmelCase       )
    lowerCAmelCase__   :List[str]      							=				simplified[::-1]
    lowerCAmelCase__   :list      							=				[]
    for row in simplified:
        lowerCAmelCase__   :Optional[int]      							=				row[-1]
        if not solutions:
            if row[-2] == 0:
                solutions.append(0       )
                continue
            solutions.append(current_solution / row[-2]       )
            continue
        lowerCAmelCase__   :Optional[int]      							=				row.copy()[: len(UpperCAmelCase       ) - 1 :]
        while temp_row[0] == 0:
            temp_row.pop(0       )
        if len(UpperCAmelCase       ) == 0:
            solutions.append(0       )
            continue
        lowerCAmelCase__   :List[Any]      							=				temp_row[1::]
        lowerCAmelCase__   :int      							=				temp_row[::-1]
        for column_index, column in enumerate(UpperCAmelCase       ):
            current_solution -= column * solutions[column_index]
        solutions.append(UpperCAmelCase       )
    lowerCAmelCase__   :Tuple      							=				[]
    for item in solutions:
        final.append(float(round(UpperCAmelCase    ,			5       )       )       )
    return final[::-1]


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 _a    :   str        =			[
     [2, 1, 1, 1, 1, 4],
     [1, 2, 1, 1, 1, 5],
     [1, 1, 2, 1, 1, 6],
     [1, 1, 1, 2, 1, 7],
     [1, 1, 1, 1, 2, 8],
 ]
 print(solve_simultaneous(eq))
 print(solve_simultaneous([[4, 2]]))











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a    :   str        =			{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _a    :   Optional[Any]        =			[
     """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """WavLMForAudioFrameClassification""",
     """WavLMForCTC""",
     """WavLMForSequenceClassification""",
     """WavLMForXVector""",
     """WavLMModel""",
     """WavLMPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_wavlm import (
      WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      WavLMForAudioFrameClassification,
      WavLMForCTC,
      WavLMForSequenceClassification,
      WavLMForXVector,
      WavLMModel,
      WavLMPreTrainedModel,
  )

else:
 import sys

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



