"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase       :    Dict									=			logging.get_logger(__name__)

UpperCAmelCase       :    Dict									=			{
    "nghuyong/ernie-1.0-base-zh": "https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-2.0-base-en": "https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json",
    "nghuyong/ernie-2.0-large-en": "https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json",
    "nghuyong/ernie-3.0-base-zh": "https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-medium-zh": "https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-mini-zh": "https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-micro-zh": "https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-nano-zh": "https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json",
    "nghuyong/ernie-gram-zh": "https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json",
    "nghuyong/ernie-health-zh": "https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json",
}

class        __SCREAMING_SNAKE_CASE     (   _lowerCAmelCase							):
				UpperCAmelCase	=      "ernie"







				def __init__(    self    :int      ,__UpperCAmelCase    :List[Any]=3_05_22      ,__UpperCAmelCase    :List[Any]=7_68      ,__UpperCAmelCase    :Optional[Any]=12      ,__UpperCAmelCase    :Tuple=12      ,__UpperCAmelCase    :Optional[Any]=30_72      ,__UpperCAmelCase    :List[str]="gelu"      ,__UpperCAmelCase    :List[str]=0.1      ,__UpperCAmelCase    :int=0.1      ,__UpperCAmelCase    :Optional[int]=5_12      ,__UpperCAmelCase    :List[str]=2      ,__UpperCAmelCase    :List[Any]=3      ,__UpperCAmelCase    :Union[str, Any]=False      ,__UpperCAmelCase    :Any=0.02      ,__UpperCAmelCase    :List[Any]=1E-12      ,__UpperCAmelCase    :Union[str, Any]=0      ,__UpperCAmelCase    :List[Any]="absolute"      ,__UpperCAmelCase    :Any=True      ,__UpperCAmelCase    :Tuple=None      ,**__UpperCAmelCase    :int      ,)      ->					Union[str, Any]:




									"""simple docstring"""



									super().__init__(pad_token_id=UpperCAmelCase__      ,**UpperCAmelCase__  )

									lowerCamelCase__		:   Optional[int]  				=					vocab_size
									lowerCamelCase__		:   Tuple  				=					hidden_size
									lowerCamelCase__		:   List[Any]  				=					num_hidden_layers
									lowerCamelCase__		:   int  				=					num_attention_heads
									lowerCamelCase__		:   Any  				=					hidden_act
									lowerCamelCase__		:   Any  				=					intermediate_size
									lowerCamelCase__		:   List[str]  				=					hidden_dropout_prob
									lowerCamelCase__		:   Tuple  				=					attention_probs_dropout_prob
									lowerCamelCase__		:   Dict  				=					max_position_embeddings
									lowerCamelCase__		:   Tuple  				=					type_vocab_size
									lowerCamelCase__		:   Dict  				=					task_type_vocab_size
									lowerCamelCase__		:   Any  				=					use_task_id
									lowerCamelCase__		:   Optional[int]  				=					initializer_range
									lowerCamelCase__		:   Tuple  				=					layer_norm_eps
									lowerCamelCase__		:   str  				=					position_embedding_type
									lowerCamelCase__		:   List[Any]  				=					use_cache
									lowerCamelCase__		:   Any  				=					classifier_dropout





class        __SCREAMING_SNAKE_CASE     (   _lowerCAmelCase							):







				@property
				def   lowercase_		(    self    :Tuple  )      ->					Optional[Any]:




									"""simple docstring"""



									if self.task == "multiple-choice":
														lowerCamelCase__		:   str  				=					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
														lowerCamelCase__		:   int  				=					{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									        ('''token_type_ids''', dynamic_axis),
									        ('''task_type_ids''', dynamic_axis),
									    ]  )









"""simple docstring"""





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    _lowerCAmelCase    (      lowercase  ):







 """simple docstring"""







 __UpperCAmelCase      :   Tuple  						=      "config.json"


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







class    _lowerCAmelCase    (      lowercase  ):







 """simple docstring"""







 __UpperCAmelCase      :   List[str]  						=      "config.json"


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







class    _lowerCAmelCase    (      lowercase  ):







 """simple docstring"""







 __UpperCAmelCase      :   str  						=      "config.json"


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







class    _lowerCAmelCase    (      lowercase  ):







 """simple docstring"""







 __UpperCAmelCase      :   List[str]  						=      "config.json"


 @register_to_config
 def __init__(     self				:     Union[str, Any],   UpperCAmelCase__				:     Any=2,   UpperCAmelCase__				:     Union[str, Any]=5,   UpperCAmelCase__				:     Optional[Any]=(2, 5),   UpperCAmelCase__				:     List[str]="for diffusion",   UpperCAmelCase__				:     Optional[Any]=[1, 5],   UpperCAmelCase__				:     Dict=[5, 4],   ):
    pass







class    _lowerCAmelCase    (      unittest.TestCase  ):







 """simple docstring"""







 def    _lowercase					(     self				:     Optional[int]      ):
    with self.assertRaises(UpperCAmelCase__      ):
       ConfigMixin.load_config("dummy_path"      )


 def    _lowercase					(     self				:     Optional[int]      ):
    __lowercase								=		SampleObject()
    __lowercase								=		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
    __lowercase								=		SampleObject(_name_or_path="lalala"      )
    __lowercase								=		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
    __lowercase								=		SampleObject(c=6      )
    __lowercase								=		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.
    __lowercase								=		SampleObject(1,   c=6      )
    __lowercase								=		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    _lowercase					(     self				:     Tuple      ):
    __lowercase								=		SampleObject()
    __lowercase								=		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(UpperCAmelCase__      )
       __lowercase								=		SampleObject.from_config(SampleObject.load_config(UpperCAmelCase__      )      )
       __lowercase								=		new_obj.config

    # unfreeze configs
    __lowercase								=		dict(UpperCAmelCase__      )
    __lowercase								=		dict(UpperCAmelCase__      )

    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    _lowercase					(     self				:     Any      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		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    _lowercase					(     self				:     int      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		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    _lowercase					(     self				:     Optional[Any]      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		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    _lowercase					(     self				:     str      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		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    _lowercase					(     self				:     Optional[Any]      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		DDPMScheduler.from_pretrained(
           "hf-internal-testing/tiny-stable-diffusion-torch",   subfolder="scheduler",   prediction_type="sample",   beta_end=8,   )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger_a:
       __lowercase								=		DDPMScheduler.from_pretrained("google/ddpm-celebahq-256",   beta_start=8_8      )

    assert ddpm.__class__ == DDPMScheduler
    assert ddpm.config.prediction_type == "sample"
    assert ddpm.config.beta_end == 8
    assert ddpm_a.config.beta_start == 8_8

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


 def    _lowercase					(     self				:     List[Any]      ):
    __lowercase								=		logging.get_logger("diffusers.configuration_utils"      )
    # 30 for warning
    logger.setLevel(3_0      )

    with CaptureLogger(UpperCAmelCase__      ) as cap_logger:
       __lowercase								=		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    _lowercase					(     self				:     str      ):
    # 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],

    __lowercase								=		SampleObject()

    __lowercase								=		{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(UpperCAmelCase__      )

       # now loading it with SampleObject2 should put f into `_use_default_values`
       __lowercase								=		SampleObjecta.from_config(UpperCAmelCase__      )

       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`
    __lowercase								=		SampleObjecta.from_config(config.config      )
    assert new_config.f == [5, 4]

    config.config._use_default_values.pop()
    __lowercase								=		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]




