

import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
	import torch

	from transformers.activations import gelu_new, gelu_python, get_activation

@require_torch
class     a__  (    unittest.TestCase	):
			"""simple docstring"""







			def    UpperCamelCase						(			self				)     ->  Dict:
							'''simple docstring'''






							A__						=	torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
							A__						=	get_activation("gelu"				)
							self.assertTrue(torch.allclose(gelu_python(lowercase				)					,					torch_builtin(lowercase				)				)				)
							self.assertFalse(torch.allclose(gelu_python(lowercase				)					,					gelu_new(lowercase				)				)				)


			def    UpperCamelCase						(			self				)     ->  List[str]:
							'''simple docstring'''






							A__						=	torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
							A__						=	get_activation("gelu"				)
							A__						=	get_activation("gelu_10"				)

							A__						=	torch_builtin(lowercase				)
							A__						=	geluaa(lowercase				)

							A__						=	torch.where(y_gelu_aa < 10.0					,					1					,					0				)

							self.assertTrue(torch.max(lowercase				).item() == 10.0				)
							self.assertTrue(torch.allclose(y_gelu * clipped_mask					,					y_gelu_aa * clipped_mask				)				)


			def    UpperCamelCase						(			self				)     ->  int:
							'''simple docstring'''






							get_activation("gelu"				)
							get_activation("gelu_10"				)
							get_activation("gelu_fast"				)
							get_activation("gelu_new"				)
							get_activation("gelu_python"				)
							get_activation("gelu_pytorch_tanh"				)
							get_activation("linear"				)
							get_activation("mish"				)
							get_activation("quick_gelu"				)
							get_activation("relu"				)
							get_activation("sigmoid"				)
							get_activation("silu"				)
							get_activation("swish"				)
							get_activation("tanh"				)
							with self.assertRaises(lowercase				):
											get_activation("bogus"				)
							with self.assertRaises(lowercase				):
											get_activation(lowercase				)


			def    UpperCamelCase						(			self				)     ->  List[str]:
							'''simple docstring'''






							A__						=	get_activation("gelu"				)
							A__						=	1
							A__						=	get_activation("gelu"				)
							self.assertEqual(acta.a					,					1				)
							with self.assertRaises(lowercase				):
											A__						=	acta.a








from __future__ import annotations






def lowerCamelCase__    (							snake_case_	:  list[int]       ,      snake_case_	:  int       )      ->				list[list[int]]:
   __snake_case							       =   []
   __snake_case							       =   []
   __snake_case							       =   0
   __snake_case							       =   sum(snake_case_       )
   create_state_space_tree(snake_case_       ,      snake_case_       ,      snake_case_       ,      snake_case_       ,      snake_case_       ,      snake_case_       )
   return result






def lowerCamelCase__    (							snake_case_	:  list[int]       ,      snake_case_	:  int       ,      snake_case_	:  int       ,      snake_case_	:  list[int]       ,      snake_case_	:  list[list[int]]       ,      snake_case_	:  int       ,      )      ->				None:
   if sum(snake_case_       ) > max_sum or (remaining_nums_sum + sum(snake_case_       )) < max_sum:
      return
   if sum(snake_case_       ) == max_sum:
      result.append(snake_case_       )
      return
   for index in range(snake_case_       ,      len(snake_case_       )       ):
      create_state_space_tree(
          snake_case_       ,      snake_case_       ,      index + 1       ,      [*path, nums[index]]       ,      snake_case_       ,      remaining_nums_sum - nums[index]       ,      )
snake_case_				=			[3, 34, 4, 12, 5, 2]
snake_case_				=			9
snake_case_				=			generate_sum_of_subsets_soln(nums, max_sum)







print(*result)

