add generator #255
add generator #255
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| @@ -37,15 +39,13 @@ class MLUGeneratorImpl : public dipu::DIPUGeneratorImpl { | |||
| */ | |||
| void init_state() const override { | |||
| // resize and set the state tensor. | |||
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从目前 camb 和 cuda 的实现看， 是否可以改成能获取 get_state_size + setState 两个基础函数就可以了？ 或者只是 camb 实现一个 intState? update 的可以直接删掉了
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update_state必须存在，当更新了seed之后，就需要update_state；init_state可以删除，现在厂商只需要实现update_state和set_state即可
| m.def("_is_in_bad_fork", []()->bool { return is_in_bad_fork(); }); | ||
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| m.def("_create_dipu_generator", [](int idx)->at::Generator { | ||
| at::DeviceIndex index = static_cast<at::DeviceIndex>(idx); |
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default generator 是否要提前初始化出来，参考 csrc/cuda/Module.cpp THCPModule_initExtension() getDefaultCUDAGenerator() 的逻辑。 否则相关接口都调不通
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增加了default_generators的提前初始化
torch_dipu/dipu/random_dipu.py
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| default_generator.seed() | ||
| random_seed = default_generator.initial_seed() | ||
| _C._seed(i) | ||
| random_seed = _C._initial_seed() |
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已修复，并增加了测试，没有传递device index导致的报错
| def create_optional_generator_process_code(arg_name): | ||
| process_template = CodeTemplate( | ||
| """ | ||
| ::diopiGeneratorHandle_t ${arg_name}DiopiGenerator = (${arg_name}.has_value() && ${arg_name}.value().defined()) ? toDiopiGeneratorHandle(${arg_name}) : toDiopiGeneratorHandle(getDefaultDIPUGenerator()); |
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::diopiGeneratorHandle_t ${arg_name}DiopiGenerator = toDiopiGeneratorHandle((${arg_name}.has_value() && ${arg_name}.value().defined()) ? ${arg_name} : getDefaultDIPUGenerator());
| @@ -592,15 +594,17 @@ | |||
| - schema: "dropout_impl(Tensor input, float p, bool train, *, Tensor(a!) mask) -> Tensor" | |||
| custom_code_at_the_beginning: | | |||
| at::Tensor out = at::empty_like(input); | |||
| diopiGeneratorHandle_t generatorDiopiGenerator = toDiopiGeneratorHandle(getDefaultDIPUGenerator()); | |||
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toDiopiGeneratorHandle() 是否可以提供一个空参数的版本？这行就可以不用显示写出来了
| register_op: False | ||
| interface: diopiDropout(ctx, out, mask, input, p, train) | ||
| interface: diopiDropout(ctx, out, mask, input, p, train, generatorDiopiGenerator) |
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interface: diopiDropout(ctx, out, mask, input, p, train, getDefalutDiopiGenerator())
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