




"""simple docstring"""



import unittest

import numpy as np

from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
      import jax.numpy as jnp

      from transformers.models.albert.modeling_flax_albert import (
          FlaxAlbertForMaskedLM,
          FlaxAlbertForMultipleChoice,
          FlaxAlbertForPreTraining,
          FlaxAlbertForQuestionAnswering,
          FlaxAlbertForSequenceClassification,
          FlaxAlbertForTokenClassification,
          FlaxAlbertModel,
      )




class      UpperCAmelCase_  (						unittest.TestCase							):




    def __init__(   self						:	int     ,			snake_case_						:	Optional[Any]     ,			snake_case_						:	List[Any]=13     ,			snake_case_						:	Union[str, Any]=7     ,			snake_case_						:	Union[str, Any]=True     ,			snake_case_						:	int=True     ,			snake_case_						:	Any=True     ,			snake_case_						:	Any=True     ,			snake_case_						:	Optional[Any]=99     ,			snake_case_						:	int=32     ,			snake_case_						:	Optional[int]=5     ,			snake_case_						:	Optional[Any]=4     ,			snake_case_						:	List[Any]=37     ,			snake_case_						:	str="gelu"     ,			snake_case_						:	Optional[Any]=0.1     ,			snake_case_						:	Optional[Any]=0.1     ,			snake_case_						:	Dict=512     ,			snake_case_						:	int=16     ,			snake_case_						:	Union[str, Any]=2     ,			snake_case_						:	Optional[Any]=0.02     ,			snake_case_						:	int=4     ,			)				->							int:




     '''simple docstring'''

     A__	=    parent
     A__	=    batch_size
     A__	=    seq_length
     A__	=    is_training
     A__	=    use_attention_mask
     A__	=    use_token_type_ids
     A__	=    use_labels
     A__	=    vocab_size
     A__	=    hidden_size
     A__	=    num_hidden_layers
     A__	=    num_attention_heads
     A__	=    intermediate_size
     A__	=    hidden_act
     A__	=    hidden_dropout_prob
     A__	=    attention_probs_dropout_prob
     A__	=    max_position_embeddings
     A__	=    type_vocab_size
     A__	=    type_sequence_label_size
     A__	=    initializer_range
     A__	=    num_choices




    def 							__magic_name__							(   self						:	Dict				)				->							Tuple:




     '''simple docstring'''

     A__	=    ids_tensor([self.batch_size, self.seq_length]     ,			self.vocab_size				)

     A__	=    None
     if self.use_attention_mask:
      A__	=    random_attention_mask([self.batch_size, self.seq_length]				)

     A__	=    None
     if self.use_token_type_ids:
      A__	=    ids_tensor([self.batch_size, self.seq_length]     ,			self.type_vocab_size				)

     A__	=    AlbertConfig(
         vocab_size=self.vocab_size     ,			hidden_size=self.hidden_size     ,			num_hidden_layers=self.num_hidden_layers     ,			num_attention_heads=self.num_attention_heads     ,			intermediate_size=self.intermediate_size     ,			hidden_act=self.hidden_act     ,			hidden_dropout_prob=self.hidden_dropout_prob     ,			attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,			max_position_embeddings=self.max_position_embeddings     ,			type_vocab_size=self.type_vocab_size     ,			is_decoder=snake_case_     ,			initializer_range=self.initializer_range     ,			)

     return config, input_ids, token_type_ids, attention_mask




    def 							__magic_name__							(   self						:	Tuple				)				->							Optional[Any]:




     '''simple docstring'''

     A__	=    self.prepare_config_and_inputs()
     A__,				A__,				A__,				A__	=    config_and_inputs
     A__	=    {"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
     return config, inputs_dict






@require_flax
class      UpperCAmelCase_  (						A_,       unittest.TestCase							):
    lowercase__						 =				(
        (
            FlaxAlbertModel,
            FlaxAlbertForPreTraining,
            FlaxAlbertForMaskedLM,
            FlaxAlbertForMultipleChoice,
            FlaxAlbertForQuestionAnswering,
            FlaxAlbertForSequenceClassification,
            FlaxAlbertForTokenClassification,
            FlaxAlbertForQuestionAnswering,
        )
        if is_flax_available()
        else ()
    )




    def 							__magic_name__							(   self						:	Optional[Any]				)				->							str:




     '''simple docstring'''

     A__	=    FlaxAlbertModelTester(self				)




    @slow
    def 							__magic_name__							(   self						:	List[Any]				)				->							Optional[Any]:




     '''simple docstring'''

     for model_class_name in self.all_model_classes:
      A__	=    model_class_name.from_pretrained("albert-base-v2"				)
      A__	=    model(np.ones((1, 1)				)				)
      self.assertIsNotNone(snake_case_				)






@require_flax
class      UpperCAmelCase_  (						unittest.TestCase							):




    @slow
    def 							__magic_name__							(   self						:	Union[str, Any]				)				->							Optional[Any]:




     '''simple docstring'''

