120 lines
5.9 KiB
C
120 lines
5.9 KiB
C
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#pragma once
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#include <ATen/core/TensorBase.h>
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#include <ATen/native/DispatchStub.h>
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#include <c10/core/Scalar.h>
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#include <c10/util/TypeSafeSignMath.h>
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namespace at {
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struct TensorIterator;
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struct TensorIteratorBase;
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}
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namespace at::native {
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inline void alpha_check(const ScalarType dtype, const Scalar& alpha) {
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TORCH_CHECK(! alpha.isBoolean() || dtype == ScalarType::Bool,
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"Boolean alpha only supported for Boolean results.");
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TORCH_CHECK(isFloatingType(dtype) || isComplexType(dtype)
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|| alpha.isIntegral(true),
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"For integral input tensors, argument alpha must not be a floating point number.");
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TORCH_CHECK(isComplexType(dtype) || !alpha.isComplex(),
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"For non-complex input tensors, argument alpha must not be a complex number.")
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}
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// Basic checking for all sub functions.
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inline void sub_check(const TensorBase& self, const TensorBase& other) {
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TORCH_CHECK(self.scalar_type() != kBool || other.scalar_type() != kBool,
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"Subtraction, the `-` operator, with two bool tensors is not supported. "
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"Use the `^` or `logical_xor()` operator instead.")
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TORCH_CHECK(self.scalar_type() != kBool && other.scalar_type() != kBool,
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"Subtraction, the `-` operator, with a bool tensor is not supported. "
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"If you are trying to invert a mask, use the `~` or `logical_not()` operator instead.");
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}
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inline void sub_check(const TensorBase& self, const Scalar& scalar) {
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TORCH_CHECK(self.scalar_type() != kBool || !scalar.isBoolean(),
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"Subtraction, the `-` operator, with two bool tensors is not supported. "
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"Use the `^` or `logical_xor()` operator instead.")
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TORCH_CHECK(self.scalar_type() != kBool && !scalar.isBoolean(),
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"Subtraction, the `-` operator, with a bool tensor is not supported. "
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"If you are trying to invert a mask, use the `~` or `logical_not()` operator instead.");
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}
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using structured_binary_fn_alpha = void(*)(TensorIteratorBase&, const Scalar& alpha);
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using structured_binary_fn_double = void(*)(TensorIteratorBase&, double);
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using structured_binary_fn = void(*)(TensorIteratorBase&);
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using binary_fn_alpha = void(*)(TensorIteratorBase&, const Scalar& alpha);
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using binary_fn_double = void(*)(TensorIterator&, double);
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using binary_fn = void(*)(TensorIterator&);
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using binary_clamp_fn_alpha =
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void(*)(TensorIterator&, const Scalar& alpha, const Scalar& min_val, const Scalar& max_val);
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// NB: codegenned
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DECLARE_DISPATCH(structured_binary_fn_alpha, add_stub);
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DECLARE_DISPATCH(binary_clamp_fn_alpha, add_clamp_stub);
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DECLARE_DISPATCH(structured_binary_fn_alpha, sub_stub);
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DECLARE_DISPATCH(structured_binary_fn, mul_stub);
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DECLARE_DISPATCH(structured_binary_fn, div_true_stub);
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DECLARE_DISPATCH(structured_binary_fn, div_floor_stub);
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DECLARE_DISPATCH(structured_binary_fn, div_trunc_stub);
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DECLARE_DISPATCH(structured_binary_fn, atan2_stub);
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DECLARE_DISPATCH(structured_binary_fn, remainder_stub);
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DECLARE_DISPATCH(structured_binary_fn, bitwise_and_stub);
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DECLARE_DISPATCH(structured_binary_fn, bitwise_or_stub);
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DECLARE_DISPATCH(structured_binary_fn, bitwise_xor_stub);
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DECLARE_DISPATCH(structured_binary_fn, lshift_stub);
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DECLARE_DISPATCH(structured_binary_fn, rshift_stub);
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DECLARE_DISPATCH(binary_fn, logical_xor_stub);
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DECLARE_DISPATCH(binary_fn, logical_and_stub);
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DECLARE_DISPATCH(binary_fn, logical_or_stub);
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DECLARE_DISPATCH(structured_binary_fn, lt_stub);
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DECLARE_DISPATCH(structured_binary_fn, le_stub);
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DECLARE_DISPATCH(structured_binary_fn, gt_stub);
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DECLARE_DISPATCH(structured_binary_fn, ge_stub);
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DECLARE_DISPATCH(structured_binary_fn, eq_stub);
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DECLARE_DISPATCH(structured_binary_fn, ne_stub);
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DECLARE_DISPATCH(binary_fn, max_elementwise_stub);
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DECLARE_DISPATCH(binary_fn, min_elementwise_stub);
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DECLARE_DISPATCH(structured_binary_fn, maximum_stub);
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DECLARE_DISPATCH(structured_binary_fn, minimum_stub);
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DECLARE_DISPATCH(structured_binary_fn, fmax_stub);
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DECLARE_DISPATCH(structured_binary_fn, fmin_stub);
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DECLARE_DISPATCH(structured_binary_fn_double, smooth_l1_stub);
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DECLARE_DISPATCH(binary_fn_double, huber_stub);
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DECLARE_DISPATCH(structured_binary_fn, sigmoid_backward_stub);
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DECLARE_DISPATCH(binary_fn_alpha, logit_backward_stub);
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DECLARE_DISPATCH(structured_binary_fn, tanh_backward_stub);
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DECLARE_DISPATCH(structured_binary_fn, mse_stub);
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DECLARE_DISPATCH(structured_binary_fn, fmod_stub);
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DECLARE_DISPATCH(structured_binary_fn, logaddexp_stub);
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DECLARE_DISPATCH(structured_binary_fn, logaddexp2_stub);
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DECLARE_DISPATCH(structured_binary_fn, gcd_stub);
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DECLARE_DISPATCH(structured_binary_fn, lcm_stub);
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DECLARE_DISPATCH(structured_binary_fn, hypot_stub);
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DECLARE_DISPATCH(structured_binary_fn, igamma_stub);
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DECLARE_DISPATCH(structured_binary_fn, igammac_stub);
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DECLARE_DISPATCH(structured_binary_fn, nextafter_stub);
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DECLARE_DISPATCH(structured_binary_fn, heaviside_stub);
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DECLARE_DISPATCH(structured_binary_fn, copysign_stub);
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DECLARE_DISPATCH(structured_binary_fn, xlogy_stub);
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DECLARE_DISPATCH(structured_binary_fn, xlog1py_stub);
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DECLARE_DISPATCH(structured_binary_fn, zeta_stub);
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DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_t_stub);
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DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_u_stub);
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DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_v_stub);
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DECLARE_DISPATCH(structured_binary_fn, chebyshev_polynomial_w_stub);
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DECLARE_DISPATCH(structured_binary_fn, hermite_polynomial_h_stub);
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DECLARE_DISPATCH(structured_binary_fn, hermite_polynomial_he_stub);
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DECLARE_DISPATCH(structured_binary_fn, laguerre_polynomial_l_stub);
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DECLARE_DISPATCH(structured_binary_fn, legendre_polynomial_p_stub);
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DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_t_stub);
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DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_u_stub);
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DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_v_stub);
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DECLARE_DISPATCH(structured_binary_fn, shifted_chebyshev_polynomial_w_stub);
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} // namespace at::native
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