





"""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

__magic_name__					:				Any	= [[1_2, 1_0], [3, 9]]
__magic_name__					:				Optional[Any]	= [[3, 4], [7, 4]]
__magic_name__					:				Any	= [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
__magic_name__					:				Tuple	= [[3, 0, -2], [2, 0, 2], [0, 1, 1]]
__magic_name__					:				str	= [[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
__magic_name__					:				Optional[int]	= [1]
__magic_name__					:				int	= [2]

__magic_name__					:				Tuple	= logging.getLogger()
__magic_name__					:				Tuple	= logging.DEBUG
__magic_name__					:				List[str]	= 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     UpperCamelCase       (SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    ):
						if (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2) or (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2):
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(f"""\n\t{test_addition.__name__} returned integer"""    )
																		matop.add(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
						elif (np.array(SCREAMING_SNAKE_CASE    )).shape == (np.array(SCREAMING_SNAKE_CASE    )).shape:
												logger.info(f"""\n\t{test_addition.__name__} with same matrix dims"""    )
												UpperCamelCase							:		Union[str, Any]							      = (np.array(SCREAMING_SNAKE_CASE    ) + np.array(SCREAMING_SNAKE_CASE    )).tolist()
												UpperCamelCase							:		Any							      = matop.add(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
												assert theo == act
						else:
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(f"""\n\t{test_addition.__name__} with different matrix dims"""    )
																		matop.add(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )

@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     UpperCamelCase       (SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    ):
						if (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2) or (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2):
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(f"""\n\t{test_subtraction.__name__} returned integer"""    )
																		matop.subtract(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
						elif (np.array(SCREAMING_SNAKE_CASE    )).shape == (np.array(SCREAMING_SNAKE_CASE    )).shape:
												logger.info(f"""\n\t{test_subtraction.__name__} with same matrix dims"""    )
												UpperCamelCase							:		Dict							      = (np.array(SCREAMING_SNAKE_CASE    ) - np.array(SCREAMING_SNAKE_CASE    )).tolist()
												UpperCamelCase							:		Dict							      = matop.subtract(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
												assert theo == act
						else:
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(f"""\n\t{test_subtraction.__name__} with different matrix dims"""    )
																		assert matop.subtract(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )

@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     UpperCamelCase       (SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    ):
						if (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2) or (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2):
												logger.info(f"""\n\t{test_multiplication.__name__} returned integer"""    )
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		matop.add(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
						elif (np.array(SCREAMING_SNAKE_CASE    )).shape == (np.array(SCREAMING_SNAKE_CASE    )).shape:
												logger.info(f"""\n\t{test_multiplication.__name__} meets dim requirements"""    )
												UpperCamelCase							:		int							      = (np.matmul(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )).tolist()
												UpperCamelCase							:		int							      = matop.multiply(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )
												assert theo == act
						else:
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(
																		    f"""\n\t{test_multiplication.__name__} does not meet dim requirements"""    )
																		assert matop.subtract(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    )

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

@pytest.mark.mat_ops
def     UpperCamelCase       ():
						UpperCamelCase							:		Dict							      = (np.identity(5    )).tolist()
						UpperCamelCase							:		Tuple							      = 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     UpperCamelCase       (SCREAMING_SNAKE_CASE    ):
						if (np.array(SCREAMING_SNAKE_CASE    )).shape < (2, 2):
												with pytest.raises(SCREAMING_SNAKE_CASE    ):
																		logger.info(f"""\n\t{test_transpose.__name__} returned integer"""    )
																		matop.transpose(SCREAMING_SNAKE_CASE    )
						else:
												UpperCamelCase							:		Optional[Any]							      = (np.transpose(SCREAMING_SNAKE_CASE    )).tolist()
												UpperCamelCase							:		List[str]							      = matop.transpose(SCREAMING_SNAKE_CASE       ,    return_map=SCREAMING_SNAKE_CASE    )
												assert theo == act










"""simple docstring"""


from typing import TYPE_CHECKING

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


__magic_name__					:				str	= {"""configuration_levit""": ["""LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LevitConfig""", """LevitOnnxConfig"""]}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__					:				Optional[int]	= ["""LevitFeatureExtractor"""]
		__magic_name__					:				Any	= ["""LevitImageProcessor"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__					:				List[Any]	= [
		    """LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """LevitForImageClassification""",
		    """LevitForImageClassificationWithTeacher""",
		    """LevitModel""",
		    """LevitPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_levit import LevitFeatureExtractor
				from .image_processing_levit import LevitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_levit import (
				    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LevitForImageClassification,
				    LevitForImageClassificationWithTeacher,
				    LevitModel,
				    LevitPreTrainedModel,
				)
else:
		import sys

		__magic_name__					:				Tuple	= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



