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def convert_model(model, to_transformer_engine=True, _convert_linear=True, _convert_ln=True): |
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""" |
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Recursively converts the linear and layernorm layers of a model to their `transformers_engine` counterpart. |
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""" |
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if not is_fp8_available(): |
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raise ImportError("Using `convert_model` requires transformer_engine to be installed.") |
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for name, module in model.named_children(): |
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if isinstance(module, nn.Linear) and to_transformer_engine and _convert_linear: |
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|
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if any(p % 16 != 0 for p in module.weight.shape): |
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return |
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has_bias = module.bias is not None |
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te_module = te.Linear( |
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module.in_features, module.out_features, bias=has_bias, params_dtype=module.weight.dtype |
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) |
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module.weight.copy_(te_module.weight) |
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if has_bias: |
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module.bias.copy_(te_module.bias) |
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setattr(model, name, te_module) |
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elif isinstance(module, nn.LayerNorm) and to_transformer_engine and _convert_ln: |
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te_module = te.LayerNorm(module.normalized_shape[0], eps=module.eps, params_dtype=module.weight.dtype) |
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module.weight.copy_(te_module.weight) |
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module.bias.copy_(te_module.bias) |
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setattr(model, name, te_module) |
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elif isinstance(module, te.Linear) and not to_transformer_engine and _convert_linear: |
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has_bias = module.bias is not None |
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new_module = nn.Linear( |
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module.in_features, module.out_features, bias=has_bias, params_dtype=module.weight.dtype |
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) |
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module.weight.copy_(new_module.weight) |
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if has_bias: |
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module.bias.copy_(new_module.bias) |
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setattr(model, name, new_module) |
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elif isinstance(module, te.LayerNorm) and not to_transformer_engine and _convert_ln: |
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new_module = nn.LayerNorm(module.normalized_shape[0], eps=module.eps, params_dtype=module.weight.dtype) |
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module.weight.copy_(new_module.weight) |
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module.bias.copy_(new_module.bias) |
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setattr(model, name, new_module) |
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else: |
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convert_model( |
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module, |
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to_transformer_engine=to_transformer_engine, |
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_convert_linear=_convert_linear, |
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_convert_ln=_convert_ln, |
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) |
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def has_transformer_engine_layers(model): |
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""" |
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Returns whether a given model has some `transformer_engine` layer or not. |
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""" |
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if not is_fp8_available(): |
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raise ImportError("Using `has_transformer_engine_layers` requires transformer_engine to be installed.") |
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for m in model.modules(): |
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if isinstance(m, (te.LayerNorm, te.Linear)): |
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return True |
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return False |
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