"polish activation" #9740
"polish activation" #9740
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| functor(*place, x, out, dout, dx); | ||
| } else { | ||
| framework::Tensor X; | ||
| auto x = framework::EigenVector<T>::Flatten(X); |
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can this flatten been avoided?
| @@ -101,6 +118,7 @@ struct SigmoidFunctor : public BaseActivationFunctor<T> { | |||
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| template <typename T> | |||
| struct SigmoidGradFunctor : public BaseActivationFunctor<T> { | |||
| bool Inplace() const { return true; } | |||
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Can we have this in C++
static char* inplace_acts = ["sigmoid", "exp", ...]
bool IsInPlaceAct(const string& n) {
return n in inplace_acts;
}
Inplace() { IsInPlaceAct("exp") }
in Python, we expose IsInPlaceAct() as core._is_in_place_act()
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| @@ -511,6 +512,9 @@ All parameter, weight, gradient are variables in Paddle. | |||
| self.back().set_lod(t.lod()); | |||
| }); | |||
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| m.def("IsInplace", | |||
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You can do that as a follow up, it seems the python style is is_in_place().
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This function bind c++ and Python, I thought that we should follow the c++ style where it been defined.
| return | ||
| self.check_grad(['X'], 'Out', max_relative_error=0.007) | ||
| # the gradient on floor, ceil, round is undefined. | ||
| # we return zero as gradient, but the numpy return nan |
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Something to consider in the future
returning None or Nan might be preferred since it avoids constructing a large zero tensor, saving some time and space.
Just curious, why it works before this PR?
| @@ -163,7 +163,12 @@ function(op_library TARGET) | |||
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| # pybind USE_OP | |||
| if (${pybind_flag} EQUAL 0) | |||
| # NOTE(*): activation use macro to regist the kernels, set use_op manually. | |||
| if(${TARGET} STREQUAL "activation") | |||
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Hopefully, we can remove this hard-coded "activation" and "relu" strings in the cmake files the future.
Add a TODO to clean up?
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Yep. The CMakeLists in operators need a clean up, will file a PR do this later.
fix #9416