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[numpy] torch.{a}tanh : promote integer inputs to float #47064

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[numpy] torch.{a}tanh : promote integer inputs to float #47064

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049d2a1
promote int to float support
kshitij12345 Oct 29, 2020
2f3c0d2
update relevant test
kshitij12345 Oct 29, 2020
2c7398a
Merge branch 'master' into develop/numpy/unary-float-ops/atanh-tanh
kshitij12345 Oct 31, 2020
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8 changes: 4 additions & 4 deletions aten/src/ATen/native/UnaryOps.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -369,8 +369,8 @@ Tensor& arcsinh_out(Tensor& result, const Tensor& self) { return at::asinh_out(r
Tensor arcsinh(const Tensor& self) { return self.asinh(); }
Tensor& arcsinh_(Tensor& self) { return self.asinh_(); }

Tensor& atanh_out(Tensor& result, const Tensor& self) { return unary_op_impl_out(result, self, atanh_stub); }
Tensor atanh(const Tensor& self) { return unary_op_impl(self, at::atanh_out); }
Tensor& atanh_out(Tensor& result, const Tensor& self) { return unary_op_impl_float_out(result, self, atanh_stub); }
Tensor atanh(const Tensor& self) { return unary_op_impl_float(self, atanh_stub); }
Tensor& atanh_(Tensor& self) { return unary_op_impl_(self, at::atanh_out); }

// arctanh, alias for atanh
Expand Down Expand Up @@ -448,8 +448,8 @@ Tensor& nan_to_num_(
return at::nan_to_num_out(self, self, nan, pos_inf, neg_inf);
}

Tensor& tanh_out(Tensor& result, const Tensor& self) { return unary_op_impl_out(result, self, tanh_stub); }
Tensor tanh(const Tensor& self) { return unary_op_impl(self, at::tanh_out); }
Tensor& tanh_out(Tensor& result, const Tensor& self) { return unary_op_impl_float_out(result, self, tanh_stub); }
Tensor tanh(const Tensor& self) { return unary_op_impl_float(self, tanh_stub); }
Tensor& tanh_(Tensor& self) { return unary_op_impl_(self, at::tanh_out); }

Tensor& tan_out(Tensor& result, const Tensor& self) { return unary_op_impl_out(result, self, tan_stub); }
Expand Down
4 changes: 2 additions & 2 deletions aten/src/ATen/native/cuda/UnaryGeometricKernels.cu
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Expand Up @@ -67,7 +67,7 @@ void cosh_kernel_cuda(TensorIterator& iter) {
}

void tanh_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_AND_COMPLEX_TYPES_AND2(ScalarType::Half, ScalarType::BFloat16, iter.dtype(), "tanh_cuda", [&]() {
AT_DISPATCH_FLOATING_AND_COMPLEX_TYPES_AND2(ScalarType::Half, ScalarType::BFloat16, iter.common_dtype(), "tanh_cuda", [&]() {
gpu_kernel(iter, []GPU_LAMBDA(scalar_t a) -> scalar_t {
return ::tanh(a);
});
Expand All @@ -91,7 +91,7 @@ void asinh_kernel_cuda(TensorIterator& iter) {
}

void atanh_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES_AND2(ScalarType::Half, ScalarType::BFloat16, iter.dtype(), "atanh_cuda", [&]() {
AT_DISPATCH_FLOATING_TYPES_AND2(ScalarType::Half, ScalarType::BFloat16, iter.common_dtype(), "atanh_cuda", [&]() {
gpu_kernel(iter, []GPU_LAMBDA(scalar_t a) -> scalar_t {
return ::atanh(a);
});
Expand Down
5 changes: 3 additions & 2 deletions torch/csrc/jit/tensorexpr/kernel.cpp
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Expand Up @@ -1123,8 +1123,9 @@ Tensor* TensorExprKernel::computeValue(const torch::jit::Value* v) {
} break;

case aten::tanh: {
return computeOneOperand(
"aten_tanh", v, [](const ExprHandle& a) { return tanh(a); });
return computeOneOperand("aten_tanh", v, [](const ExprHandle& a) {
return tanh(promoteIntegerToFloat(a));
});
} break;

case aten::sqrt: {
Expand Down
11 changes: 8 additions & 3 deletions torch/testing/_internal/common_methods_invocations.py
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Expand Up @@ -268,8 +268,10 @@ def sample_inputs(self, device, dtype, requires_grad=False):
UnaryUfuncInfo('atanh',
ref=np.arctanh,
domain=(-1, 1),
dtypesIfCPU=floating_types(),
dtypesIfCUDA=floating_types_and(torch.half, torch.bfloat16),
dtypes=all_types_and(torch.bool),
dtypesIfCPU=all_types_and(torch.bool),
dtypesIfCUDA=all_types_and(torch.bool, torch.half, torch.bfloat16),
promotes_integers_to_float=True,
decorators=(precisionOverride({torch.bfloat16: 1e-2}),),
test_inplace_grad=False),
UnaryUfuncInfo('cos',
Expand Down Expand Up @@ -395,7 +397,10 @@ def sample_inputs(self, device, dtype, requires_grad=False):
UnaryUfuncInfo('tanh',
ref=np.tanh,
decorators=(precisionOverride({torch.bfloat16: 1e-2}),),
dtypesIfCUDA=floating_and_complex_types_and(torch.half, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool),
dtypesIfCPU=all_types_and_complex_and(torch.bool, torch.bfloat16),
dtypesIfCUDA=all_types_and_complex_and(torch.bool, torch.half, torch.bfloat16),
promotes_integers_to_float=True,
skips=(
SkipInfo('TestUnaryUfuncs', 'test_reference_numerics',
device_type='cuda', dtypes=[torch.cfloat, torch.cdouble]),
Expand Down