| /external/arm-optimized-routines/math/aarch64/experimental/ |
| D | log1p_2u.c | 34 /* log1p approximation using polynomial on reduced interval. Largest 38 log1p(-0x1.2e1aea97b3e5cp-2) got -0x1.65fb8659a2f9p-2 41 log1p (double x) in log1p() function 53 /* x == -0 => log1p(x) = -0. in log1p() 54 x == Inf => log1p(x) = Inf. */ in log1p() 59 /* x == -1 => log1p(x) = -Inf. */ in log1p() 65 /* x == +/-NaN => log1p(x) = NaN. */ in log1p() 68 /* x < -1 => log1p(x) = NaN. in log1p() 69 x == -Inf => log1p(x) = NaN. */ in log1p() 75 log1p(x) = k*log(2) + log1p(f). in log1p() [all …]
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| /external/cronet/tot/third_party/llvm-libc/src/test/src/math/smoke/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 19 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 20 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 21 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 22 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 23 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 24 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 25 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 29 LIBC_NAMESPACE::log1p(0x1.9b536cac3a09dp1023)); in TEST_F() [all …]
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| /external/cronet/stable/third_party/llvm-libc/src/test/src/math/smoke/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 19 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 20 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 21 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 22 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 23 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 24 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 25 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 29 LIBC_NAMESPACE::log1p(0x1.9b536cac3a09dp1023)); in TEST_F() [all …]
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| /external/llvm-libc/test/src/math/smoke/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 19 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 20 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 21 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 22 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 23 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 24 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 25 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 29 LIBC_NAMESPACE::log1p(0x1.9b536cac3a09dp1023)); in TEST_F() [all …]
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| /external/python/cpython3/Lib/test/mathdata/ |
| D | math_testcases.txt | 374 -- log1p: log(1 + x), without precision loss for small x -- 378 log1p0000 log1p 0.0 -> 0.0 379 log1p0001 log1p -0.0 -> -0.0 380 log1p0002 log1p inf -> inf 381 log1p0003 log1p -inf -> nan invalid 382 log1p0004 log1p nan -> nan 385 log1p0010 log1p -1.0 -> -inf divide-by-zero 386 log1p0011 log1p -0.9999999999999999 -> -36.736800569677101 389 log1p0020 log1p -1.0000000000000002 -> nan invalid 390 log1p0021 log1p -1.1 -> nan invalid [all …]
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| /external/arm-optimized-routines/math/test/testcases/directed/ |
| D | log1p.tst | 1 ; log1p.tst 6 func=log1p op1=7ff80000.00000001 result=7ff80000.00000001 errno=0 7 func=log1p op1=fff80000.00000001 result=7ff80000.00000001 errno=0 8 func=log1p op1=7ff00000.00000001 result=7ff80000.00000001 errno=0 status=i 9 func=log1p op1=fff00000.00000001 result=7ff80000.00000001 errno=0 status=i 10 func=log1p op1=fff02000.00000000 result=7ff80000.00000001 errno=0 status=i 11 func=log1p op1=7ff00000.00000000 result=7ff00000.00000000 errno=0 15 func=log1p op1=00000000.00000000 result=00000000.00000000 errno=0 16 func=log1p op1=80000000.00000000 result=80000000.00000000 errno=0 21 func=log1p op1=00000000.00000001 result=00000000.00000001 errno=0 maybestatus=ux [all …]
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| /external/arm-optimized-routines/math/aarch64/advsimd/ |
