
"""simple docstring"""







from __future__ import annotations

import pandas as pd
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase		):
	__lowerCAmelCase      :						int						      =				[0] * no_of_processes
	__lowerCAmelCase      :						str						      =				[0] * no_of_processes
	# Copy the burst time into remaining_time[]
	for i in range(__snake_case		):
		__lowerCAmelCase      :						List[Any]						      =				burst_time[i]

	__lowerCAmelCase      :						Union[str, Any]						      =				0
	__lowerCAmelCase      :						str						      =				0
	__lowerCAmelCase      :						Optional[int]						      =				9_9999_9999
	__lowerCAmelCase      :						Optional[Any]						      =				0
	__lowerCAmelCase      :						List[str]						      =				False

	# Process until all processes are completed
	while complete != no_of_processes:
		for j in range(__snake_case		):
			if arrival_time[j] <= increment_time and remaining_time[j] > 0:
				if remaining_time[j] < minm:
					__lowerCAmelCase      :						List[str]						      =				remaining_time[j]
					__lowerCAmelCase      :						int						      =				j
					__lowerCAmelCase      :						Optional[int]						      =				True

		if not check:
			increment_time += 1
			continue
		remaining_time[short] -= 1

		__lowerCAmelCase      :						Tuple						      =				remaining_time[short]
		if minm == 0:
			__lowerCAmelCase      :						Any						      =				9_9999_9999

		if remaining_time[short] == 0:
			complete += 1
			__lowerCAmelCase      :						str						      =				False

			# Find finish time of current process
			__lowerCAmelCase      :						Union[str, Any]						      =				increment_time + 1

			# Calculate waiting time
			__lowerCAmelCase      :						Optional[Any]						      =				finish_time - arrival_time[short]
			__lowerCAmelCase      :						Optional[Any]						      =				finar - burst_time[short]

			if waiting_time[short] < 0:
				__lowerCAmelCase      :						Any						      =				0

        # Increment time
		increment_time += 1
	return waiting_time
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase		):
	__lowerCAmelCase      :						Dict						      =				[0] * no_of_processes
	for i in range(__snake_case		):
		__lowerCAmelCase      :						Optional[Any]						      =				burst_time[i] + waiting_time[i]
	return turn_around_time
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase		):
	__lowerCAmelCase      :						Any						      =				0
	__lowerCAmelCase      :						List[str]						      =				0
	for i in range(__snake_case		):
		__lowerCAmelCase      :						int						      =				total_waiting_time + waiting_time[i]
		__lowerCAmelCase      :						str						      =				total_turn_around_time + turn_around_time[i]
	print(F"Average waiting time = {total_waiting_time / no_of_processes:.5f}"		)
	print('Average turn around time ='	,  total_turn_around_time / no_of_processes		)


if __name__ == "__main__":
							print("""Enter how many process you want to analyze""")
							lowerCamelCase__        =						int(input())
							lowerCamelCase__        =						[0] * no_of_processes
							lowerCamelCase__        =						[0] * no_of_processes
							lowerCamelCase__        =						list(range(1, no_of_processes + 1))

							for i in range(no_of_processes):
														print("""Enter the arrival time and burst time for process:--""" + str(i + 1))
														lowerCamelCase__ ,						lowerCamelCase__        =						map(int, input().split())

							lowerCamelCase__        =						calculate_waitingtime(arrival_time, burst_time, no_of_processes)

							lowerCamelCase__        =						burst_time
							lowerCamelCase__        =						no_of_processes
							lowerCamelCase__        =						waiting_time
							lowerCamelCase__        =						calculate_turnaroundtime(bt, n, wt)

							calculate_average_times(waiting_time, turn_around_time, no_of_processes)

							lowerCamelCase__        =						pd.DataFrame(
							    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
							    columns=[
							        """Process""",
							        """BurstTime""",
							        """ArrivalTime""",
							        """WaitingTime""",
							        """TurnAroundTime""",
							    ],
							)

							# Printing the dataFrame
							pd.set_option("""display.max_rows""", fcfs.shape[0] + 1)
							print(fcfs)

"""simple docstring"""







