prepare_gradient_aggregation for non-leaf output of PartialProgramLayer #44893
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你的PR提交成功，感谢你对开源项目的贡献! |
Aurelius84
reviewed
Aug 4, 2022
| for in_arg in op.input_arg_names: | ||
| if in_arg == var.name: | ||
| return True | ||
| return False |
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reuturn var.name in op.input_arg_names
| @@ -287,6 +287,63 @@ def _verify_program(self, main_program): | |||
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| return main_program | |||
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| def prepare_gradient_aggregation(self, main_program, target_program): | |||
| # Why we need add Reverse gradient aggregation operation ? | |||
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函数注释最好用
""""
xxxx
"""""
格式
| lambda x: any([ | ||
| out_arg == var_grad_name | ||
| for out_arg in x[1].output_arg_names | ||
| ]), enumerate(target_program.block(0).ops))) |
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这个enumerate得到的值是插入的idx，后续插入Op会用到的。
| return False | ||
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| def _insert_aggregation_ops_for_var(target_program, var): | ||
| var_grad_name = var.name + "@GRAD" |
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这里最好不要写死 + "@Grad" ，grad后缀框架是有统一的API的
| # len(finded_ops) may > 1, because we may have fill_constant op. | ||
| if len(finded_ops) == 0: | ||
| return None | ||
| suffix = "@dy2static" |
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这里是不是最好使用 var_name + _dy2static + grad_suffix。
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