| /external/tensorflow/tensorflow/core/kernels/ |
| cwise_op_gpu_igammas_double.cu.cc | 25 DEFINE_BINARY1(igammac, double);
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| cwise_op_gpu_igammas_float.cu.cc | 25 DEFINE_BINARY1(igammac, float);
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| cwise_op_igammas.cc | 22 REGISTER2(BinaryOp, CPU, "Igammac", functor::igammac, float, double);
26 REGISTER2(BinaryOp, GPU, "Igammac", functor::igammac, float, double);
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| cwise_ops.h | 971 struct igammac : base<T, Eigen::internal::scalar_igammac_op<T>> {}; struct in namespace:tensorflow::functor
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| /external/eigen/unsupported/Eigen/src/SpecialFunctions/ |
| SpecialFunctionsPacketMath.h | 45 /** \internal \returns the complementary incomplete gamma function igammac(\a a, \a x) */
47 Packet pigammac(const Packet& a, const Packet& x) { using numext::igammac; return igammac(a, x); }
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| SpecialFunctionsHalf.h | 36 template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half igammac(const Eigen::half& a, const Eigen::half& x) { function in namespace:Eigen::numext
37 return Eigen::half(Eigen::numext::igammac(static_cast<float>(a), static_cast<float>(x)));
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| SpecialFunctionsArrayAPI.h | 21 * or float/double in non c++11 mode, the user has to provide implementations of igammac(T,T) for any scalar
24 * \sa Eigen::igammac(), Eigen::lgamma()
36 /** \cpp11 \returns an expression of the coefficient-wise igammac(\a a, \a x) to the given arrays.
41 * or float/double in non c++11 mode, the user has to provide implementations of igammac(T,T) for any scalar
48 igammac(const Eigen::ArrayBase<Derived>& a, const Eigen::ArrayBase<ExponentDerived>& x) function in namespace:Eigen
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| SpecialFunctionsFunctors.h | 46 * \brief Template functor to compute the complementary incomplete gamma function igammac(a, x)
48 * \sa class CwiseBinaryOp, Cwise::igammac
54 using numext::igammac; return igammac(a, x);
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| SpecialFunctionsImpl.h | 401 * Implementation of igammac (complemented incomplete gamma integral), based on Cephes but requires C++11/C99 *
1550 igammac(const Scalar& a, const Scalar& x) { function in namespace:Eigen::numext
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| /external/eigen/unsupported/Eigen/src/SpecialFunctions/arch/CUDA/ |
| CudaSpecialFunctions.h | 126 using numext::igammac;
128 igammac(a.x, x.x),
129 igammac(a.y, x.y),
130 igammac(a.z, x.z),
131 igammac(a.w, x.w));
137 using numext::igammac;
138 return make_double2(igammac(a.x, x.x), igammac(a.y, x.y));
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| /external/eigen/unsupported/test/ |
| special_functions.cpp | 61 // Test various propreties of igamma & igammac. These are normalized
63 // igammac(a, x) = Gamma(a, x) / Gamma(a)
72 ArrayType Gamma_a_x = Eigen::igammac(a, x) * a.lgamma().exp();
73 ArrayType Gamma_a_m1_x = Eigen::igammac(a_m1, x) * a_m1.lgamma().exp();
78 VERIFY_IS_APPROX(Eigen::igammac(a, zero), one);
91 // Check exact values of igamma and igammac against a third party calculation.
126 VERIFY((std::isnan)(numext::igammac(a_s[i], x_s[j])));
128 VERIFY_IS_APPROX(numext::igammac(a_s[i], x_s[j]), igammac_s[i][j]);
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| /external/tensorflow/tensorflow/contrib/labeled_tensor/ |
| __init__.py | 99 igammac = _core.igammac variable
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| poisson.py | 168 return math_ops.igammac(1. + x, self.rate)
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| inverse_gamma.py | 208 # Note that igammac returns the upper regularized incomplete gamma
210 return math_ops.igammac(self.concentration, self.rate / x)
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| /external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
| core.py | 1198 igammac = define_binary_op('igammac', math_ops.igammac) variable
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| core_test.py | 844 ('igammac', None, math_ops.igammac, core.igammac),
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| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/optimization/ |
| map_vectorization_test.py | 161 ("Igammac", math_ops.igammac),
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| math_test.py | 168 math_ops.igammac,
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| pfor.py | [all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| cwise_ops_binary_test.py | 227 math_ops.igammac)
295 math_ops.igammac)
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| /external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
| TensorBase.h | 143 // igammac(a = this, x = other)
146 igammac(const OtherDerived& other) const { function in class:Eigen::TensorBase
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