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[Prim][PIR] elu op forward decomp #62255

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merged 4 commits into from
Mar 18, 2024
Merged

[Prim][PIR] elu op forward decomp #62255

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3d08afd
forward decomp the elu op
zeroRains Feb 29, 2024
9b2e38f
fix code style
zeroRains Feb 29, 2024
9cfa0b6
add the check_prim_pir for grad
zeroRains Mar 4, 2024
744c528
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zeroRains Mar 16, 2024
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2 changes: 2 additions & 0 deletions paddle/fluid/pir/dialect/op_generator/decomp_interface_gen_op_list.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,7 @@
"batch_norm",
"batch_norm_",
"dropout",
"elu",
"embedding",
"flatten",
"full_like",
Expand Down Expand Up @@ -58,6 +59,7 @@
decomp_interface_implementation_gen_op_list = [
"add_n",
"dropout",
"elu",
"embedding",
"flatten",
"full_like",
Expand Down
20 changes: 20 additions & 0 deletions paddle/fluid/primitive/composite/composite.h
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Expand Up @@ -1043,6 +1043,26 @@ Tensor index_sample_decomp(const Tensor& x, const Tensor& index) {
}
}

template <typename T>
Tensor elu_decomp(const Tensor& x, const float alpha) {
auto org_dtype = x.dtype();
auto x_cast = x;

bool need_cast = is_half_dtype(org_dtype);
if (need_cast) {
x_cast = cast<T>(x, DataType::FLOAT32);
}

const Tensor zero = full<T>(x_cast.shape(), 0, x_cast.type());
auto tmp_res = alpha * (exp<T>(x_cast) - 1);
auto ans = where<T>(x_cast > zero, x_cast, tmp_res);
if (need_cast) {
return cast<T>(ans, org_dtype);
} else {
return ans;
}
}

} // namespace details

} // namespace primitive
Expand Down
17 changes: 14 additions & 3 deletions test/legacy_test/test_activation_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3443,6 +3443,8 @@ def setUp(self):
self.init_dtype()
self.init_shape()
self.python_api = paddle.nn.functional.elu
self.prim_op_type = "comp"
self.public_python_api = paddle.nn.functional.elu

np.random.seed(1024)
x = np.random.uniform(-3, 3, self.shape).astype(self.dtype)
Expand All @@ -3463,7 +3465,16 @@ def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(
['X'], 'Out', check_pir=True, check_pir_onednn=self.check_pir_onednn
['X'],
'Out',
check_pir=True,
check_prim_pir=True,
check_pir_onednn=self.check_pir_onednn,
)

def test_check_output(self):
self.check_output(
check_prim_pir=True, check_pir_onednn=self.check_pir_onednn
)

def get_alpha(self):
Expand Down Expand Up @@ -5320,7 +5331,7 @@ def test_check_grad(self):
create_test_act_fp16_class(TestBRelu, check_pir=True)
create_test_act_fp16_class(TestRelu6)
create_test_act_fp16_class(TestSoftRelu, check_dygraph=False)
create_test_act_fp16_class(TestELU, check_pir=True)
create_test_act_fp16_class(TestELU, check_pir=True, check_prim_pir=True)
create_test_act_fp16_class(TestCELU, check_pir=True)
create_test_act_fp16_class(TestReciprocal, check_pir=True)
create_test_act_fp16_class(TestLog, check_prim=True, check_pir=True)
Expand Down Expand Up @@ -5492,7 +5503,7 @@ def test_check_grad(self):
create_test_act_bf16_class(TestBRelu, check_pir=True)
create_test_act_bf16_class(TestRelu6)
create_test_act_bf16_class(TestSoftRelu, check_dygraph=False)
create_test_act_bf16_class(TestELU, check_pir=True)
create_test_act_bf16_class(TestELU, check_pir=True, check_prim_pir=True)
create_test_act_bf16_class(TestCELU, check_pir=True)
create_test_act_bf16_class(TestReciprocal, check_pir=True)
create_test_act_bf16_class(TestLog, check_prim=True, check_pir=True)
Expand Down