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@@ -45,11 +45,18 @@ _current_dir = os.path.dirname(os.path.realpath(__file__)) |
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def _set_bert_all_reduce_split(): |
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"""set bert all_reduce fusion split, support num_hidden_layers is 12 and 24.""" |
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device_target = context.get_context('device_target') |
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enable_graph_kernel = context.get_context('enable_graph_kernel') |
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device_num = context.get_auto_parallel_context('device_num') |
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if bert_net_cfg.num_hidden_layers == 12: |
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if bert_net_cfg.use_relative_positions: |
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context.set_auto_parallel_context(all_reduce_fusion_config=[29, 58, 87, 116, 145, 174, 203, 217]) |
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else: |
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context.set_auto_parallel_context(all_reduce_fusion_config=[28, 55, 82, 109, 136, 163, 190, 205]) |
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if device_target == 'GPU' and enable_graph_kernel and device_num == 8: |
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context.set_auto_parallel_context(all_reduce_fusion_config=[180, 205]) |
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elif device_target == 'GPU' and enable_graph_kernel and device_num == 16: |
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context.set_auto_parallel_context(all_reduce_fusion_config=[120, 205]) |
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elif bert_net_cfg.num_hidden_layers == 24: |
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if bert_net_cfg.use_relative_positions: |
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context.set_auto_parallel_context(all_reduce_fusion_config=[30, 90, 150, 210, 270, 330, 390, 421]) |
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@@ -119,8 +126,7 @@ def _get_optimizer(args_opt, network): |
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def _auto_enable_graph_kernel(device_target, graph_kernel_mode): |
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"""Judge whether is suitable to enable graph kernel.""" |
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return graph_kernel_mode in ("auto", "true") and device_target == 'GPU' and \ |
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cfg.bert_network == 'base' and (cfg.batch_size == 32 or cfg.batch_size == 64) and \ |
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cfg.optimizer == 'AdamWeightDecay' |
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cfg.bert_network == 'base' and cfg.optimizer == 'AdamWeightDecay' |
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def _set_graph_kernel_context(device_target, enable_graph_kernel, is_auto_enable_graph_kernel): |
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@@ -131,10 +137,15 @@ def _set_graph_kernel_context(device_target, enable_graph_kernel, is_auto_enable |
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logger.warning('Graph kernel only supports GPU back-end now, run with graph kernel off.') |
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def _check_compute_type(device_target, is_auto_enable_graph_kernel): |
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if device_target == 'GPU' and bert_net_cfg.compute_type != mstype.float32 and not is_auto_enable_graph_kernel: |
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logger.warning('Gpu only support fp32 temporarily, run with fp32.') |
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def _check_compute_type(args_opt, is_auto_enable_graph_kernel): |
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if args_opt.device_target == 'GPU' and bert_net_cfg.compute_type != mstype.float32 and \ |
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not is_auto_enable_graph_kernel: |
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warning_message = 'Gpu only support fp32 temporarily, run with fp32.' |
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bert_net_cfg.compute_type = mstype.float32 |
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if args_opt.enable_lossscale == "true": |
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args_opt.enable_lossscale = "false" |
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warning_message = 'Gpu only support fp32 temporarily, run with fp32 and disable lossscale.' |
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logger.warning(warning_message) |
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def argparse_init(): |
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@@ -180,6 +191,8 @@ def run_pretrain(): |
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args_opt = parser.parse_args() |
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context.set_context(mode=context.GRAPH_MODE, device_target=args_opt.device_target, device_id=args_opt.device_id) |
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context.set_context(reserve_class_name_in_scope=False) |
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is_auto_enable_graph_kernel = _auto_enable_graph_kernel(args_opt.device_target, args_opt.enable_graph_kernel) |
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_set_graph_kernel_context(args_opt.device_target, args_opt.enable_graph_kernel, is_auto_enable_graph_kernel) |
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ckpt_save_dir = args_opt.save_checkpoint_path |
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if args_opt.distribute == "true": |
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if args_opt.device_target == 'Ascend': |
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@@ -195,15 +208,12 @@ def run_pretrain(): |
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context.reset_auto_parallel_context() |
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context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True, |
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device_num=device_num) |
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if args_opt.device_target == 'Ascend': |
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_set_bert_all_reduce_split() |
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_set_bert_all_reduce_split() |
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else: |
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rank = 0 |
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device_num = 1 |
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is_auto_enable_graph_kernel = _auto_enable_graph_kernel(args_opt.device_target, args_opt.enable_graph_kernel) |
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_set_graph_kernel_context(args_opt.device_target, args_opt.enable_graph_kernel, is_auto_enable_graph_kernel) |
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_check_compute_type(args_opt.device_target, is_auto_enable_graph_kernel) |
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_check_compute_type(args_opt, is_auto_enable_graph_kernel) |
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if args_opt.accumulation_steps > 1: |
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logger.info("accumulation steps: {}".format(args_opt.accumulation_steps)) |
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