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@@ -336,10 +336,8 @@ class Trainer(TrainerIO):
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# set up server using proc 0's ip address
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# try to init for 20 times at max in case ports are taken
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ip_file_dir = os.path.join(self.cluster.log_path, 'ip_tables')
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dist.init_process_group("nccl", init_method=f'file://{ip_file_dir}', rank=self.proc_rank,
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world_size=self.world_size)
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# self.__init_tcp_connection(ip_file_dir)
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ip = self.__get_root_node_ip(self.proc_rank, self.nb_gpu_nodes)
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self.__init_tcp_connection(ip)
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# CHOOSE OPTIMIZER
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# filter out the weights that were done on gpu so we can load on good old cpus
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@@ -364,16 +362,16 @@ class Trainer(TrainerIO):
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# continue training routine
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self.__run_pretrain_routine(model)
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def __init_tcp_connection(self, path, port=12000, tries=0):
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def __init_tcp_connection(self, ip, port=12000, tries=0):
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if tries > 20:
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raise RuntimeError('Failed to connect using 20 different ip addresses')
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try:
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dist.init_process_group("nccl", init_method=f'file://{path}:{port}', rank=self.proc_rank, world_size=self.world_size)
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dist.init_process_group("nccl", init_method=f'tcp://{ip}:{port}', rank=self.proc_rank, world_size=self.world_size)
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except RuntimeError as e:
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# port taken
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warnings.warn(f'port {port} taken, trying port {port}...')
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self.__init_tcp_connection(path, port + 1, tries + 1)
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self.__init_tcp_connection(ip, port + 1, tries + 1)
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def __get_root_node_ip(self, world_gpu_nb, nb_gpu_nodes):
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"""
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@@ -386,8 +384,8 @@ class Trainer(TrainerIO):
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:return:
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"""
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# on one node we use localhost
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# if nb_gpu_nodes == 1:
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# return '127.0.0.1'
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if nb_gpu_nodes == 1:
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return '127.0.0.1'
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# where to store ip_table
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ip_file_dir = os.path.join(self.cluster.log_path, 'ip_tables')
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@@ -411,9 +409,6 @@ class Trainer(TrainerIO):
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return root_ip
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else:
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# sleep 10 seconds first to give file chance to write
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sleep(10)
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# wait up to 120 seconds until proc 0 writes
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# once written, read proc 0's address and use it to configure server
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for i in range(0, 120):
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