import tempfile
import unittest

from diffusers import (
    DDIMScheduler,
    DDPMScheduler,
    DPMSolverMultistepScheduler,
    EulerAncestralDiscreteScheduler,
    EulerDiscreteScheduler,
    PNDMScheduler,
    logging,
)
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.utils.testing_utils import CaptureLogger







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):
       A							:	str          =	"config.json"

       @register_to_config
       def __init__(							self					:     Any			,			_lowerCAmelCase					:     Tuple=2			,			_lowerCAmelCase					:     List[Any]=5			,			_lowerCAmelCase					:     int=(2, 5)			,			_lowerCAmelCase					:     Dict="for diffusion"			,			_lowerCAmelCase					:     List[str]=[1, 3]			,			):
           pass







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):
       A							:	Optional[int]          =	"config.json"

       @register_to_config
       def __init__(							self					:     int			,			_lowerCAmelCase					:     Dict=2			,			_lowerCAmelCase					:     Union[str, Any]=5			,			_lowerCAmelCase					:     Any=(2, 5)			,			_lowerCAmelCase					:     Optional[int]="for diffusion"			,			_lowerCAmelCase					:     int=[1, 3]			,			):
           pass







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):
       A							:	str          =	"config.json"

       @register_to_config
       def __init__(							self					:     Any			,			_lowerCAmelCase					:     Optional[int]=2			,			_lowerCAmelCase					:     Optional[int]=5			,			_lowerCAmelCase					:     int=(2, 5)			,			_lowerCAmelCase					:     Tuple="for diffusion"			,			_lowerCAmelCase					:     Any=[1, 3]			,			_lowerCAmelCase					:     str=[1, 3]			,			):
           pass







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):
       A							:	Union[str, Any]          =	"config.json"

       @register_to_config
       def __init__(							self					:     Any			,			_lowerCAmelCase					:     Dict=2			,			_lowerCAmelCase					:     Optional[int]=5			,			_lowerCAmelCase					:     Optional[Any]=(2, 5)			,			_lowerCAmelCase					:     int="for diffusion"			,			_lowerCAmelCase					:     Dict=[1, 5]			,			_lowerCAmelCase					:     Optional[Any]=[5, 4]			,			):
           pass







class      SCREAMING_SNAKE_CASE__					(  unittest.TestCase    ):

       def 			snake_case__    (							self					:     List[str]			):
           with self.assertRaises(_lowerCAmelCase			):
               ConfigMixin.load_config("""dummy_path"""			)

       def 			snake_case__    (							self					:     List[Any]			):
           __snake_case       :				List[Any] 			=    SampleObject()
           __snake_case       :				Optional[Any] 			=    obj.config
           assert config["a"] == 2
           assert config["b"] == 5
           assert config["c"] == (2, 5)
           assert config["d"] == "for diffusion"
           assert config["e"] == [1, 3]

           # init ignore private arguments
           __snake_case       :				Optional[Any] 			=    SampleObject(_name_or_path="""lalala"""			)
           __snake_case       :				List[Any] 			=    obj.config
           assert config["a"] == 2
           assert config["b"] == 5
           assert config["c"] == (2, 5)
           assert config["d"] == "for diffusion"
           assert config["e"] == [1, 3]

           # can override default
           __snake_case       :				int 			=    SampleObject(c=6			)
           __snake_case       :				Union[str, Any] 			=    obj.config
           assert config["a"] == 2
           assert config["b"] == 5
           assert config["c"] == 6
           assert config["d"] == "for diffusion"
           assert config["e"] == [1, 3]

           # can use positional arguments.
           __snake_case       :				List[str] 			=    SampleObject(1			,			c=6			)
           __snake_case       :				str 			=    obj.config
           assert config["a"] == 1
           assert config["b"] == 5
           assert config["c"] == 6
           assert config["d"] == "for diffusion"
           assert config["e"] == [1, 3]

       def 			snake_case__    (							self					:     Union[str, Any]			):
           __snake_case       :				Union[str, Any] 			=    SampleObject()
           __snake_case       :				Optional[Any] 			=    obj.config

           assert config["a"] == 2
           assert config["b"] == 5
           assert config["c"] == (2, 5)
           assert config["d"] == "for diffusion"
           assert config["e"] == [1, 3]

           with tempfile.TemporaryDirectory() as tmpdirname:
               obj.save_config(_lowerCAmelCase			)
               __snake_case       :				List[Any] 			=    SampleObject.from_config(SampleObject.load_config(_lowerCAmelCase			)			)
               __snake_case       :				Union[str, Any] 			=    new_obj.config

