"""simple docstring"""



import logging

# standard libraries
import sys

import numpy as np
import pytest  # type: ignore

# Custom/local libraries
from matrix import matrix_operation as matop

_UpperCamelCase         =		[[12, 10], [3, 9]]
_UpperCamelCase         =		[[3, 4], [7, 4]]
_UpperCamelCase         =		[[3, 0, 2], [2, 0, -2], [0, 1, 1]]
_UpperCamelCase         =		[[3, 0, -2], [2, 0, 2], [0, 1, 1]]
_UpperCamelCase         =		[[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
_UpperCamelCase         =		[1]
_UpperCamelCase         =		[2]

_UpperCamelCase         =		logging.getLogger()
_UpperCamelCase         =		logging.DEBUG
_UpperCamelCase         =		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(		lowerCAmelCase ,     lowerCAmelCase       ):
							if (np.array(lowercase__       )).shape < (2, 2) or (np.array(lowercase__       )).shape < (2, 2):
														with pytest.raises(lowercase__       ):
																					logger.info(F'''\n\t{test_addition.__name__} returned integer'''       )
																					matop.add(lowercase__ ,     lowercase__       )
							elif (np.array(lowercase__       )).shape == (np.array(lowercase__       )).shape:
														logger.info(F'''\n\t{test_addition.__name__} with same matrix dims'''       )
														A__					:    Dict														= (np.array(lowercase__       ) + np.array(lowercase__       )).tolist()
														A__					:    List[str]														= matop.add(lowercase__ ,     lowercase__       )
														assert theo == act
							else:
														with pytest.raises(lowercase__       ):
																					logger.info(F'''\n\t{test_addition.__name__} with different matrix dims'''       )
																					matop.add(lowercase__ ,     lowercase__       )

@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(		lowerCAmelCase ,     lowerCAmelCase       ):
							if (np.array(lowercase__       )).shape < (2, 2) or (np.array(lowercase__       )).shape < (2, 2):
														with pytest.raises(lowercase__       ):
																					logger.info(F'''\n\t{test_subtraction.__name__} returned integer'''       )
																					matop.subtract(lowercase__ ,     lowercase__       )
							elif (np.array(lowercase__       )).shape == (np.array(lowercase__       )).shape:
														logger.info(F'''\n\t{test_subtraction.__name__} with same matrix dims'''       )
														A__					:    List[Any]														= (np.array(lowercase__       ) - np.array(lowercase__       )).tolist()
														A__					:    str														= matop.subtract(lowercase__ ,     lowercase__       )
														assert theo == act
							else:
														with pytest.raises(lowercase__       ):
																					logger.info(F'''\n\t{test_subtraction.__name__} with different matrix dims'''       )
																					assert matop.subtract(lowercase__ ,     lowercase__       )

@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(		lowerCAmelCase ,     lowerCAmelCase       ):
							if (np.array(lowercase__       )).shape < (2, 2) or (np.array(lowercase__       )).shape < (2, 2):
														logger.info(F'''\n\t{test_multiplication.__name__} returned integer'''       )
														with pytest.raises(lowercase__       ):
																					matop.add(lowercase__ ,     lowercase__       )
							elif (np.array(lowercase__       )).shape == (np.array(lowercase__       )).shape:
														logger.info(F'''\n\t{test_multiplication.__name__} meets dim requirements'''       )
														A__					:    Any														= (np.matmul(lowercase__ ,     lowercase__       )).tolist()
														A__					:    List[Any]														= matop.multiply(lowercase__ ,     lowercase__       )
														assert theo == act
							else:
														with pytest.raises(lowercase__       ):
																					logger.info(
																					    F'''\n\t{test_multiplication.__name__} does not meet dim requirements'''       )
																					assert matop.subtract(lowercase__ ,     lowercase__       )

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

@pytest.mark.mat_ops
def    _A(		):
							A__					:    Tuple														= (np.identity(5       )).tolist()
							A__					:    str														= 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(		lowerCAmelCase       ):
							if (np.array(lowercase__       )).shape < (2, 2):
														with pytest.raises(lowercase__       ):
																					logger.info(F'''\n\t{test_transpose.__name__} returned integer'''       )
																					matop.transpose(lowercase__       )
							else:
														A__					:    Optional[int]														= (np.transpose(lowercase__       )).tolist()
														A__					:    Union[str, Any]														= matop.transpose(lowercase__ ,     return_map=lowercase__       )
														assert theo == act






"""simple docstring"""



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


_UpperCamelCase         =		logging.get_logger(__name__)

_UpperCamelCase         =		{
    "facebook/opt-125m": "https://huggingface.co/facebook/opt-125m/blob/main/config.json",
    "facebook/opt-350m": "https://huggingface.co/facebook/opt-350m/blob/main/config.json",
    "facebook/opt-1.3b": "https://huggingface.co/facebook/opt-1.3b/blob/main/config.json",
    "facebook/opt-2.7b": "https://huggingface.co/facebook/opt-2.7b/blob/main/config.json",
    "facebook/opt-6.7b": "https://huggingface.co/facebook/opt-6.7b/blob/main/config.json",
    "facebook/opt-13b": "https://huggingface.co/facebook/opt-13b/blob/main/config.json",
}
class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''
			_UpperCamelCase     :	Dict				    =							'opt'
			_UpperCamelCase     :	Optional[Any]				    =							['past_key_values']





			def __init__( self      ,			snake_case_=50_272      ,			snake_case_=768      ,			snake_case_=12      ,			snake_case_=3_072      ,			snake_case_=2_048      ,			snake_case_=True      ,			snake_case_=False      ,			snake_case_=None      ,			snake_case_=0.1      ,			snake_case_=0.0      ,			snake_case_=12      ,			snake_case_="relu"      ,			snake_case_=0.0      ,			snake_case_=0.02      ,			snake_case_=True      ,			snake_case_=1      ,			snake_case_=2      ,			snake_case_=2      ,			snake_case_=True      ,			snake_case_=True      ,			**snake_case_      ,			):







										'''simple docstring'''


										super().__init__(
										    pad_token_id=snake_case_      ,			bos_token_id=snake_case_      ,			eos_token_id=snake_case_      ,			**snake_case_      ,			)
										A__					:    int														= vocab_size
										A__					:    List[str]														= max_position_embeddings
										A__					:    str														= num_attention_heads
										A__					:    Dict														= word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
										A__					:    Optional[int]														= ffn_dim
										A__					:    Optional[int]														= hidden_size
										A__					:    int														= num_hidden_layers
										A__					:    str														= dropout
										A__					:    Tuple														= attention_dropout
										A__					:    Optional[Any]														= activation_function
										A__					:    Any														= init_std
										A__					:    Optional[int]														= layerdrop
										A__					:    Optional[int]														= use_cache
										A__					:    int														= do_layer_norm_before
										# We keep these variables at `True` for backward compatibility.
										A__					:    str														= enable_bias
										A__					:    List[str]														= layer_norm_elementwise_affine

										# Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
										# with checkpoints that have been fine-tuned before transformers v4.20.1
										# see https://github.com/facebookresearch/metaseq/pull/164
										A__					:    str														= _remove_final_layer_norm