| D | log1p.c | 31 return v_call_f64 (log1p, x, log1p_inline (x_nospecial, &d->d), cmp); in special_case() 34 /* Vector log1p approximation using polynomial on reduced interval. Routine is 35 a modification of the algorithm used in scalar log1p, with no shortcut for 39 VPCS_ATTR float64x2_t V_NAME_D1 (log1p) (float64x2_t x) in V_NAME_D1() argument 54 TEST_SIG (V, D, 1, log1p, -0.9, 10.0) 55 TEST_ULP (V_NAME_D1 (log1p), 1.95) 56 TEST_DISABLE_FENV_IF_NOT (V_NAME_D1 (log1p), WANT_SIMD_EXCEPT) 57 TEST_SYM_INTERVAL (V_NAME_D1 (log1p), 0.0, 0x1p-23, 50000) 58 TEST_SYM_INTERVAL (V_NAME_D1 (log1p), 0x1p-23, 0.001, 50000) 59 TEST_SYM_INTERVAL (V_NAME_D1 (log1p), 0.001, 1.0, 50000) [all …]
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| D | log1pf.c | 41 float32x4_t VPCS_ATTR NOINLINE V_NAME_F1 (log1p) (float32x4_t x) in V_NAME_F1() argument 71 float32x4_t VPCS_ATTR NOINLINE V_NAME_F1 (log1p) (float32x4_t x) in V_NAME_F1() argument 84 HALF_WIDTH_ALIAS_F1 (log1p) 86 TEST_SIG (V, F, 1, log1p, -0.9, 10.0) 87 TEST_ULP (V_NAME_F1 (log1p), 1.20) 88 TEST_DISABLE_FENV_IF_NOT (V_NAME_F1 (log1p), WANT_SIMD_EXCEPT) 89 TEST_SYM_INTERVAL (V_NAME_F1 (log1p), 0.0, 0x1p-23, 30000) 90 TEST_SYM_INTERVAL (V_NAME_F1 (log1p), 0x1p-23, 1, 50000) 91 TEST_INTERVAL (V_NAME_F1 (log1p), 1, inf, 50000) 92 TEST_INTERVAL (V_NAME_F1 (log1p), -1.0, -inf, 1000)
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| /external/arm-optimized-routines/math/aarch64/sve/ |
| D | log1p.c | 44 return sv_call_f64 (log1p, x, y, special); in special_case() 47 /* Vector approximation for log1p using polynomial on reduced interval. Maximum 51 svfloat64_t SV_NAME_D1 (log1p) (svfloat64_t x, svbool_t pg) in SV_NAME_D1() argument 61 log1p(x) = k*log(2) + log1p(f). in SV_NAME_D1() 65 c << m: at very small x, log1p(x) ~ x, hence: in SV_NAME_D1() 68 We therefore calculate log1p(x) by k*log2 + log1p(f) + c/m. */ in SV_NAME_D1() 90 /* Approximate log1p(x) on the reduced input using a polynomial. Because in SV_NAME_D1() 91 log1p(0)=0 we choose an approximation of the form: in SV_NAME_D1() 110 TEST_SIG (SV, D, 1, log1p, -0.9, 10.0) 111 TEST_ULP (SV_NAME_D1 (log1p), 1.97) [all …]
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| D | log1pf.c | 24 svfloat32_t SV_NAME_F1 (log1p) (svfloat32_t x, svbool_t pg) in SV_NAME_F1() argument 36 TEST_SIG (SV, F, 1, log1p, -0.9, 10.0) 37 TEST_ULP (SV_NAME_F1 (log1p), 0.77) 38 TEST_DISABLE_FENV (SV_NAME_F1 (log1p)) 39 TEST_SYM_INTERVAL (SV_NAME_F1 (log1p), 0, 0x1p-23, 5000) 40 TEST_SYM_INTERVAL (SV_NAME_F1 (log1p), 0x1p-23, 1, 5000) 41 TEST_INTERVAL (SV_NAME_F1 (log1p), 1, inf, 10000) 42 TEST_INTERVAL (SV_NAME_F1 (log1p), -1, -inf, 10)
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| /external/cronet/tot/third_party/llvm-libc/src/test/src/math/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 25 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 26 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 27 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 28 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 29 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 30 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 31 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 71 EXPECT_MPFR_MATCH_ALL_ROUNDING(mpfr::Operation::Log1p, x, in TEST_F() [all …]
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| /external/cronet/stable/third_party/llvm-libc/src/test/src/math/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 25 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 26 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 27 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 28 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 29 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 30 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 31 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 71 EXPECT_MPFR_MATCH_ALL_ROUNDING(mpfr::Operation::Log1p, x, in TEST_F() [all …]
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| /external/llvm-libc/test/src/math/ |
| D | log1p_test.cpp | 1 //===-- Unittests for log1p -----------------------------------------------===// 12 #include "src/math/log1p.h" 25 EXPECT_FP_EQ(aNaN, LIBC_NAMESPACE::log1p(aNaN)); in TEST_F() 26 EXPECT_FP_EQ(inf, LIBC_NAMESPACE::log1p(inf)); in TEST_F() 27 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(neg_inf), FE_INVALID); in TEST_F() 28 EXPECT_FP_IS_NAN_WITH_EXCEPTION(LIBC_NAMESPACE::log1p(-2.0), FE_INVALID); in TEST_F() 29 EXPECT_FP_EQ(zero, LIBC_NAMESPACE::log1p(0.0)); in TEST_F() 30 EXPECT_FP_EQ(neg_zero, LIBC_NAMESPACE::log1p(-0.0)); in TEST_F() 31 EXPECT_FP_EQ_WITH_EXCEPTION(neg_inf, LIBC_NAMESPACE::log1p(-1.0), in TEST_F() 71 EXPECT_MPFR_MATCH_ALL_ROUNDING(mpfr::Operation::Log1p, x, in TEST_F() [all …]
