






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 							__a							(  unittest.TestCase						):





		'''simple docstring'''



		@slow
		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   TFCamembertModel.from_pretrained('jplu/tf-camembert-base'       )

						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   tf.convert_to_tensor(
						    [[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]] ,    dtype=tf.intaa ,    )  # J'aime le camembert !"

						SCREAMING_SNAKE_CASE_   :	Dict													=   model(UpperCamelCase__       )['last_hidden_state']
						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   tf.TensorShape((1, 10, 768)       )
						self.assertEqual(output.shape ,    UpperCamelCase__       )
						# compare the actual values for a slice.
						SCREAMING_SNAKE_CASE_   :	int													=   tf.convert_to_tensor(
						    [[[-0.02_54, 0.02_35, 0.10_27], [0.06_06, -0.18_11, -0.04_18], [-0.15_61, -0.11_27, 0.26_87]]] ,    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       )       )







import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union


@dataclass
class 							__a							:





		'''simple docstring'''



		UpperCAmelCase__      :				Optional[Union[str, Path]]				    =						None
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				Optional[Dict]				    =						None
		UpperCAmelCase__      :				Optional[str]				    =						None
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				bool				    =						True
		UpperCAmelCase__      :				Optional[int]				    =						None
		UpperCAmelCase__      :				int				    =						1
		UpperCAmelCase__      :				Optional[Union[str, bool]]				    =						None
		UpperCAmelCase__      :				bool				    =						False
		UpperCAmelCase__      :				Optional[Dict]				    =						None
		UpperCAmelCase__      :				Optional[str]				    =						None


		def   __snake_case			(						self       ):
						return self.__class__(**{k: copy.deepcopy(UpperCamelCase__       ) for k, v in self.__dict__.items()}       )