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


lowerCamelCase__        =		logging.get_logger(__name__)

lowerCamelCase__        =		{
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}




class 			A__	(     _lowerCamelCase):
		A_						:	str           =     'nllb-moe'
		A_						:	Optional[Any]           =     ['past_key_values']
		A_						:	List[str]           =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

		def __init__(				self	,		_SCREAMING_SNAKE_CASE=12_81_12	,		_SCREAMING_SNAKE_CASE=10_24	,		_SCREAMING_SNAKE_CASE=12	,		_SCREAMING_SNAKE_CASE=40_96	,		_SCREAMING_SNAKE_CASE=16	,		_SCREAMING_SNAKE_CASE=12	,		_SCREAMING_SNAKE_CASE=40_96	,		_SCREAMING_SNAKE_CASE=16	,		_SCREAMING_SNAKE_CASE=0.05	,		_SCREAMING_SNAKE_CASE=0.05	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE="relu"	,		_SCREAMING_SNAKE_CASE=10_24	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.0	,		_SCREAMING_SNAKE_CASE=0.02	,		_SCREAMING_SNAKE_CASE=2	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE="float32"	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=1_28	,		_SCREAMING_SNAKE_CASE=64	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=0.001	,		_SCREAMING_SNAKE_CASE=0.001	,		_SCREAMING_SNAKE_CASE="all"	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=1.0	,		_SCREAMING_SNAKE_CASE=0.2	,		_SCREAMING_SNAKE_CASE=1	,		_SCREAMING_SNAKE_CASE=0	,		_SCREAMING_SNAKE_CASE=2	,		_SCREAMING_SNAKE_CASE=False	,		**_SCREAMING_SNAKE_CASE	,		):
			__lowerCAmelCase      :						int						      =				vocab_size
			__lowerCAmelCase      :						str						      =				max_position_embeddings
			__lowerCAmelCase      :						Dict						      =				d_model
			__lowerCAmelCase      :						Tuple						      =				encoder_ffn_dim
			__lowerCAmelCase      :						Optional[Any]						      =				encoder_layers
			__lowerCAmelCase      :						Any						      =				encoder_attention_heads
			__lowerCAmelCase      :						Tuple						      =				decoder_ffn_dim
			__lowerCAmelCase      :						Dict						      =				decoder_layers
			__lowerCAmelCase      :						str						      =				decoder_attention_heads
			__lowerCAmelCase      :						str						      =				dropout
			__lowerCAmelCase      :						List[str]						      =				attention_dropout
			__lowerCAmelCase      :						Optional[int]						      =				activation_dropout
			__lowerCAmelCase      :						List[Any]						      =				activation_function
			__lowerCAmelCase      :						List[str]						      =				init_std
			__lowerCAmelCase      :						Union[str, Any]						      =				encoder_layerdrop
			__lowerCAmelCase      :						List[Any]						      =				decoder_layerdrop
			__lowerCAmelCase      :						Optional[int]						      =				use_cache
			__lowerCAmelCase      :						Optional[Any]						      =				encoder_layers
			__lowerCAmelCase      :						Optional[int]						      =				scale_embedding  # scale factor will be sqrt(d_model) if True
			__lowerCAmelCase      :						Union[str, Any]						      =				router_z_loss_coef
			__lowerCAmelCase      :						Optional[Any]						      =				router_aux_loss_coef
			__lowerCAmelCase      :						int						      =				decoder_sparse_step
			__lowerCAmelCase      :						str						      =				encoder_sparse_step
			__lowerCAmelCase      :						Tuple						      =				num_experts
			__lowerCAmelCase      :						Dict						      =				expert_capacity
			__lowerCAmelCase      :						Union[str, Any]						      =				router_bias
			if router_dtype not in ["float32", "float16", "bfloat16"]:
				raise ValueError(f"`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}"			)
			__lowerCAmelCase      :						Union[str, Any]						      =				router_dtype

			__lowerCAmelCase      :						Any						      =				router_ignore_padding_tokens
			__lowerCAmelCase      :						str						      =				batch_prioritized_routing
			__lowerCAmelCase      :						Tuple						      =				second_expert_policy
			__lowerCAmelCase      :						List[str]						      =				normalize_router_prob_before_dropping
			__lowerCAmelCase      :						Dict						      =				moe_eval_capacity_token_fraction
			__lowerCAmelCase      :						Union[str, Any]						      =				moe_token_dropout
			__lowerCAmelCase      :						List[Any]						      =				output_router_logits
			super().__init__(
			    pad_token_id=_SCREAMING_SNAKE_CASE	,		bos_token_id=_SCREAMING_SNAKE_CASE	,		eos_token_id=_SCREAMING_SNAKE_CASE	,		is_encoder_decoder=_SCREAMING_SNAKE_CASE	,		decoder_start_token_id=_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE	,		)