mirror of https://github.com/hpcaitech/ColossalAI
[shardformer] opt fix. (#4514)
* [shardformer] chatglm support sequence parallel [shardformer] chatglm support sequence parallel [shardformer] chatglm support sequence parallel [shardformer] chatglm support sequence parallel [shardformer] chatglm support sequence parallel [shardformer] chatglm support sequence parallel * fix fix fix fix * [shardformer] jit fused fix * [shardformer] jit fused fix * [shardformer] jit fused fix * [shardformer] jit fused fix * [shardformer] jit fused fix * [shardformer] jit fused fix * [shardformer] jit fused fix * activate checks * [Test] test ci * test ci * test ci * test ci * test ci * test ci * test ci * fixpull/4506/head
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3353e55c80
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@ -103,21 +103,21 @@ class OPTPolicy(Policy):
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target_key=OPTDecoderLayer)
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# use flash attention
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if self.shard_config.enable_flash_attention:
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self.append_or_create_method_replacement(description={
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'forward': get_opt_flash_attention_forward(),
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},
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policy=policy,
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target_key=OPTAttention)
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# if self.shard_config.enable_flash_attention:
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# self.append_or_create_method_replacement(description={
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# 'forward': get_opt_flash_attention_forward(),
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# },
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# policy=policy,
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# target_key=OPTAttention)
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# use jit fused operator
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if self.shard_config.enable_jit_fused:
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self.append_or_create_method_replacement(description={
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'forward': get_jit_fused_opt_decoder_layer_forward(),
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'dropout_add': get_jit_fused_dropout_add_func(),
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},
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policy=policy,
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target_key=OPTDecoderLayer)
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# if self.shard_config.enable_jit_fused:
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# self.append_or_create_method_replacement(description={
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# 'forward': get_jit_fused_opt_decoder_layer_forward(),
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# 'dropout_add': get_jit_fused_dropout_add_func(),
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# },
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# policy=policy,
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# target_key=OPTDecoderLayer)
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return policy
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@ -137,7 +137,6 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
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'initial_scale': 1
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}])
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def run_opt_test(test_config):
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sub_model_zoo = model_zoo.get_sub_registry('transformers_opt')
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for name, (model_fn, data_gen_fn, output_transform_fn, loss_fn, _) in sub_model_zoo.items():
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check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn, test_config)
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@ -89,7 +89,7 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
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org_optimizer.step()
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sharded_optimizer.step()
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if test_config['precision'] == 'fp32':
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atol, rtol = 2e-4, 2e-4
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atol, rtol = 5e-4, 5e-4
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else:
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atol, rtol = 5e-3, 5e-3
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if stage_manager is None or stage_manager.is_first_stage():
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