           # unfreeze configs
           __snake_case       :				Optional[Any] 			=    dict(_lowerCAmelCase			)
           __snake_case       :				Optional[Any] 			=    dict(_lowerCAmelCase			)

           assert config.pop("""c"""			) == (2, 5)  # instantiated as tuple
           assert new_config.pop("""c"""			) == [2, 5]  # saved & loaded as list because of json
           config.pop("""_use_default_values"""			)
           assert config == new_config

       def 			snake_case__    (							self					:     Tuple			):
           __snake_case       :				Optional[Any] 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				List[Any] 			=    DDIMScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			)

           assert ddim.__class__ == DDIMScheduler
           # no warning should be thrown
           assert cap_logger.out == ""

       def 			snake_case__    (							self					:     Optional[int]			):
           __snake_case       :				int 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				Optional[int] 			=    EulerDiscreteScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			)

           assert euler.__class__ == EulerDiscreteScheduler
           # no warning should be thrown
           assert cap_logger.out == ""

       def 			snake_case__    (							self					:     Tuple			):
           __snake_case       :				int 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				Any 			=    EulerAncestralDiscreteScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			)

           assert euler.__class__ == EulerAncestralDiscreteScheduler
           # no warning should be thrown
           assert cap_logger.out == ""

       def 			snake_case__    (							self					:     List[Any]			):
           __snake_case       :				str 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				Optional[int] 			=    PNDMScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			)

           assert pndm.__class__ == PNDMScheduler
           # no warning should be thrown
           assert cap_logger.out == ""

       def 			snake_case__    (							self					:     Tuple			):
           __snake_case       :				int 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				List[str] 			=    DDPMScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			,			prediction_type="""sample"""			,			beta_end=8			,			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger_a:
               __snake_case       :				Optional[Any] 			=    DDPMScheduler.from_pretrained("""google/ddpm-celebahq-256"""			,			beta_start=88			)

           assert ddpm.__class__ == DDPMScheduler
           assert ddpm.config.prediction_type == "sample"
           assert ddpm.config.beta_end == 8
           assert ddpm_a.config.beta_start == 88

           # no warning should be thrown
           assert cap_logger.out == ""
           assert cap_logger_a.out == ""

       def 			snake_case__    (							self					:     List[Any]			):
           __snake_case       :				List[Any] 			=    logging.get_logger("""diffusers.configuration_utils"""			)
           # 30 for warning
           logger.setLevel(30			)

           with CaptureLogger(_lowerCAmelCase			) as cap_logger:
               __snake_case       :				str 			=    DPMSolverMultistepScheduler.from_pretrained(
                   """hf-internal-testing/tiny-stable-diffusion-torch"""			,			subfolder="""scheduler"""			)

           assert dpm.__class__ == DPMSolverMultistepScheduler
           # no warning should be thrown
           assert cap_logger.out == ""





       def 			snake_case__    (							self					:     List[Any]			):
           # let's first save a config that should be in the form
           #    a=2,
           #    b=5,
           #    c=(2, 5),
           #    d="for diffusion",
           #    e=[1, 3],

           __snake_case       :				Optional[Any] 			=    SampleObject()

           __snake_case       :				Union[str, Any] 			=    {k: v for k, v in config.config.items() if not k.startswith("""_"""			)}

           # make sure that default config has all keys in `_use_default_values`
           assert set(config_dict.keys()			) == set(config.config._use_default_values			)

           with tempfile.TemporaryDirectory() as tmpdirname:
               config.save_config(_lowerCAmelCase			)

               # now loading it with SampleObject2 should put f into `_use_default_values`
               __snake_case       :				Union[str, Any] 			=    SampleObjecta.from_config(_lowerCAmelCase			)

               assert "f" in config._use_default_values
               assert config.f == [1, 3]

           # now loading the config, should **NOT** use [1, 3] for `f`, but the default [1, 4] value
           # **BECAUSE** it is part of `config._use_default_values`
           __snake_case       :				Optional[int] 			=    SampleObjecta.from_config(config.config			)
           assert new_config.f == [5, 4]

           config.config._use_default_values.pop()
           __snake_case       :				Optional[Any] 			=    SampleObjecta.from_config(config.config			)
           assert new_config_a.f == [1, 3]

