






#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# You may need to add --master_addr $MASTER_ADDR --master_port $MASTER_PORT if using a custom addr:port
#
# You can also use the rdzv API: --rdzv_endpoint $MASTER_ADDR:$MASTER_PORT --rdzv_backend c10d
#
# use torch.distributed.launch instead of torch.distributed.run for torch < 1.9
#
# If you get a hanging in `barrier` calls you have some network issues, you may try to debug this with:
#
# NCCL_DEBUG=INFO python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# which should tell you what's going on behind the scenes.
#
#
# This script can be run via `srun` in the SLURM environment as well. Here is a SLURM script that
# runs on 2 nodes of 4 gpus per node:
#
# #SBATCH --job-name=test-nodes        # name
# #SBATCH --nodes=2                    # nodes
# #SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
# #SBATCH --cpus-per-task=10           # number of cores per tasks
# #SBATCH --gres=gpu:4                 # number of gpus
# #SBATCH --time 0:05:00               # maximum execution time (HH:MM:SS)
# #SBATCH --output=%x-%j.out           # output file name
#
# GPUS_PER_NODE=4
# MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
# MASTER_PORT=6000
#
# srun --jobid $SLURM_JOBID bash -c 'python -m torch.distributed.run \
# --nproc_per_node $GPUS_PER_NODE --nnodes $SLURM_NNODES --node_rank $SLURM_PROCID \
# --master_addr $MASTER_ADDR --master_port $MASTER_PORT \
# torch-distributed-gpu-test.py'
#

import fcntl
import os
import socket

import torch
import torch.distributed as dist






def 				lowerCamelCase__				(*_UpperCAmelCase):



			with open(A__							,       'r') as fh:
						fcntl.flock(A__							,       fcntl.LOCK_EX)
						try:
									print(*A__)
						finally:
									fcntl.flock(A__							,       fcntl.LOCK_UN)


a_		:						str             =    int(os.environ['LOCAL_RANK'])
torch.cuda.set_device(local_rank)
a_		:						List[Any]             =    torch.device('cuda', local_rank)
a_		:						Union[str, Any]             =    socket.gethostname()

a_		:						Optional[int]             =    f"""[{hostname}-{local_rank}]"""

try:
				# test distributed
				dist.init_process_group('nccl')
				dist.all_reduce(torch.ones(1).to(device), op=dist.ReduceOp.SUM)
				dist.barrier()

				# test cuda is available and can allocate memory
				torch.cuda.is_available()
				torch.ones(1).cuda(local_rank)

				# global rank
				a_		:						Any             =    dist.get_rank()
				a_		:						Optional[Any]             =    dist.get_world_size()

				printflock(f"""{gpu} is OK (global rank: {rank}/{world_size})""")

				dist.barrier()
				if rank == 0:
								printflock(f"""pt={torch.__version__}, cuda={torch.version.cuda}, nccl={torch.cuda.nccl.version()}""")

except Exception:
				printflock(f"""{gpu} is broken""")
				raise












from abc import ABC, abstractmethod
from typing import List, Optional

class 		_snake_case  (  A__					):






			def __init__(       self)      ->       int:
						# test for the above condition
						self.test()






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Tuple:
						SCREAMING_SNAKE_CASE						= 0
						SCREAMING_SNAKE_CASE						= False
						while not completed:
									if counter == 1:
												self.reset()
									SCREAMING_SNAKE_CASE						= self.advance()
									if not self.does_advance(a):
												raise Exception(
												    'Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true.')

									SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= self.update(a)
									counter += 1

									if counter > 1_0000:
												raise Exception('update() does not fulfill the constraint.')

						if self.remaining() != 0:
									raise Exception('Custom Constraint is not defined correctly.')






			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')






			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       List[Any]:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')






			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Dict:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')






			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')






			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Dict:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')







			@abstractmethod
			def    SCREAMING_SNAKE_CASE__    (       self		,					a=False)      ->       int:
						raise NotImplementedError(
						    f'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''')



class 		_snake_case  (  A__					):






			def __init__(       self		,					a)      ->       Dict:
						super(a		,					self).__init__()

						if not isinstance(a		,					a) or len(a) == 0:
									raise ValueError(f'''`token_ids` has to be a non-empty list, but is {token_ids}.''')
						if any((not isinstance(a		,					a) or token_id < 0) for token_id in token_ids):
									raise ValueError(f'''Each list in `token_ids` has to be a list of positive integers, but is {token_ids}.''')

