
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase		:    List[str]			=       logging.get_logger(__name__)

lowercase		:    List[str]			=       {
    'uw-madison/yoso-4096': 'https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}




class  _snake_case	(    a_							):
							SCREAMING_SNAKE_CASE		  =    '''yoso'''






							def __init__(       self    :      List[str]    ,			snake_case__    :      List[str]=5_0_2_6_5    ,			snake_case__    :      Any=7_6_8    ,			snake_case__    :      Union[str, Any]=1_2    ,			snake_case__    :      Optional[int]=1_2    ,			snake_case__    :      Tuple=3_0_7_2    ,			snake_case__    :      Dict="gelu"    ,			snake_case__    :      int=0.1    ,			snake_case__    :      Optional[Any]=0.1    ,			snake_case__    :      Tuple=4_0_9_6    ,			snake_case__    :      int=1    ,			snake_case__    :      List[str]=0.02    ,			snake_case__    :      Dict=1e-12    ,			snake_case__    :      int="absolute"    ,			snake_case__    :      List[str]=True    ,			snake_case__    :      List[str]=9    ,			snake_case__    :      str=6_4    ,			snake_case__    :      Optional[int]=None    ,			snake_case__    :      List[Any]=True    ,			snake_case__    :      Any=True    ,			snake_case__    :      Dict=1    ,			snake_case__    :      Union[str, Any]=0    ,			snake_case__    :      Optional[int]=2    ,			**snake_case__    :      int    ,			):






												"""simple docstring"""



												super().__init__(pad_token_id=_a    ,			bos_token_id=_a    ,			eos_token_id=_a    ,			**_a     )

												__a:    List[Any]		     =       vocab_size
												__a:    Optional[int]		     =       max_position_embeddings
												__a:    List[Any]		     =       hidden_size
												__a:    str		     =       num_hidden_layers
												__a:    Any		     =       num_attention_heads
												__a:    Union[str, Any]		     =       intermediate_size
												__a:    Tuple		     =       hidden_act
												__a:    str		     =       hidden_dropout_prob
												__a:    Optional[Any]		     =       attention_probs_dropout_prob
												__a:    Optional[Any]		     =       initializer_range
												__a:    Optional[Any]		     =       type_vocab_size
												__a:    Any		     =       layer_norm_eps
												__a:    Optional[int]		     =       position_embedding_type
												__a:    Union[str, Any]		     =       use_expectation
												__a:    str		     =       hash_code_len
												__a:    List[Any]		     =       num_hash
												__a:    Optional[int]		     =       conv_window
												__a:    Optional[int]		     =       use_fast_hash
												__a:    List[Any]		     =       lsh_backward




import logging

# standard libraries
import sys

import numpy as np
import pytest  # type: ignore

# Custom/local libraries
from matrix import matrix_operation as matop

_snake_case				=			[[1_2, 1_0], [3, 9]]
_snake_case				=			[[3, 4], [7, 4]]
_snake_case				=			[[3, 0, 2], [2, 0, -2], [0, 1, 1]]
_snake_case				=			[[3, 0, -2], [2, 0, 2], [0, 1, 1]]
_snake_case				=			[[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
_snake_case				=			[1]
_snake_case				=			[2]

_snake_case				=			logging.getLogger()
_snake_case				=			logging.DEBUG
_snake_case				=			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_addition.__name__} returned integer'			)
               matop.add(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_addition.__name__} with same matrix dims'			)
          UpperCAmelCase    :					Tuple			=      (np.array(A__			) + np.array(A__			)).tolist()
          UpperCAmelCase    :					Optional[Any]			=      matop.add(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_addition.__name__} with different matrix dims'			)
               matop.add(A__		,		A__			)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_subtraction.__name__} returned integer'			)
               matop.subtract(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_subtraction.__name__} with same matrix dims'			)
          UpperCAmelCase    :					Tuple			=      (np.array(A__			) - np.array(A__			)).tolist()
          UpperCAmelCase    :					Optional[int]			=      matop.subtract(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_subtraction.__name__} with different matrix dims'			)
               assert matop.subtract(A__		,		A__			)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          logger.info(f'\n\t{test_multiplication.__name__} returned integer'			)
          with pytest.raises(A__			):
               matop.add(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_multiplication.__name__} meets dim requirements'			)
          UpperCAmelCase    :					List[str]			=      (np.matmul(A__		,		A__			)).tolist()
          UpperCAmelCase    :					int			=      matop.multiply(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(
                   f'\n\t{test_multiplication.__name__} does not meet dim requirements'			)
               assert matop.subtract(A__		,		A__			)







@pytest.mark.mat_ops
def 	A (		):
     UpperCAmelCase    :					int			=      (3.5 * np.array(A__			)).tolist()
     UpperCAmelCase    :					Optional[int]			=      matop.scalar_multiply(A__		,		3.5			)
     assert theo == act







@pytest.mark.mat_ops
def 	A (		):
     UpperCAmelCase    :					List[Any]			=      (np.identity(5			)).tolist()
     UpperCAmelCase    :					Optional[int]			=      matop.identity(5			)
     assert theo == act







@pytest.mark.mat_ops
@pytest.mark.parametrize("mat"		,		[mat_a, mat_b, mat_c, mat_d, mat_e, mat_f]			)
def 	A (		A__			):
     if (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_transpose.__name__} returned integer'			)
               matop.transpose(A__			)
     else:
          UpperCAmelCase    :					Dict			=      (np.transpose(A__			)).tolist()
          UpperCAmelCase    :					List[str]			=      matop.transpose(A__		,		return_map=A__			)
          assert theo == act



