Fix shape error when run qwen1.5-14b using deepspeed autotp (#11420)
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1 changed files with 8 additions and 5 deletions
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@ -361,8 +361,8 @@ def merge_qkv(module: torch.nn.Module):
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def padding_mlp(module: torch.nn.Module):
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# for qwen 1.5 14B
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if isinstance(module, Qwen2MLP):
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hidden_size = module.hidden_size
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intermediate_size = module.intermediate_size
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hidden_size = module.gate_proj.weight.shape[1]
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intermediate_size = module.gate_proj.weight.shape[0]
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padding_intermediate_size = (intermediate_size + 256 - 1) // 256 * 256
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if intermediate_size % 256 == 0:
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return
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@ -371,21 +371,24 @@ def padding_mlp(module: torch.nn.Module):
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new_gate_weight = torch.zeros([padding_intermediate_size, hidden_size],
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dtype=gate_weight.dtype, device=gate_weight.device)
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new_gate_weight[:intermediate_size, :] = gate_weight
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module.gate_proj.out_features = padding_intermediate_size
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if hasattr(module.gate_proj, 'out_features'):
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module.gate_proj.out_features = padding_intermediate_size
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module.gate_proj.weight = torch.nn.Parameter(new_gate_weight, requires_grad=False)
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up_weight = module.up_proj.weight.data
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new_up_weight = torch.zeros([padding_intermediate_size, hidden_size],
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dtype=up_weight.dtype, device=up_weight.device)
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new_up_weight[:intermediate_size, :] = up_weight
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module.up_proj.out_features = padding_intermediate_size
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if hasattr(module.gate_proj, 'out_features'):
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module.up_proj.out_features = padding_intermediate_size
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module.up_proj.weight = torch.nn.Parameter(new_up_weight, requires_grad=False)
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down_weight = module.down_proj.weight.data
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new_down_weight = torch.zeros([hidden_size, padding_intermediate_size],
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dtype=down_weight.dtype, device=down_weight.device)
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new_down_weight[:, :intermediate_size] = down_weight
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module.down_proj.in_features = padding_intermediate_size
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if hasattr(module.gate_proj, 'out_features'):
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module.down_proj.in_features = padding_intermediate_size
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module.down_proj.weight = torch.nn.Parameter(new_down_weight, requires_grad=False)
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