						SCREAMING_SNAKE_CASE						= token_ids

						SCREAMING_SNAKE_CASE						= len(self.token_ids)
						SCREAMING_SNAKE_CASE						= -1  # the index of the currently fulfilled step
						SCREAMING_SNAKE_CASE						= False






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[Any]:
						if self.completed:
									return None
						return self.token_ids[self.fulfilled_idx + 1]






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Any:
						if not isinstance(a		,					a):
									raise ValueError(f'''`token_id` has to be an `int`, but is {token_id} of type {type(a)}''')

						if self.completed:
									return False

						return token_id == self.token_ids[self.fulfilled_idx + 1]






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Optional[int]:
						if not isinstance(a		,					a):
									raise ValueError(f'''`token_id` has to be an `int`, but is {token_id} of type {type(a)}''')

						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= False

						if self.does_advance(a):
									self.fulfilled_idx += 1
									SCREAMING_SNAKE_CASE						= True
									if self.fulfilled_idx == (self.seqlen - 1):
												SCREAMING_SNAKE_CASE						= True
									SCREAMING_SNAKE_CASE						= completed
						else:
									# failed to make progress.
									SCREAMING_SNAKE_CASE						= True
									self.reset()
						return stepped, completed, reset






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= 0






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						return self.seqlen - (self.fulfilled_idx + 1)







			def    SCREAMING_SNAKE_CASE__    (       self		,					a=False)      ->       int:
						SCREAMING_SNAKE_CASE						= PhrasalConstraint(self.token_ids)

						if stateful:
									SCREAMING_SNAKE_CASE						= self.seqlen
									SCREAMING_SNAKE_CASE						= self.fulfilled_idx
									SCREAMING_SNAKE_CASE						= self.completed

						return new_constraint



class 		_snake_case  :






			def __init__(       self		,					a		,					a=True)      ->       Tuple:
						SCREAMING_SNAKE_CASE						= max([len(a) for one in nested_token_ids])

						SCREAMING_SNAKE_CASE						= {}
						for token_ids in nested_token_ids:
									SCREAMING_SNAKE_CASE						= root
									for tidx, token_id in enumerate(a):
												if token_id not in level:
															SCREAMING_SNAKE_CASE						= {}

												SCREAMING_SNAKE_CASE						= level[token_id]

						if no_subsets and self.has_subsets(a		,					a):
									raise ValueError(
									    'Each list in `nested_token_ids` can\'t be a complete subset of another list, but is'
									    f''' {nested_token_ids}.''')

						SCREAMING_SNAKE_CASE						= root






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Union[str, Any]:
						SCREAMING_SNAKE_CASE						= self.trie

						for current_token in current_seq:
									SCREAMING_SNAKE_CASE						= start[current_token]

						SCREAMING_SNAKE_CASE						= list(start.keys())

						return next_tokens






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       int:
						SCREAMING_SNAKE_CASE						= self.next_tokens(a)

						return len(a) == 0






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       int:
						SCREAMING_SNAKE_CASE						= list(root.values())
						if len(a) == 0:
									return 1
						else:
									return sum([self.count_leaves(a) for nn in next_nodes])







			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= self.count_leaves(a)
						return len(a) != leaf_count



class 		_snake_case  (  A__					):






			def __init__(       self		,					a)      ->       Dict:
						super(a		,					self).__init__()

						if not isinstance(a		,					a) or len(a) == 0:
									raise ValueError(f'''`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}.''')
						if any(not isinstance(a		,					a) for token_ids in nested_token_ids):
									raise ValueError(f'''`nested_token_ids` has to be a list of lists, but is {nested_token_ids}.''')
						if any(
						    any((not isinstance(a		,					a) or token_id < 0) for token_id in token_ids)
						    for token_ids in nested_token_ids):
									raise ValueError(
									    f'''Each list in `nested_token_ids` has to be a list of positive integers, but is {nested_token_ids}.''')

						SCREAMING_SNAKE_CASE						= DisjunctiveTrie(a)
						SCREAMING_SNAKE_CASE						= nested_token_ids

						SCREAMING_SNAKE_CASE						= self.trie.max_height
						SCREAMING_SNAKE_CASE						= []
						SCREAMING_SNAKE_CASE						= False






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= self.trie.next_tokens(self.current_seq)

						if len(a) == 0:
									return None
						else:
									return token_list






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       List[str]:
						if not isinstance(a		,					a):
									raise ValueError(f'''`token_id` is supposed to be type `int`, but is {token_id} of type {type(a)}''')

						SCREAMING_SNAKE_CASE						= self.trie.next_tokens(self.current_seq)

						return token_id in next_tokens






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       List[Any]:
						if not isinstance(a		,					a):
									raise ValueError(f'''`token_id` is supposed to be type `int`, but is {token_id} of type {type(a)}''')

						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= False

						if self.does_advance(a):
									self.current_seq.append(a)
									SCREAMING_SNAKE_CASE						= True
						else:
									SCREAMING_SNAKE_CASE						= True
									self.reset()

						SCREAMING_SNAKE_CASE						= self.trie.reached_leaf(self.current_seq)
						SCREAMING_SNAKE_CASE						= completed

						return stepped, completed, reset






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						SCREAMING_SNAKE_CASE						= False
						SCREAMING_SNAKE_CASE						= []






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Dict:
						if self.completed:
									# since this can be completed without reaching max height
									return 0
						else:
									return self.seqlen - len(self.current_seq)







			def    SCREAMING_SNAKE_CASE__    (       self		,					a=False)      ->       Union[str, Any]:
						SCREAMING_SNAKE_CASE						= DisjunctiveConstraint(self.token_ids)

						if stateful:
									SCREAMING_SNAKE_CASE						= self.seqlen
									SCREAMING_SNAKE_CASE						= self.current_seq
									SCREAMING_SNAKE_CASE						= self.completed

						return new_constraint



class 		_snake_case  :






			def __init__(       self		,					a)      ->       Union[str, Any]:
						SCREAMING_SNAKE_CASE						= constraints

