




'''simple docstring'''


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      SCREAMING_SNAKE_CASE    (						unittest.TestCase				):






      def 							lowercase_						( self   :  int       ):


           '''simple docstring'''

           a_     :							Dict     						=  {
               """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},
               }
           }
           a_     :							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 							lowercase_						( self   :  List[Any]       ):


           '''simple docstring'''

           a_     :							List[str]     						=  np.random.randn(3						,						4       )
           self.assertTrue(np.allclose(transpose(lowercase__       )						,						x.transpose()       )       )

           a_     :							Union[str, 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 							lowercase_						( self   :  List[str]       ):


           '''simple docstring'''

           a_     :							List[Any]     						=  np.random.randn(3						,						4       )
           a_     :							Union[str, Any]     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(transpose(lowercase__       )						,						transpose(lowercase__       ).numpy()       )       )

           a_     :							Any     						=  np.random.randn(3						,						4						,						5       )
           a_     :							Optional[Any]     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(transpose(lowercase__						,						axes=(1, 2, 0)       )						,						transpose(lowercase__						,						axes=(1, 2, 0)       ).numpy()       )       )






      @require_tf
      def 							lowercase_						( self   :  Union[str, Any]       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  np.random.randn(3						,						4       )
           a_     :							List[str]     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(transpose(lowercase__       )						,						transpose(lowercase__       ).numpy()       )       )

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






      @require_flax
      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							Any     						=  np.random.randn(3						,						4       )
           a_     :							Union[str, Any]     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(transpose(lowercase__       )						,						np.asarray(transpose(lowercase__       )       )       )       )

           a_     :							Union[str, Any]     						=  np.random.randn(3						,						4						,						5       )
           a_     :							Union[str, Any]     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(transpose(lowercase__						,						axes=(1, 2, 0)       )						,						np.asarray(transpose(lowercase__						,						axes=(1, 2, 0)       )       )       )       )






      def 							lowercase_						( self   :  List[str]       ):


           '''simple docstring'''

           a_     :							str     						=  np.random.randn(3						,						4       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(4, 3)       )						,						np.reshape(lowercase__						,						(4, 3)       )       )       )

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






      @require_torch
      def 							lowercase_						( self   :  int       ):


           '''simple docstring'''

           a_     :							List[str]     						=  np.random.randn(3						,						4       )
           a_     :							str     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(4, 3)       )						,						reshape(lowercase__						,						(4, 3)       ).numpy()       )       )

           a_     :							int     						=  np.random.randn(3						,						4						,						5       )
           a_     :							Dict     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(12, 5)       )						,						reshape(lowercase__						,						(12, 5)       ).numpy()       )       )






      @require_tf
      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  np.random.randn(3						,						4       )
           a_     :							Optional[Any]     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(4, 3)       )						,						reshape(lowercase__						,						(4, 3)       ).numpy()       )       )

           a_     :							int     						=  np.random.randn(3						,						4						,						5       )
           a_     :							str     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(12, 5)       )						,						reshape(lowercase__						,						(12, 5)       ).numpy()       )       )






      @require_flax
      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           a_     :							Any     						=  np.random.randn(3						,						4       )
           a_     :							Tuple     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(4, 3)       )						,						np.asarray(reshape(lowercase__						,						(4, 3)       )       )       )       )

           a_     :							int     						=  np.random.randn(3						,						4						,						5       )
           a_     :							Any     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(reshape(lowercase__						,						(12, 5)       )						,						np.asarray(reshape(lowercase__						,						(12, 5)       )       )       )       )






      def 							lowercase_						( self   :  Optional[Any]       ):


           '''simple docstring'''

           a_     :							Dict     						=  np.random.randn(1						,						3						,						4       )
           self.assertTrue(np.allclose(squeeze(lowercase__       )						,						np.squeeze(lowercase__       )       )       )

           a_     :							Dict     						=  np.random.randn(1						,						4						,						1						,						5       )
           self.assertTrue(np.allclose(squeeze(lowercase__						,						axis=2       )						,						np.squeeze(lowercase__						,						axis=2       )       )       )






      @require_torch
      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							Optional[Any]     						=  np.random.randn(1						,						3						,						4       )
           a_     :							Any     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__       )						,						squeeze(lowercase__       ).numpy()       )       )

           a_     :							Optional[int]     						=  np.random.randn(1						,						4						,						1						,						5       )
           a_     :							Optional[Any]     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__						,						axis=2       )						,						squeeze(lowercase__						,						axis=2       ).numpy()       )       )






      @require_tf
      def 							lowercase_						( self   :  Any       ):


           '''simple docstring'''

           a_     :							List[str]     						=  np.random.randn(1						,						3						,						4       )
           a_     :							Dict     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__       )						,						squeeze(lowercase__       ).numpy()       )       )

           a_     :							List[str]     						=  np.random.randn(1						,						4						,						1						,						5       )
           a_     :							Optional[int]     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__						,						axis=2       )						,						squeeze(lowercase__						,						axis=2       ).numpy()       )       )






      @require_flax
      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           a_     :							Union[str, Any]     						=  np.random.randn(1						,						3						,						4       )
           a_     :							str     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__       )						,						np.asarray(squeeze(lowercase__       )       )       )       )

           a_     :							Tuple     						=  np.random.randn(1						,						4						,						1						,						5       )
           a_     :							str     						=  jnp.array(lowercase__       )
           self.assertTrue(np.allclose(squeeze(lowercase__						,						axis=2       )						,						np.asarray(squeeze(lowercase__						,						axis=2       )       )       )       )






      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

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






      @require_torch
      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							int     						=  np.random.randn(3						,						4       )
           a_     :							Union[str, Any]     						=  torch.tensor(lowercase__       )
           self.assertTrue(np.allclose(expand_dims(lowercase__						,						axis=1       )						,						expand_dims(lowercase__						,						axis=1       ).numpy()       )       )






      @require_tf
      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           a_     :							str     						=  np.random.randn(3						,						4       )
           a_     :							int     						=  tf.constant(lowercase__       )
           self.assertTrue(np.allclose(expand_dims(lowercase__						,						axis=1       )						,						expand_dims(lowercase__						,						axis=1       ).numpy()       )       )






      @require_flax
      def 							lowercase_						( self   :  Tuple       ):


           '''simple docstring'''

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






'''simple docstring'''


from __future__ import annotations



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					list[float]				):




     """simple docstring"""


     if len(UpperCamelCase__				) < 2:
          raise ValueError("""Monogons and Digons are not polygons in the Euclidean space"""				)
     if any(i <= 0 for i in nums				):
          raise ValueError("""All values must be greater than 0"""				)
     a_     :							int     						=  nums.copy()
     copy_nums.sort()
     return copy_nums[-1] < sum(copy_nums[:-1]				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