           # Nevertheless "e" should still be correctly loaded to [1, 3] from SampleObject2 instead of defaulting to [1, 5]
           assert new_config_a.e == [1, 3]




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_  							=			logging.get_logger(__name__)

lowercase_  							=			{
    "google/mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json"
}







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):
       A							:	List[Any]          =	MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
       A							:	int          =	"mobilebert"

       def __init__(							self					:     Any			,			_lowerCAmelCase					:     Union[str, Any]=3_05_22			,			_lowerCAmelCase					:     Tuple=5_12			,			_lowerCAmelCase					:     Dict=24			,			_lowerCAmelCase					:     int=4			,			_lowerCAmelCase					:     Optional[Any]=5_12			,			_lowerCAmelCase					:     Union[str, Any]="relu"			,			_lowerCAmelCase					:     List[str]=0.0			,			_lowerCAmelCase					:     str=0.1			,			_lowerCAmelCase					:     Tuple=5_12			,			_lowerCAmelCase					:     Optional[Any]=2			,			_lowerCAmelCase					:     Optional[int]=0.02			,			_lowerCAmelCase					:     List[str]=1e-12			,			_lowerCAmelCase					:     int=0			,			_lowerCAmelCase					:     Union[str, Any]=1_28			,			_lowerCAmelCase					:     Optional[Any]=True			,			_lowerCAmelCase					:     Dict=True			,			_lowerCAmelCase					:     Any=1_28			,			_lowerCAmelCase					:     Optional[int]=False			,			_lowerCAmelCase					:     str=True			,			_lowerCAmelCase					:     Tuple=4			,			_lowerCAmelCase					:     List[str]="no_norm"			,			_lowerCAmelCase					:     Union[str, Any]=True			,			_lowerCAmelCase					:     Optional[int]=None			,			**_lowerCAmelCase					:     int			,			):
           super().__init__(pad_token_id=_lowerCAmelCase			,			**_lowerCAmelCase			)

           __snake_case       :				Any 			=    vocab_size
           __snake_case       :				Tuple 			=    hidden_size
           __snake_case       :				int 			=    num_hidden_layers
           __snake_case       :				Dict 			=    num_attention_heads
           __snake_case       :				List[Any] 			=    hidden_act
           __snake_case       :				List[Any] 			=    intermediate_size
           __snake_case       :				Union[str, Any] 			=    hidden_dropout_prob
           __snake_case       :				Any 			=    attention_probs_dropout_prob
           __snake_case       :				Any 			=    max_position_embeddings
           __snake_case       :				List[Any] 			=    type_vocab_size
           __snake_case       :				List[Any] 			=    initializer_range
           __snake_case       :				Dict 			=    layer_norm_eps
           __snake_case       :				Any 			=    embedding_size
           __snake_case       :				List[str] 			=    trigram_input
           __snake_case       :				Union[str, Any] 			=    use_bottleneck
           __snake_case       :				List[Any] 			=    intra_bottleneck_size
           __snake_case       :				Tuple 			=    use_bottleneck_attention
           __snake_case       :				Optional[Any] 			=    key_query_shared_bottleneck
           __snake_case       :				Tuple 			=    num_feedforward_networks
           __snake_case       :				int 			=    normalization_type
           __snake_case       :				List[Any] 			=    classifier_activation

           if self.use_bottleneck:
               __snake_case       :				List[str] 			=    intra_bottleneck_size
           else:
               __snake_case       :				int 			=    hidden_size

           __snake_case       :				Optional[Any] 			=    classifier_dropout







class      SCREAMING_SNAKE_CASE__					(  __UpperCamelCase    ):

       @property
       def 			snake_case__    (							self					:     Optional[Any]			):
           if self.task == "multiple-choice":
               __snake_case       :				Any 			=    {0: """batch""", 1: """choice""", 2: """sequence"""}
           else:
               __snake_case       :				Optional[Any] 			=    {0: """batch""", 1: """sequence"""}
           return OrderedDict(
               [
                   ("""input_ids""", dynamic_axis),
                   ("""attention_mask""", dynamic_axis),
                   ("""token_type_ids""", dynamic_axis),
               ]			)