						# max # of steps required to fulfill a given constraint
						SCREAMING_SNAKE_CASE						= max([c.seqlen for c in constraints])
						SCREAMING_SNAKE_CASE						= len(a)
						SCREAMING_SNAKE_CASE						= False

						self.init_state()






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= []
						SCREAMING_SNAKE_CASE						= None
						SCREAMING_SNAKE_CASE						= [constraint.copy(stateful=a) for constraint in self.constraints]






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Union[str, Any]:
						SCREAMING_SNAKE_CASE						= 0
						if self.inprogress_constraint:
									# extra points for having a constraint mid-fulfilled
									add += self.max_seqlen - self.inprogress_constraint.remaining()

						return (len(self.complete_constraints) * self.max_seqlen) + add






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Union[str, Any]:
						SCREAMING_SNAKE_CASE						= []
						if self.inprogress_constraint is None:
									for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
												SCREAMING_SNAKE_CASE						= constraint.advance()
												if isinstance(a		,					a):
															token_list.append(a)
												elif isinstance(a		,					a):
															token_list.extend(a)
						else:
									SCREAMING_SNAKE_CASE						= self.inprogress_constraint.advance()
									if isinstance(a		,					a):
												token_list.append(a)
									elif isinstance(a		,					a):
												token_list.extend(a)

						if len(a) == 0:
									return None
						else:
									return token_list






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       int:
						self.init_state()

						if token_ids is not None:
									for token in token_ids:
												# completes or steps **one** constraint
												SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= self.add(a)

												# the entire list of constraints are fulfilled
												if self.completed:
															break






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Union[str, Any]:
						if not isinstance(a		,					a):
									raise ValueError(f'''`token_id` should be an `int`, but is `{token_id}`.''')

						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= False, False

						if self.completed:
									SCREAMING_SNAKE_CASE						= True
									SCREAMING_SNAKE_CASE						= False
									return complete, stepped

						if self.inprogress_constraint is not None:
									# In the middle of fulfilling a constraint. If the `token_id` *does* makes an incremental progress to current
									# job, simply update the state

									SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= self.inprogress_constraint.update(a)
									if reset:
												# 1. If the next token breaks the progress, then we must restart.
												#     e.g. constraint = "I love pies" and sequence so far is "I love" but `token_id` == "books".

												#     But that doesn't mean we self.init_state(), since we only reset the state for this particular
												#     constraint, not the full list of constraints.

												self.pending_constraints.append(self.inprogress_constraint.copy(stateful=a))
												SCREAMING_SNAKE_CASE						= None

									if complete:
												# 2. If the next token completes the constraint, move it to completed list, set
												#     inprogress to None. If there are no pending constraints either, then this full list of constraints
												#     is complete.

												self.complete_constraints.append(self.inprogress_constraint)
												SCREAMING_SNAKE_CASE						= None

												if len(self.pending_constraints) == 0:
															# we're done!
															SCREAMING_SNAKE_CASE						= True

						else:
									# Not in the middle of fulfilling a constraint. So does this `token_id` helps us step towards any of our list
									# of constraints?

									for cidx, pending_constraint in enumerate(self.pending_constraints):
												if pending_constraint.does_advance(a):
															SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= pending_constraint.update(a)

															if not stepped:
																		raise Exception(
																		    '`constraint.update(token_id)` is not yielding incremental progress, '
																		    'even though `constraint.does_advance(token_id)` is true.')

															if complete:
																		self.complete_constraints.append(a)
																		SCREAMING_SNAKE_CASE						= None

															if not complete and stepped:
																		SCREAMING_SNAKE_CASE						= pending_constraint

															if complete or stepped:
																		# If we made any progress at all, then it's at least not a "pending constraint".

																		SCREAMING_SNAKE_CASE						= (
																		    self.pending_constraints[:cidx] + self.pending_constraints[cidx + 1 :]
																		)

																		if len(self.pending_constraints) == 0 and self.inprogress_constraint is None:
																					# If there's no longer any pending after this and no inprogress either, then we must be
																					# complete.

																					SCREAMING_SNAKE_CASE						= True

																		break  # prevent accidentally stepping through multiple constraints with just one token.

						return complete, stepped







			def    SCREAMING_SNAKE_CASE__    (       self		,					a=True)      ->       str:
						SCREAMING_SNAKE_CASE						= ConstraintListState(self.constraints)  # we actually never though self.constraints objects
						# throughout this process. So it's at initialization state.

						if stateful:
									SCREAMING_SNAKE_CASE						= [
									    constraint.copy(stateful=a) for constraint in self.complete_constraints
									]
									if self.inprogress_constraint is not None:
												SCREAMING_SNAKE_CASE						= self.inprogress_constraint.copy(stateful=a)
									SCREAMING_SNAKE_CASE						= [constraint.copy() for constraint in self.pending_constraints]

						return new_state




