






"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE						:						Optional[Any]					   =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						:						Tuple					   =       {
    '''facebook/s2t-small-librispeech-asr''': (
        '''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'''
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}





class       snake_case_       (    lowercase_       ):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:							Dict   			=					"""speech_to_text"""
	SCREAMING_SNAKE_CASE_:							List[str]   			=					["""past_key_values"""]
	SCREAMING_SNAKE_CASE_:							str   			=					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}


	def __init__(      self  ,					__a=1_0000  ,					__a=12  ,					__a=2048  ,					__a=4  ,					__a=6  ,					__a=2048  ,					__a=4  ,					__a=0.0  ,					__a=0.0  ,					__a=True  ,					__a=True  ,					__a="relu"  ,					__a=256  ,					__a=0.1  ,					__a=0.0  ,					__a=0.0  ,					__a=0.02  ,					__a=2  ,					__a=True  ,					__a=1  ,					__a=0  ,					__a=2  ,					__a=6000  ,					__a=1024  ,					__a=2  ,					__a=(5, 5)  ,					__a=1024  ,					__a=80  ,					__a=1  ,					**__a  ,					):


					"""simple docstring"""

					A__							 =       vocab_size
					A__							 =       d_model
					A__							 =       encoder_ffn_dim
					A__							 =       encoder_layers
					A__							 =       encoder_attention_heads
					A__							 =       decoder_ffn_dim
					A__							 =       decoder_layers
					A__							 =       decoder_attention_heads
					A__							 =       dropout
					A__							 =       attention_dropout
					A__							 =       activation_dropout
					A__							 =       activation_function
					A__							 =       init_std
					A__							 =       encoder_layerdrop
					A__							 =       decoder_layerdrop
					A__							 =       use_cache
					A__							 =       encoder_layers
					A__							 =       scale_embedding  # scale factor will be sqrt(d_model) if True
					A__							 =       max_source_positions
					A__							 =       max_target_positions
					A__							 =       num_conv_layers
					A__							 =       list(lowerCamelCase_						)
					A__							 =       conv_channels
					A__							 =       input_feat_per_channel
					A__							 =       input_channels

					if len(self.conv_kernel_sizes						) != self.num_conv_layers:
									raise ValueError(
									    'Configuration for convolutional module is incorrect. '
									    'It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '
									    f'''but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes						)}`, '''
									    f'''`config.num_conv_layers = {self.num_conv_layers}`.'''						)

					super().__init__(
					    pad_token_id=lowerCamelCase_  ,					bos_token_id=lowerCamelCase_  ,					eos_token_id=lowerCamelCase_  ,					is_encoder_decoder=lowerCamelCase_  ,					decoder_start_token_id=lowerCamelCase_  ,					**lowerCamelCase_  ,					)










"""simple docstring"""






class       snake_case_       :



	"""simple docstring"""

	def __init__(      self  ,					__a  ,					__a						):


					"""simple docstring"""

					A__							 =       name
					A__							 =       val


	def __str__(      self						):


					"""simple docstring"""

					return f'''{self.__class__.__name__}({self.name}, {self.val})'''






	def __lt__(      self  ,					__a						):


					"""simple docstring"""

					return self.val < other.val





class       snake_case_       :



	"""simple docstring"""

	def __init__(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       {}
					A__							 =       {}
					A__							 =       self.build_heap(__a						)


	def __getitem__(      self  ,					__a						):


					"""simple docstring"""

					return self.get_value(__a						)


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return (idx - 1) // 2


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return idx * 2 + 1


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return idx * 2 + 2


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return self.heap_dict[key]


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       len(__a						) - 1
					A__							 =       self.get_parent_idx(__a						)

					for idx, i in enumerate(__a						):
									A__							 =       idx
									A__							 =       i.val

					for i in range(__a  ,					-1  ,					-1						):
									self.sift_down(__a  ,					__a						)
					return array


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a						):


					"""simple docstring"""

					while True:
									A__							 =       self.get_left_child_idx(__a						)  # noqa: E741
									A__							 =       self.get_right_child_idx(__a						)

									A__							 =       idx
									if l < len(__a						) and array[l] < array[idx]:
													A__							 =       l
									if r < len(__a						) and array[r] < array[smallest]:
													A__							 =       r

									if smallest != idx:
													A__ ,			A__							 =       array[smallest], array[idx]
													(
													    (
													    A__
													) ,			(
													    A__
													) ,			
													)							 =       (
													    self.idx_of_element[array[smallest]],
													    self.idx_of_element[array[idx]],
													)
													A__							 =       smallest
									else:
													break


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       self.get_parent_idx(__a						)
					while p >= 0 and self.heap[p] > self.heap[idx]:
									A__ ,			A__							 =       self.heap[idx], self.heap[p]
									A__ ,			A__							 =       (
									    self.idx_of_element[self.heap[idx]],
									    self.idx_of_element[self.heap[p]],
									)
									A__							 =       p
									A__							 =       self.get_parent_idx(__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return self.heap[0]


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__ ,			A__							 =       self.heap[-1], self.heap[0]
					A__ ,			A__							 =       (
					    self.idx_of_element[self.heap[-1]],
					    self.idx_of_element[self.heap[0]],
					)

					A__							 =       self.heap.pop()
					del self.idx_of_element[x]
					self.sift_down(0  ,					self.heap						)
					return x


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					self.heap.append(__a						)
					A__							 =       len(self.heap						) - 1
					A__							 =       node.val
					self.sift_up(len(self.heap						) - 1						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return len(self.heap						) == 0






	def       _UpperCAmelCase						(      self  ,					__a  ,					__a						):


					"""simple docstring"""

					assert (
					    self.heap[self.idx_of_element[node]].val > new_value
					), "newValue must be less that current value"
					A__							 =       new_value
					A__							 =       new_value
					self.sift_up(self.idx_of_element[node]						)





SCREAMING_SNAKE_CASE						:						List[str]					   =       Node('''R''', -1)
SCREAMING_SNAKE_CASE						:						Tuple					   =       Node('''B''', 6)
SCREAMING_SNAKE_CASE						:						List[Any]					   =       Node('''A''', 3)
SCREAMING_SNAKE_CASE						:						int					   =       Node('''X''', 1)
SCREAMING_SNAKE_CASE						:						Union[str, Any]					   =       Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
SCREAMING_SNAKE_CASE						:						str					   =       MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
					print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -17)

# After
for i in my_min_heap.heap:
					print(i)

if __name__ == "__main__":
					import doctest

					doctest.testmod()


