


import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible

class     snake_case      (							unittest.TestCase						):
			'''simple docstring'''

			def _lowercase			(						self  :  Optional[Any]       )       ->       Dict:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.bin''',
								    '''safety_checker/model.safetensors''',
								    '''vae/diffusion_pytorch_model.bin''',
								    '''vae/diffusion_pytorch_model.safetensors''',
								    '''text_encoder/pytorch_model.bin''',
								    '''text_encoder/model.safetensors''',
								    '''unet/diffusion_pytorch_model.bin''',
								    '''unet/diffusion_pytorch_model.safetensors''',
								]
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__       )       )

			def _lowercase			(						self  :  Union[str, Any]       )       ->       Optional[Any]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''unet/diffusion_pytorch_model.bin''',
								    '''unet/diffusion_pytorch_model.safetensors''',
								]
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__       )       )

			def _lowercase			(						self  :  str       )       ->       Union[str, Any]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.bin''',
								    '''safety_checker/model.safetensors''',
								    '''vae/diffusion_pytorch_model.bin''',
								    '''vae/diffusion_pytorch_model.safetensors''',
								    '''text_encoder/pytorch_model.bin''',
								    '''text_encoder/model.safetensors''',
								    '''unet/diffusion_pytorch_model.bin''',
								    # Removed: 'unet/diffusion_pytorch_model.safetensors',
								]
								self.assertFalse(is_safetensors_compatible(UpperCamelCase__       )       )

			def _lowercase			(						self  :  int       )       ->       Dict:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''text_encoder/pytorch_model.bin''',
								    '''text_encoder/model.safetensors''',
								]
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__       )       )

			def _lowercase			(						self  :  Union[str, Any]       )       ->       str:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.bin''',
								    '''safety_checker/model.safetensors''',
								    '''vae/diffusion_pytorch_model.bin''',
								    '''vae/diffusion_pytorch_model.safetensors''',
								    '''text_encoder/pytorch_model.bin''',
								    # Removed: 'text_encoder/model.safetensors',
								    '''unet/diffusion_pytorch_model.bin''',
								    '''unet/diffusion_pytorch_model.safetensors''',
								]
								self.assertFalse(is_safetensors_compatible(UpperCamelCase__       )       )

			def _lowercase			(						self  :  str       )       ->       Dict:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.fp16.bin''',
								    '''safety_checker/model.fp16.safetensors''',
								    '''vae/diffusion_pytorch_model.fp16.bin''',
								    '''vae/diffusion_pytorch_model.fp16.safetensors''',
								    '''text_encoder/pytorch_model.fp16.bin''',
								    '''text_encoder/model.fp16.safetensors''',
								    '''unet/diffusion_pytorch_model.fp16.bin''',
								    '''unet/diffusion_pytorch_model.fp16.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )

			def _lowercase			(						self  :  Optional[int]       )       ->       List[str]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''unet/diffusion_pytorch_model.fp16.bin''',
								    '''unet/diffusion_pytorch_model.fp16.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )

			def _lowercase			(						self  :  List[str]       )       ->       List[str]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''unet/diffusion_pytorch_model.bin''',
								    '''unet/diffusion_pytorch_model.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )

			def _lowercase			(						self  :  List[Any]       )       ->       Optional[Any]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.fp16.bin''',
								    '''safety_checker/model.fp16.safetensors''',
								    '''vae/diffusion_pytorch_model.fp16.bin''',
								    '''vae/diffusion_pytorch_model.fp16.safetensors''',
								    '''text_encoder/pytorch_model.fp16.bin''',
								    '''text_encoder/model.fp16.safetensors''',
								    '''unet/diffusion_pytorch_model.fp16.bin''',
								    # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertFalse(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )

			def _lowercase			(						self  :  Dict       )       ->       Union[str, Any]:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''text_encoder/pytorch_model.fp16.bin''',
								    '''text_encoder/model.fp16.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )

			def _lowercase			(						self  :  Tuple       )       ->       str:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''text_encoder/pytorch_model.bin''',
								    '''text_encoder/model.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertTrue(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )




			def _lowercase			(						self  :  List[Any]       )       ->       int:




								"""simple docstring"""






								SCREAMING_SNAKE_CASE_						   =							[
								    '''safety_checker/pytorch_model.fp16.bin''',
								    '''safety_checker/model.fp16.safetensors''',
								    '''vae/diffusion_pytorch_model.fp16.bin''',
								    '''vae/diffusion_pytorch_model.fp16.safetensors''',
								    '''text_encoder/pytorch_model.fp16.bin''',
								    # 'text_encoder/model.fp16.safetensors',
								    '''unet/diffusion_pytorch_model.fp16.bin''',
								    '''unet/diffusion_pytorch_model.fp16.safetensors''',
								]
								SCREAMING_SNAKE_CASE_						   =							'''fp16'''
								self.assertFalse(is_safetensors_compatible(UpperCamelCase__				,				variant=UpperCamelCase__       )       )



'''simple docstring'''






from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
   import numpy as np
   import tensorflow as tf

   from transformers import TFCamembertModel







@require_tf
@require_sentencepiece
@require_tokenizers
class lowercase_       (		unittest.TestCase			):







   """simple docstring"""

   @slow
   def 	__UpperCAmelCase   (      self      :			List[str]     )  ->			Any:
        _A    		=  TFCamembertModel.from_pretrained('jplu/tf-camembert-base'     )

        _A    		=  tf.convert_to_tensor(
            [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]], dtype=tf.intaa, )  # J'aime le camembert !"

        _A    		=  model(UpperCamelCase__     )['last_hidden_state']
        _A    		=  tf.TensorShape((1, 10, 7_68)     )
        self.assertEqual(output.shape, UpperCamelCase__     )
        # compare the actual values for a slice.
        _A    		=  tf.convert_to_tensor(
            [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]], dtype=tf.floataa, )
        # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
        # camembert.eval()
        # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

        self.assertTrue(np.allclose(output[:, :3, :3].numpy(), expected_slice.numpy(), atol=1e-4     )     )



