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feat: align elu with PyTorch Python API #811

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Merged
voltjia merged 1 commit into from
Jul 27, 2026
Merged

feat: align elu with PyTorch Python API #811

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22 changes: 22 additions & 0 deletions src/base/elu.h
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,21 @@ namespace infini::ops {

class Elu : public Operator<Elu> {
public:
Elu(const Tensor input, const double alpha, Tensor out)
: input_shape_{input.shape()},
input_strides_{input.strides()},
input_type_{input.dtype()},
out_shape_{out.shape()},
out_strides_{out.strides()},
out_type_{out.dtype()},
alpha_{alpha},
scale_{1.0},
input_scale_{1.0},
device_index_{out.device().index()} {}

/// \deprecated Use `Elu(input, alpha, out)`. This constructor will be
/// removed in a future release.
[[deprecated("Use the `(input, alpha, out)` overload instead.")]]
Elu(const Tensor input, const double alpha, const double scale,
const double input_scale, Tensor out)
: input_shape_{input.shape()},
Expand All @@ -20,6 +35,13 @@ class Elu : public Operator<Elu> {
input_scale_{input_scale},
device_index_{out.device().index()} {}

void operator()(const Tensor input, const double alpha, Tensor out) const {
return operator()(input, alpha, 1.0, 1.0, out);
}

/// \deprecated Use `operator()(input, alpha, out)`. This overload will be
/// removed in a future release.
[[deprecated("Use `operator()(input, alpha, out)` instead.")]]
virtual void operator()(const Tensor input, const double alpha,
const double scale, const double input_scale,
Tensor out) const = 0;
Expand Down
19 changes: 16 additions & 3 deletions tests/test_torch_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,8 +96,8 @@
("softplus", "beta"): 1.0,
("softplus", "threshold"): 20.0,
("elu", "alpha"): 1.0,
("elu", "scale"): 1.0,
("elu", "input_scale"): 1.0,
("elu", "scale"): 1.25,
("elu", "input_scale"): 0.75,
("sub", "alpha"): 1.0,
("addcmul", "value"): 1.0,
("addcdiv", "value"): 1.0,
Expand Down Expand Up @@ -530,8 +530,13 @@ def test_op(op_meta, shape, dtype, device, rtol, atol):
clone_strided(x) if isinstance(x, torch.Tensor) else x for x in inputs
]

if aten_name == "elu":
ref_func = torch.ops.aten.elu.default
else:
ref_func = _torch_func(aten_name)

try:
ref = _torch_func(aten_name)(*ref_inputs)
ref = ref_func(*ref_inputs)
except (
RuntimeError,
TypeError,
Expand Down Expand Up @@ -595,3 +600,11 @@ def test_op(op_meta, shape, dtype, device, rtol, atol):

for actual, expected in zip(outs, ref_outs):
_assert_close(actual, expected, rtol, atol)

if aten_name == "elu":
input, alpha = inputs[:2]
alpha_out = torch.empty_like(ref_outs[0])
_call_infini(op_name, input, alpha, alpha_out)
_assert_close(
alpha_out, torch.nn.functional.elu(input, alpha=alpha), rtol, atol
)
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