






from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[str]     ):
	return getitem, k







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Tuple  ,						snake_case_      :							Tuple     ):
	return setitem, k, v







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	return delitem, k







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str  ,						snake_case_      :							Any  ,						*snake_case_      :							int     ):
	try:
		return fun(snake_case_  ,						*snake_case_     ), None
	except Exception as e:
		return None, e


__lowerCamelCase      :    Any   		=   (
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

__lowerCamelCase      :    int   		=   [
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

__lowerCamelCase      :    List[Any]   		=   [
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
    _del("""key_a"""),
    _del("""key_b"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
]

__lowerCamelCase      :    Optional[int]   		=   [
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

__lowerCamelCase      :    Any   		=   [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

__lowerCamelCase      :    Optional[int]   		=   [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("""key_a""", """val_b"""),
]







@pytest.mark.parametrize(
    "operations"  ,						(
        pytest.param(_add_items  ,						id="add items"     ),
        pytest.param(_overwrite_items  ,						id="overwrite items"     ),
        pytest.param(_delete_items  ,						id="delete items"     ),
        pytest.param(_access_absent_items  ,						id="access absent items"     ),
        pytest.param(_add_with_resize_up  ,						id="add with resize up"     ),
        pytest.param(_add_with_resize_down  ,						id="add with resize down"     ),
    )  ,						)
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	snake_case__				:   Optional[Any]     =						HashMap(initial_block_size=4     )
	snake_case__				:   Optional[Any]     =						{}
	for _, (fun, *args) in enumerate(snake_case_     ):
		snake_case__,		snake_case__				:   List[str]     =						_run_operation(snake_case_  ,						snake_case_  ,						*snake_case_     )
		snake_case__,		snake_case__				:   Dict     =						_run_operation(snake_case_  ,						snake_case_  ,						*snake_case_     )
		assert my_res == py_res
		assert str(snake_case_     ) == str(snake_case_     )
		assert set(snake_case_     ) == set(snake_case_     )
		assert len(snake_case_     ) == len(snake_case_     )
		assert set(my.items()     ) == set(py.items()     )







def   SCREAMING_SNAKE_CASE       (				):
	def is_public(snake_case_      :							str     ) -> bool:
		return not name.startswith("_"     )

	snake_case__				:   Tuple     =						{name for name in dir({}     ) if is_public(snake_case_     )}
	snake_case__				:   List[Any]     =						{name for name in dir(HashMap()     ) if is_public(snake_case_     )}

	assert dict_public_names > hash_public_names











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 							SCREAMING_SNAKE_CASE__		(       unittest.TestCase		):





					"""simple docstring"""






					def  _lowercase  (      self  :						Tuple ):
						snake_case__				:   List[str]     =						torch.tensor([-1_0_0, -1, -0.1, 0, 0.1, 1.0, 1_0_0] )
						snake_case__				:   Tuple     =						get_activation("gelu" )
						self.assertTrue(torch.allclose(gelu_python(__A )							,	torch_builtin(__A ) ) )
						self.assertFalse(torch.allclose(gelu_python(__A )							,	gelu_new(__A ) ) )



					def  _lowercase  (      self  :						Dict ):
						snake_case__				:   str     =						torch.tensor([-1_0_0, -1, -0.1, 0, 0.1, 1.0, 1_0_0] )
						snake_case__				:   Union[str, Any]     =						get_activation("gelu" )
						snake_case__				:   int     =						get_activation("gelu_10" )

						snake_case__				:   Optional[int]     =						torch_builtin(__A )
						snake_case__				:   Dict     =						geluaa(__A )

						snake_case__				:   Optional[Any]     =						torch.where(y_gelu_aa < 1_0.0							,	1							,	0 )

						self.assertTrue(torch.max(__A ).item() == 1_0.0 )
						self.assertTrue(torch.allclose(y_gelu * clipped_mask							,	y_gelu_aa * clipped_mask ) )



					def  _lowercase  (      self  :						str ):
						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(__A ):
							get_activation("bogus" )
						with self.assertRaises(__A ):
							get_activation(__A )






					def  _lowercase  (      self  :						List[str] ):
						snake_case__				:   List[str]     =						get_activation("gelu" )
						snake_case__				:   Any     =						1
						snake_case__				:   Union[str, Any]     =						get_activation("gelu" )
						self.assertEqual(acta.a							,	1 )
						with self.assertRaises(__A ):
							snake_case__				:   int     =						acta.a



