
'''simple docstring'''







from typing import TYPE_CHECKING

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


_lowercase :  List[Any]    							=       {
    "configuration_groupvit": [
        "GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "GroupViTConfig",
        "GroupViTOnnxConfig",
        "GroupViTTextConfig",
        "GroupViTVisionConfig",
    ],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase :  Tuple    							=       [
							    "GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "GroupViTModel",
							    "GroupViTPreTrainedModel",
							    "GroupViTTextModel",
							    "GroupViTVisionModel",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase :  List[str]    							=       [
							    "TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFGroupViTModel",
							    "TFGroupViTPreTrainedModel",
							    "TFGroupViTTextModel",
							    "TFGroupViTVisionModel",
							]

if TYPE_CHECKING:
							from .configuration_groupvit import (
							    GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    GroupViTConfig,
							    GroupViTOnnxConfig,
							    GroupViTTextConfig,
							    GroupViTVisionConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_groupvit import (
														    GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GroupViTModel,
														    GroupViTPreTrainedModel,
														    GroupViTTextModel,
														    GroupViTVisionModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_groupvit import (
														    TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFGroupViTModel,
														    TFGroupViTPreTrainedModel,
														    TFGroupViTTextModel,
														    TFGroupViTVisionModel,
														)

else:
							import sys

							_lowercase :  int    							=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''







import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
							from transformers import AutoModelForSeqaSeqLM, AutoTokenizer






@require_torch
@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase__   (  unittest.TestCase     ):






					@slow
					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Dict													=       AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''				,							return_dict=__SCREAMING_SNAKE_CASE		).to(__SCREAMING_SNAKE_CASE		)
											lowercase_	:     Union[str, Any]													=       AutoTokenizer.from_pretrained('''google/mt5-small'''		)

											lowercase_	:     int													=       tokenizer('''Hello there'''				,							return_tensors='''pt'''		).input_ids
											lowercase_	:     Union[str, Any]													=       tokenizer('''Hi I am'''				,							return_tensors='''pt'''		).input_ids

											lowercase_	:     Union[str, Any]													=       model(input_ids.to(__SCREAMING_SNAKE_CASE		)				,							labels=labels.to(__SCREAMING_SNAKE_CASE		)		).loss
											lowercase_	:     int													=       -(labels.shape[-1] * loss.item())

											lowercase_	:     Any													=       -84.9_127
											self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1E-4		)



