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namespace at { | |
struct TensorIterator; | |
struct TensorIteratorBase; | |
} | |
namespace at::native { | |
inline void alpha_check(const ScalarType dtype, const Scalar& alpha) { | |
TORCH_CHECK(! alpha.isBoolean() || dtype == ScalarType::Bool, | |
"Boolean alpha only supported for Boolean results."); | |
TORCH_CHECK(isFloatingType(dtype) || isComplexType(dtype) | |
|| alpha.isIntegral(true), | |
"For integral input tensors, argument alpha must not be a floating point number."); | |
TORCH_CHECK(isComplexType(dtype) || !alpha.isComplex(), | |
"For non-complex input tensors, argument alpha must not be a complex number.") | |
} | |
// Basic checking for all sub functions. | |
inline void sub_check(const TensorBase& self, const TensorBase& other) { | |
TORCH_CHECK(self.scalar_type() != kBool || other.scalar_type() != kBool, | |
"Subtraction, the `-` operator, with two bool tensors is not supported. " | |
"Use the `^` or `logical_xor()` operator instead.") | |
TORCH_CHECK(self.scalar_type() != kBool && other.scalar_type() != kBool, | |
"Subtraction, the `-` operator, with a bool tensor is not supported. " | |
"If you are trying to invert a mask, use the `~` or `logical_not()` operator instead."); | |
} | |
inline void sub_check(const TensorBase& self, const Scalar& scalar) { | |
TORCH_CHECK(self.scalar_type() != kBool || !scalar.isBoolean(), | |
"Subtraction, the `-` operator, with two bool tensors is not supported. " | |
"Use the `^` or `logical_xor()` operator instead.") | |
TORCH_CHECK(self.scalar_type() != kBool && !scalar.isBoolean(), | |
"Subtraction, the `-` operator, with a bool tensor is not supported. " | |
"If you are trying to invert a mask, use the `~` or `logical_not()` operator instead."); | |
} | |
using structured_binary_fn_alpha = void(*)(TensorIteratorBase&, const Scalar& alpha); | |
using structured_binary_fn_double = void(*)(TensorIteratorBase&, double); | |
using structured_binary_fn = void(*)(TensorIteratorBase&); | |
using binary_fn_alpha = void(*)(TensorIteratorBase&, const Scalar& alpha); | |
using binary_fn_double = void(*)(TensorIterator&, double); | |
using binary_fn = void(*)(TensorIterator&); | |
using binary_clamp_fn_alpha = | |
void(*)(TensorIterator&, const Scalar& alpha, const Scalar& min_val, const Scalar& max_val); | |
// NB: codegenned | |
DECLARE_DISPATCH(structured_binary_fn_alpha, add_stub); | |
DECLARE_DISPATCH(binary_clamp_fn_alpha, add_clamp_stub); | |
DECLARE_DISPATCH(structured_binary_fn_alpha, sub_stub); | |
DECLARE_DISPATCH(structured_binary_fn, mul_stub); | |
DECLARE_DISPATCH(structured_binary_fn, div_true_stub); | |
DECLARE_DISPATCH(structured_binary_fn, div_floor_stub); | |
DECLARE_DISPATCH(structured_binary_fn, div_trunc_stub); | |
DECLARE_DISPATCH(structured_binary_fn, atan2_stub); | |
DECLARE_DISPATCH(structured_binary_fn, remainder_stub); | |
DECLARE_DISPATCH(structured_binary_fn, bitwise_and_stub); | |
DECLARE_DISPATCH(structured_binary_fn, bitwise_or_stub); | |
DECLARE_DISPATCH(structured_binary_fn, bitwise_xor_stub); | |
DECLARE_DISPATCH(structured_binary_fn, lshift_stub); | |
DECLARE_DISPATCH(structured_binary_fn, rshift_stub); | |
DECLARE_DISPATCH(binary_fn, logical_xor_stub); | |
DECLARE_DISPATCH(binary_fn, logical_and_stub); | |
DECLARE_DISPATCH(binary_fn, logical_or_stub); | |
DECLARE_DISPATCH(structured_binary_fn, lt_stub); | |
DECLARE_DISPATCH(structured_binary_fn, le_stub); | |
DECLARE_DISPATCH(structured_binary_fn, gt_stub); | |
DECLARE_DISPATCH(structured_binary_fn, ge_stub); | |
DECLARE_DISPATCH(structured_binary_fn, eq_stub); | |
DECLARE_DISPATCH(structured_binary_fn, ne_stub); | |
DECLARE_DISPATCH(binary_fn, max_elementwise_stub); | |
DECLARE_DISPATCH(binary_fn, min_elementwise_stub); | |
DECLARE_DISPATCH(structured_binary_fn, maximum_stub); | |
DECLARE_DISPATCH(structured_binary_fn, minimum_stub); | |
DECLARE_DISPATCH(structured_binary_fn, fmax_stub); | |
DECLARE_DISPATCH(structured_binary_fn, fmin_stub); | |
DECLARE_DISPATCH(structured_binary_fn_double, smooth_l1_stub); | |
DECLARE_DISPATCH(binary_fn_double, huber_stub); | |
DECLARE_DISPATCH(structured_binary_fn, sigmoid_backward_stub); | |
DECLARE_DISPATCH(binary_fn_alpha, logit_backward_stub); | |
DECLARE_DISPATCH(structured_binary_fn, tanh_backward_stub); | |
DECLARE_DISPATCH(structured_binary_fn, mse_stub); | |
DECLARE_DISPATCH(structured_binary_fn, fmod_stub); | |
DECLARE_DISPATCH(structured_binary_fn, logaddexp_stub); | |
DECLARE_DISPATCH(structured_binary_fn, logaddexp2_stub); | |
DECLARE_DISPATCH(structured_binary_fn, gcd_stub); | |
DECLARE_DISPATCH(structured_binary_fn, lcm_stub); | |
DECLARE_DISPATCH(structured_binary_fn, hypot_stub); | |
DECLARE_DISPATCH(structured_binary_fn, igamma_stub); | |
DECLARE_DISPATCH(structured_binary_fn, igammac_stub); | |
DECLARE_DISPATCH(structured_binary_fn, nextafter_stub); | |
DECLARE_DISPATCH(structured_binary_fn, heaviside_stub); | |
DECLARE_DISPATCH(structured_binary_fn, copysign_stub); | |
DECLARE_DISPATCH(structured_binary_fn, xlogy_stub); | |
DECLARE_DISPATCH(structured_binary_fn, xlog1py_stub); | |
DECLARE_DISPATCH(structured_binary_fn, zeta_stub); | |
DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_t_stub); | |
DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_u_stub); | |
DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_v_stub); | |
DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_w_stub); | |
DECLARE_DISPATCH(structured_binary_fn, hermite_polynomial_h_stub); | |
DECLARE_DISPATCH(structured_binary_fn, hermite_polynomial_he_stub); | |
DECLARE_DISPATCH(structured_binary_fn, laguerre_polynomial_l_stub); | |
DECLARE_DISPATCH(structured_binary_fn, legendre_polynomial_p_stub); | |
DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_t_stub); | |
DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_u_stub); | |
DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_v_stub); | |
DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_w_stub); | |
} // namespace at::native | |