
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_      (__A							,					__A			)							->	Dict:



					"""simple docstring"""
					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'			)
										__a				:	Tuple			=				(np.array(__A			) + np.array(__A			)).tolist()
										__a				:	List[str]			=				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			)							->	Optional[Any]:



					"""simple docstring"""
					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'			)
										__a				:	List[Any]			=				(np.array(__A			) - np.array(__A			)).tolist()
										__a				:	List[str]			=				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			)							->	Any:



					"""simple docstring"""
					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'			)
										__a				:	Dict			=				(np.matmul(__A							,					__A			)).tolist()
										__a				:	Optional[Any]			=				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_      ()							->	str:



					"""simple docstring"""
					__a				:	str			=				(3.5 * np.array(__A			)).tolist()
					__a				:	List[Any]			=				matop.scalar_multiply(__A							,					3.5			)
					assert theo == act







@pytest.mark.mat_ops
def 						a_      ()							->	Any:



					"""simple docstring"""
					__a				:	int			=				(np.identity(5			)).tolist()
					__a				:	Union[str, Any]			=				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			)							->	Optional[Any]:



					"""simple docstring"""
					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:
										__a				:	str			=				(np.transpose(__A			)).tolist()
										__a				:	int			=				matop.transpose(__A							,					return_map=__A			)
										assert theo == act













from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase__			 =	{'''configuration_pegasus''': ['''PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusConfig''']}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	['''PegasusTokenizer''']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	['''PegasusTokenizerFast''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''PegasusForCausalLM''',
			    '''PegasusForConditionalGeneration''',
			    '''PegasusModel''',
			    '''PegasusPreTrainedModel''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''TFPegasusForConditionalGeneration''',
			    '''TFPegasusModel''',
			    '''TFPegasusPreTrainedModel''',
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''FlaxPegasusForConditionalGeneration''',
			    '''FlaxPegasusModel''',
			    '''FlaxPegasusPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_pegasus import PegasusTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_pegasus_fast import PegasusTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_pegasus import (
						    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
						    PegasusForCausalLM,
						    PegasusForConditionalGeneration,
						    PegasusModel,
						    PegasusPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_pegasus import (
						    FlaxPegasusForConditionalGeneration,
						    FlaxPegasusModel,
						    FlaxPegasusPreTrainedModel,
						)

else:
			import sys

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