     A__	=    FlaxAlbertModel.from_pretrained("albert-base-v2"				)
     A__	=    np.array([[0, 345, 232, 328, 740, 140, 1_695, 69, 6_078, 1_588, 2]]				)
     A__	=    np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]				)
     A__	=    model(snake_case_     ,			attention_mask=snake_case_				)[0]
     A__	=    (1, 11, 768)
     self.assertEqual(output.shape     ,			snake_case_				)
     A__	=    np.array(
         [[[-0.6513, 1.5035, -0.2766], [-0.6515, 1.5046, -0.2780], [-0.6512, 1.5049, -0.2784]]]				)

     self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]     ,			snake_case_     ,			atol=1e-4				)				)







"""simple docstring"""



import unittest

from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		int:
 return x + 2






class      UpperCAmelCase_  (						unittest.TestCase							):




    def 							__magic_name__							(   self						:	Any				)				->							Any:




     '''simple docstring'''

     A__	=    "x = 3"
     A__	=    {}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     assert result == 3
     self.assertDictEqual(snake_case_     ,			{"x": 3}				)

     A__	=    "x = y"
     A__	=    {"y": 5}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     # evaluate returns the value of the last assignment.
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 5, "y": 5}				)




    def 							__magic_name__							(   self						:	Optional[Any]				)				->							Any:




     '''simple docstring'''

     A__	=    "y = add_two(x)"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{"add_two": add_two}     ,			state=snake_case_				)
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 3, "y": 5}				)

     # Won't work without the tool
     with CaptureStdout() as out:
      A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     assert result is None
     assert "tried to execute add_two" in out.out




    def 							__magic_name__							(   self						:	Dict				)				->							List[str]:




     '''simple docstring'''

     A__	=    "x = 3"
     A__	=    {}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     assert result == 3
     self.assertDictEqual(snake_case_     ,			{"x": 3}				)




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




     '''simple docstring'''

     A__	=    "test_dict = {'x': x, 'y': add_two(x)}"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{"add_two": add_two}     ,			state=snake_case_				)
     self.assertDictEqual(snake_case_     ,			{"x": 3, "y": 5}				)
     self.assertDictEqual(snake_case_     ,			{"x": 3, "test_dict": {"x": 3, "y": 5}}				)




    def 							__magic_name__							(   self						:	int				)				->							str:




     '''simple docstring'''

     A__	=    "x = 3\ny = 5"
     A__	=    {}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     # evaluate returns the value of the last assignment.
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 3, "y": 5}				)




    def 							__magic_name__							(   self						:	Any				)				->							List[Any]:




     '''simple docstring'''

     A__	=    "text = f'This is x: {x}.'"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     # evaluate returns the value of the last assignment.
     assert result == "This is x: 3."
     self.assertDictEqual(snake_case_     ,			{"x": 3, "text": "This is x: 3."}				)




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




     '''simple docstring'''

     A__	=    "if x <= 3:\n    y = 2\nelse:\n    y = 5"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     # evaluate returns the value of the last assignment.
     assert result == 2
     self.assertDictEqual(snake_case_     ,			{"x": 3, "y": 2}				)

     A__	=    {"x": 8}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     # evaluate returns the value of the last assignment.
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 8, "y": 5}				)




    def 							__magic_name__							(   self						:	List[str]				)				->							Tuple:




     '''simple docstring'''

     A__	=    "test_list = [x, add_two(x)]"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{"add_two": add_two}     ,			state=snake_case_				)
     self.assertListEqual(snake_case_     ,			[3, 5]				)
     self.assertDictEqual(snake_case_     ,			{"x": 3, "test_list": [3, 5]}				)




    def 							__magic_name__							(   self						:	Tuple				)				->							int:




     '''simple docstring'''

     A__	=    "y = x"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{}     ,			state=snake_case_				)
     assert result == 3
     self.assertDictEqual(snake_case_     ,			{"x": 3, "y": 3}				)




    def 							__magic_name__							(   self						:	str				)				->							Dict:




     '''simple docstring'''

     A__	=    "test_list = [x, add_two(x)]\ntest_list[1]"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{"add_two": add_two}     ,			state=snake_case_				)
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 3, "test_list": [3, 5]}				)

     A__	=    "test_dict = {'x': x, 'y': add_two(x)}\ntest_dict['y']"
     A__	=    {"x": 3}
     A__	=    evaluate(snake_case_     ,			{"add_two": add_two}     ,			state=snake_case_				)
     assert result == 5
     self.assertDictEqual(snake_case_     ,			{"x": 3, "test_dict": {"x": 3, "y": 5}}				)




    def 							__magic_name__							(   self						:	Optional[int]				)				->							Tuple:




     '''simple docstring'''

     A__	=    "x = 0\nfor i in range(3):\n    x = i"
     A__	=    {}
     A__	=    evaluate(snake_case_     ,			{"range": range}     ,			state=snake_case_				)
     assert result == 2
     self.assertDictEqual(snake_case_     ,			{"x": 2, "i": 2}				)





