
import logging

# standard libraries
import sys

import numpy as np
import pytest  # type: ignore

# Custom/local libraries
from matrix import matrix_operation as matop

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

lowerCamelCase__        =						logging.getLogger()
lowerCamelCase__        =						logging.DEBUG
lowerCamelCase__        =						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 					lowerCAmelCase__     (    SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_	)							->						Optional[int]:
			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'''	)
						lowerCAmelCase__ : str   =						(np.array(SCREAMING_SNAKE_CASE_	) + np.array(SCREAMING_SNAKE_CASE_	)).tolist()
						lowerCAmelCase__ : List[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 					lowerCAmelCase__     (    SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_	)							->						Optional[Any]:
			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'''	)
						lowerCAmelCase__ : Dict   =						(np.array(SCREAMING_SNAKE_CASE_	) - np.array(SCREAMING_SNAKE_CASE_	)).tolist()
						lowerCAmelCase__ : Any   =						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 					lowerCAmelCase__     (    SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_	)							->						int:
			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'''	)
						lowerCAmelCase__ : Optional[int]   =						(np.matmul(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_	)).tolist()
						lowerCAmelCase__ : Union[str, Any]   =						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 					lowerCAmelCase__     (    )							->						str:
			lowerCAmelCase__ : str   =						(3.5 * np.array(SCREAMING_SNAKE_CASE_	)).tolist()
			lowerCAmelCase__ : Optional[Any]   =						matop.scalar_multiply(SCREAMING_SNAKE_CASE_			,				3.5	)
			assert theo == act
@pytest.mark.mat_ops
def 					lowerCAmelCase__     (    )							->						str:
			lowerCAmelCase__ : str   =						(np.identity(5	)).tolist()
			lowerCAmelCase__ : Dict   =						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 					lowerCAmelCase__     (    SCREAMING_SNAKE_CASE_	)							->						List[str]:
			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:
						lowerCAmelCase__ : Optional[int]   =						(np.transpose(SCREAMING_SNAKE_CASE_	)).tolist()
						lowerCAmelCase__ : str   =						matop.transpose(SCREAMING_SNAKE_CASE_			,				return_map=SCREAMING_SNAKE_CASE_	)
						assert theo == act

from typing import TYPE_CHECKING

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


lowerCamelCase__        =						{"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__        =						[
					    """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """RegNetForImageClassification""",
					    """RegNetModel""",
					    """RegNetPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__        =						[
					    """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFRegNetForImageClassification""",
					    """TFRegNetModel""",
					    """TFRegNetPreTrainedModel""",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__        =						[
					    """FlaxRegNetForImageClassification""",
					    """FlaxRegNetModel""",
					    """FlaxRegNetPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_regnet import (
										    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    RegNetForImageClassification,
										    RegNetModel,
										    RegNetPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_regnet import (
										    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFRegNetForImageClassification,
										    TFRegNetModel,
										    TFRegNetPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_regnet import (
										    FlaxRegNetForImageClassification,
										    FlaxRegNetModel,
										    FlaxRegNetPreTrainedModel,
										)


else:
					import sys

					lowerCamelCase__        =						_LazyModule(__name__, globals()["""__file__"""], _import_structure)