



"""simple docstring"""







import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402


UpperCamelCase     =							get_tests_dir("""fixtures/dummy-config.json""")






class       UpperCamelCase__			(   unittest.TestCase      ):

			"""simple docstring"""


			def   snake_case__	(      self		)      ->	Optional[int]:
				A__											=					0


			def   snake_case__	(      self		)      ->	Union[str, Any]:
				self.assertIsNotNone(transformers.models.auto.__spec__		)
				self.assertIsNotNone(importlib.util.find_spec("transformers.models.auto"		)		)


			def   snake_case__	(      self		)      ->	str:
				A__											=					AutoConfig.from_pretrained("bert-base-uncased"		)
				self.assertIsInstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self		)      ->	List[str]:
				A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__		)
				self.assertIsInstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self		)      ->	Dict:
				A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__		)
				self.assertIsInstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self		)      ->	Dict:
				A__											=					AutoConfig.for_model("roberta"		)
				self.assertIsInstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self		)      ->	Union[str, Any]:
				with tempfile.TemporaryDirectory() as tmp_dir:
					# This model name contains bert and roberta, but roberta ends up being picked.
					A__											=					os.path.join(SCREAMING_SNAKE_CASE__						,	"fake-roberta"		)
					os.makedirs(SCREAMING_SNAKE_CASE__						,	exist_ok=SCREAMING_SNAKE_CASE__		)
					with open(os.path.join(SCREAMING_SNAKE_CASE__						,	"config.json"		)						,	"w"		) as f:
						f.write(json.dumps({}		)		)
					A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__		)
					self.assertEqual(type(SCREAMING_SNAKE_CASE__		)						,	SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self		)      ->	str:
				try:
					AutoConfig.register("custom"						,	SCREAMING_SNAKE_CASE__		)
					# Wrong model type will raise an error
					with self.assertRaises(SCREAMING_SNAKE_CASE__		):
						AutoConfig.register("model"						,	SCREAMING_SNAKE_CASE__		)
					# Trying to register something existing in the Transformers library will raise an error
					with self.assertRaises(SCREAMING_SNAKE_CASE__		):
						AutoConfig.register("bert"						,	SCREAMING_SNAKE_CASE__		)

					# Now that the config is registered, it can be used as any other config with the auto-API
					A__											=					CustomConfig()
					with tempfile.TemporaryDirectory() as tmp_dir:
						config.save_pretrained(SCREAMING_SNAKE_CASE__		)
						A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__		)
						self.assertIsInstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)

				finally:
					if "custom" in CONFIG_MAPPING._extra_content:
						del CONFIG_MAPPING._extra_content["custom"]


			def   snake_case__	(      self		)      ->	List[Any]:
				with self.assertRaisesRegex(
				    SCREAMING_SNAKE_CASE__						,	"bert-base is not a local folder and is not a valid model identifier"		):
					A__											=					AutoConfig.from_pretrained("bert-base"		)


			def   snake_case__	(      self		)      ->	Tuple:
				with self.assertRaisesRegex(
				    SCREAMING_SNAKE_CASE__						,	R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"		):
					A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__						,	revision="aaaaaa"		)


			def   snake_case__	(      self		)      ->	Dict:
				with self.assertRaisesRegex(
				    SCREAMING_SNAKE_CASE__						,	"hf-internal-testing/no-config-test-repo does not appear to have a file named config.json."						,	):
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/no-config-test-repo"		)


			def   snake_case__	(      self		)      ->	str:
				# If remote code is not set, we will time out when asking whether to load the model.
				with self.assertRaises(SCREAMING_SNAKE_CASE__		):
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		)
				# If remote code is disabled, we can't load this config.
				with self.assertRaises(SCREAMING_SNAKE_CASE__		):
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"						,	trust_remote_code=SCREAMING_SNAKE_CASE__		)

				A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"						,	trust_remote_code=SCREAMING_SNAKE_CASE__		)
				self.assertEqual(config.__class__.__name__						,	"NewModelConfig"		)

				# Test config can be reloaded.
				with tempfile.TemporaryDirectory() as tmp_dir:
					config.save_pretrained(SCREAMING_SNAKE_CASE__		)
					A__											=					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__						,	trust_remote_code=SCREAMING_SNAKE_CASE__		)
				self.assertEqual(reloaded_config.__class__.__name__						,	"NewModelConfig"		)







			def   snake_case__	(      self		)      ->	int:






				class       UpperCamelCase__			(   _lowerCAmelCase      ):

							"""simple docstring"""


							A__	:					int							  =     "new-model"

				try:
					AutoConfig.register("new-model"						,	SCREAMING_SNAKE_CASE__		)
					# If remote code is not set, the default is to use local
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		)
					self.assertEqual(config.__class__.__name__						,	"NewModelConfigLocal"		)

					# If remote code is disabled, we load the local one.
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"						,	trust_remote_code=SCREAMING_SNAKE_CASE__		)
					self.assertEqual(config.__class__.__name__						,	"NewModelConfigLocal"		)

					# If remote is enabled, we load from the Hub
					A__											=					AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"						,	trust_remote_code=SCREAMING_SNAKE_CASE__		)
					self.assertEqual(config.__class__.__name__						,	"NewModelConfig"		)

				finally:
					if "new-model" in CONFIG_MAPPING._extra_content:
						del CONFIG_MAPPING._extra_content["new-model"]









"""simple docstring"""







from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ..utils.dummy_pt_objects import *  # noqa F403
else:
			from .scheduling_consistency_models import CMStochasticIterativeScheduler
			from .scheduling_ddim import DDIMScheduler
			from .scheduling_ddim_inverse import DDIMInverseScheduler
			from .scheduling_ddim_parallel import DDIMParallelScheduler
			from .scheduling_ddpm import DDPMScheduler
			from .scheduling_ddpm_parallel import DDPMParallelScheduler
			from .scheduling_deis_multistep import DEISMultistepScheduler
			from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
			from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
			from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
			from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
			from .scheduling_euler_discrete import EulerDiscreteScheduler
			from .scheduling_heun_discrete import HeunDiscreteScheduler
			from .scheduling_ipndm import IPNDMScheduler
			from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
			from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
			from .scheduling_karras_ve import KarrasVeScheduler
			from .scheduling_pndm import PNDMScheduler
			from .scheduling_repaint import RePaintScheduler
			from .scheduling_sde_ve import ScoreSdeVeScheduler
			from .scheduling_sde_vp import ScoreSdeVpScheduler
			from .scheduling_unclip import UnCLIPScheduler
			from .scheduling_unipc_multistep import UniPCMultistepScheduler
			from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
			from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ..utils.dummy_flax_objects import *  # noqa F403
else:
			from .scheduling_ddim_flax import FlaxDDIMScheduler
			from .scheduling_ddpm_flax import FlaxDDPMScheduler
			from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
			from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
			from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
			from .scheduling_pndm_flax import FlaxPNDMScheduler
			from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
			from .scheduling_utils_flax import (
			    FlaxKarrasDiffusionSchedulers,
			    FlaxSchedulerMixin,
			    FlaxSchedulerOutput,
			    broadcast_to_shape_from_left,
			)


try:
			if not (is_torch_available() and is_scipy_available()):
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
			from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
			if not (is_torch_available() and is_torchsde_available()):
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
			from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler




