


import unittest

import numpy as np

from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
    expand_dims,
    flatten_dict,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    reshape,
    squeeze,
    transpose,
)


if is_flax_available():
 import jax.numpy as jnp

if is_tf_available():
 import tensorflow as tf

if is_torch_available():
 import torch




class A    (  unittest.TestCase	):






      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						Any            ={
                 'task_specific_params': {
                     'summarization': {'length_penalty': 1.0, 'max_length': 128, 'min_length': 12, 'num_beams': 4},
                     'summarization_cnn': {'length_penalty': 2.0, 'max_length': 142, 'min_length': 56, 'num_beams': 4},
                     'summarization_xsum': {'length_penalty': 1.0, 'max_length': 62, 'min_length': 11, 'num_beams': 6},
                 }
             }
             _lowerCamelCase			:						List[Any]            ={
                 'task_specific_params.summarization.length_penalty': 1.0,
                 'task_specific_params.summarization.max_length': 128,
                 'task_specific_params.summarization.min_length': 12,
                 'task_specific_params.summarization.num_beams': 4,
                 'task_specific_params.summarization_cnn.length_penalty': 2.0,
                 'task_specific_params.summarization_cnn.max_length': 142,
                 'task_specific_params.summarization_cnn.min_length': 56,
                 'task_specific_params.summarization_cnn.num_beams': 4,
                 'task_specific_params.summarization_xsum.length_penalty': 1.0,
                 'task_specific_params.summarization_xsum.max_length': 62,
                 'task_specific_params.summarization_xsum.min_length': 11,
                 'task_specific_params.summarization_xsum.num_beams': 6,
             }

             self.assertEqual(flatten_dict(lowercase_					)     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Dict					)   ->		List[str]:
             """simple docstring"""




             _lowerCamelCase			:						Dict            =np.random.randn(3     ,  4					)
             self.assertTrue(np.allclose(transpose(lowercase_					)     ,  x.transpose()					)					)

             _lowerCamelCase			:						Any            =np.random.randn(3     ,  4     ,  5					)
             self.assertTrue(np.allclose(transpose(lowercase_     ,  axes=(1, 2, 0)					)     ,  x.transpose((1, 2, 0)					)					)					)






      @require_torch
      def 			lowerCamelCase			(   self		:	str					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						Optional[Any]            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_					)     ,  transpose(lowercase_					).numpy()					)					)

             _lowerCamelCase			:						Optional[int]            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						Dict            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_     ,  axes=(1, 2, 0)					)     ,  transpose(lowercase_     ,  axes=(1, 2, 0)					).numpy()					)					)






      @require_tf
      def 			lowerCamelCase			(   self		:	Optional[int]					)   ->		Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase			:						Any            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						List[str]            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_					)     ,  transpose(lowercase_					).numpy()					)					)

             _lowerCamelCase			:						List[str]            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						Optional[int]            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_     ,  axes=(1, 2, 0)					)     ,  transpose(lowercase_     ,  axes=(1, 2, 0)					).numpy()					)					)






      @require_flax
      def 			lowerCamelCase			(   self		:	List[str]					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						Optional[int]            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_					)     ,  np.asarray(transpose(lowercase_					)					)					)					)

             _lowerCamelCase			:						Any            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						int            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(transpose(lowercase_     ,  axes=(1, 2, 0)					)     ,  np.asarray(transpose(lowercase_     ,  axes=(1, 2, 0)					)					)					)					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		Dict:
             """simple docstring"""




             _lowerCamelCase			:						int            =np.random.randn(3     ,  4					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (4, 3)					)     ,  np.reshape(lowercase_     ,  (4, 3)					)					)					)

             _lowerCamelCase			:						Optional[int]            =np.random.randn(3     ,  4     ,  5					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (12, 5)					)     ,  np.reshape(lowercase_     ,  (12, 5)					)					)					)






      @require_torch
      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		Dict:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						Tuple            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (4, 3)					)     ,  reshape(lowercase_     ,  (4, 3)					).numpy()					)					)

             _lowerCamelCase			:						Union[str, Any]            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						Optional[Any]            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (12, 5)					)     ,  reshape(lowercase_     ,  (12, 5)					).numpy()					)					)






      @require_tf
      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Dict            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						Any            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (4, 3)					)     ,  reshape(lowercase_     ,  (4, 3)					).numpy()					)					)

             _lowerCamelCase			:						Dict            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						int            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (12, 5)					)     ,  reshape(lowercase_     ,  (12, 5)					).numpy()					)					)






      @require_flax
      def 			lowerCamelCase			(   self		:	Dict					)   ->		Dict:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						List[Any]            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (4, 3)					)     ,  np.asarray(reshape(lowercase_     ,  (4, 3)					)					)					)					)

             _lowerCamelCase			:						Any            =np.random.randn(3     ,  4     ,  5					)
             _lowerCamelCase			:						Optional[int]            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(reshape(lowercase_     ,  (12, 5)					)     ,  np.asarray(reshape(lowercase_     ,  (12, 5)					)					)					)					)






      def 			lowerCamelCase			(   self		:	Any					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =np.random.randn(1     ,  3     ,  4					)
             self.assertTrue(np.allclose(squeeze(lowercase_					)     ,  np.squeeze(lowercase_					)					)					)

             _lowerCamelCase			:						Tuple            =np.random.randn(1     ,  4     ,  1     ,  5					)
             self.assertTrue(np.allclose(squeeze(lowercase_     ,  axis=2					)     ,  np.squeeze(lowercase_     ,  axis=2					)					)					)






      @require_torch
      def 			lowerCamelCase			(   self		:	Tuple					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =np.random.randn(1     ,  3     ,  4					)
             _lowerCamelCase			:						Any            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_					)     ,  squeeze(lowercase_					).numpy()					)					)

             _lowerCamelCase			:						int            =np.random.randn(1     ,  4     ,  1     ,  5					)
             _lowerCamelCase			:						int            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_     ,  axis=2					)     ,  squeeze(lowercase_     ,  axis=2					).numpy()					)					)






      @require_tf
      def 			lowerCamelCase			(   self		:	Dict					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						int            =np.random.randn(1     ,  3     ,  4					)
             _lowerCamelCase			:						int            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_					)     ,  squeeze(lowercase_					).numpy()					)					)

             _lowerCamelCase			:						Dict            =np.random.randn(1     ,  4     ,  1     ,  5					)
             _lowerCamelCase			:						int            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_     ,  axis=2					)     ,  squeeze(lowercase_     ,  axis=2					).numpy()					)					)






      @require_flax
      def 			lowerCamelCase			(   self		:	Any					)   ->		Dict:
             """simple docstring"""




             _lowerCamelCase			:						Any            =np.random.randn(1     ,  3     ,  4					)
             _lowerCamelCase			:						Optional[Any]            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_					)     ,  np.asarray(squeeze(lowercase_					)					)					)					)

             _lowerCamelCase			:						Optional[int]            =np.random.randn(1     ,  4     ,  1     ,  5					)
             _lowerCamelCase			:						int            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(squeeze(lowercase_     ,  axis=2					)     ,  np.asarray(squeeze(lowercase_     ,  axis=2					)					)					)					)






      def 			lowerCamelCase			(   self		:	int					)   ->		Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase			:						Any            =np.random.randn(3     ,  4					)
             self.assertTrue(np.allclose(expand_dims(lowercase_     ,  axis=1					)     ,  np.expand_dims(lowercase_     ,  axis=1					)					)					)






      @require_torch
      def 			lowerCamelCase			(   self		:	Tuple					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						str            =torch.tensor(lowercase_					)
             self.assertTrue(np.allclose(expand_dims(lowercase_     ,  axis=1					)     ,  expand_dims(lowercase_     ,  axis=1					).numpy()					)					)






      @require_tf
      def 			lowerCamelCase			(   self		:	List[Any]					)   ->		Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						int            =tf.constant(lowercase_					)
             self.assertTrue(np.allclose(expand_dims(lowercase_     ,  axis=1					)     ,  expand_dims(lowercase_     ,  axis=1					).numpy()					)					)






      @require_flax
      def 			lowerCamelCase			(   self		:	List[str]					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =np.random.randn(3     ,  4					)
             _lowerCamelCase			:						Any            =jnp.array(lowercase_					)
             self.assertTrue(np.allclose(expand_dims(lowercase_     ,  axis=1					)     ,  np.asarray(expand_dims(lowercase_     ,  axis=1					)					)					)					)






import warnings

from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor


lowerCamelCase		   =			logging.get_logger(__name__)




class A    (  UpperCamelCase_	):






      def __init__(   self		:	Optional[Any]     ,  *lowercase_		:	str     ,  **lowercase_		:	List[Any]					)   ->		None:
             """simple docstring"""




             warnings.warn(
                 'The class MobileViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
                 ' Please use MobileViTImageProcessor instead.'     ,  lowercase_     ,  )
             super().__init__(*lowercase_     ,  **lowercase_					)