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| /external/tensorflow/tensorflow/compiler/mlir/tfrt/python_tests/ |
| D | tf_log1p_test.py | 15 """Tests for tf.Log1p JIT compilation.""" 31 func.func @log1p(%arg0: tensor<?xf32>) -> tensor<?xf32> { 32 %0 = "tf.Log1p"(%arg0): (tensor<?xf32>) -> tensor<?xf32> 39 func.func @log1p(%arg0: tensor<?x?xf32>) -> tensor<?x?xf32> { 40 %0 = "tf.Log1p"(%arg0): (tensor<?x?xf32>) -> tensor<?x?xf32> 50 compiled = jitrt.compile(fn(), "log1p", specialize) 57 np.testing.assert_allclose(res, np.log1p(arg), atol=1e-06)
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| /external/python/cpython3/Modules/ |
| D | _math.h | 1 /* log1p(x) = log(1+x). The log1p function is designed to avoid the 10 /* Some platforms (e.g. MacOS X 10.8, see gh-59682) supply a log1p function in _Py_log1p() 11 but don't respect the sign of zero: log1p(-0.0) gives 0.0 instead of in _Py_log1p() 21 return log1p(x); in _Py_log1p()
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| /external/trusty/musl/src/math/ |
| D | log1p.c | 12 /* double log1p(double x) 29 * 3. Finally, log1p(x) = k*ln2 + log(1+f) + c/u. See log.c 32 * log1p(x) is NaN with signal if x < -1 (including -INF) ; 33 * log1p(+INF) is +INF; log1p(-1) is -INF with signal; 34 * log1p(NaN) is that NaN with no signal. 47 * algorithm can be used to compute log1p(x) to within a few ULP: 69 double log1p(double x) in log1p() function 81 return x/0.0; /* log1p(-1) = -inf */ in log1p() 82 return (x-x)/0.0; /* log1p(x<-1) = NaN */ in log1p()
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| /external/musl/src/math/ |
| D | log1p.c | 12 /* double log1p(double x) 29 * 3. Finally, log1p(x) = k*ln2 + log(1+f) + c/u. See log.c 32 * log1p(x) is NaN with signal if x < -1 (including -INF) ; 33 * log1p(+INF) is +INF; log1p(-1) is -INF with signal; 34 * log1p(NaN) is that NaN with no signal. 47 * algorithm can be used to compute log1p(x) to within a few ULP: 69 double log1p(double x) in log1p() function 81 return x/0.0; /* log1p(-1) = -inf */ in log1p() 82 return (x-x)/0.0; /* log1p(x<-1) = NaN */ in log1p()
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| /external/rust/android-crates-io/crates/libm/src/math/ |
| D | log1p.rs | 12 /* double log1p(double x) 29 * 3. Finally, log1p(x) = k*ln2 + log(1+f) + c/u. See log.c 32 * log1p(x) is NaN with signal if x < -1 (including -INF) ; 33 * log1p(+INF) is +INF; log1p(-1) is -INF with signal; 34 * log1p(NaN) is that NaN with no signal. 47 * algorithm can be used to compute log1p(x) to within a few ULP: 70 pub fn log1p(x: f64) -> f64 { in log1p() function 93 return x / 0.0; /* log1p(-1) = -inf */ in log1p() 95 return (x - x) / 0.0; /* log1p(x<-1) = NaN */ in log1p()
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| D | atanh.rs | 1 use super::log1p; 3 /* atanh(x) = log((1+x)/(1-x))/2 = log1p(2x/(1-x))/2 ~= x + x^3/3 + o(x^5) */ 7 /// Is defined as `log((1+x)/(1-x))/2 = log1p(2x/(1-x))/2`. 25 y = 0.5 * log1p(2.0 * y + 2.0 * y * y / (1.0 - y)); in atanh() 29 y = 0.5 * log1p(2.0 * (y / (1.0 - y))); in atanh()
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| /external/tensorflow/tensorflow/core/api_def/python_api/ |
| D | api_def_Log1p.pbtxt | 2 graph_op_name: "Log1p" 4 name: "math.log1p" 7 name: "log1p" 15 >>> tf.math.log1p(x)
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| /external/tensorflow/tensorflow/compiler/mlir/tfrt/benchmarks/ |
| D | cwise_op_log1p_benchmark.cc | 24 %0 = "tf.Log1p"(%arg0): (tensor<?xf32>) -> tensor<?xf32> 29 #define EXPR_BUILDER [](auto& in) { return in.log1p(); } 31 BM_TFMlir(Log1p, mlir_input, "log1p_1d", 1, f32, 1.0, 0.0, /* num_threads */ 0) 37 BM_EigenScalar(Log1p, EXPR_BUILDER, 1, f32, 1.0, 0.0, /* num_threads */ 0) 43 BM_EigenVectorized(Log1p, EXPR_BUILDER, 1, f32, 1.0, 0.0, /* num_threads */ 0)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | cwise_op_log1p.cc | 19 REGISTER6(UnaryOp, CPU, "Log1p", functor::log1p, float, Eigen::half, bfloat16, 24 REGISTER3(UnaryOp, GPU, "Log1p", functor::log1p, float, Eigen::half, double);
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| /external/pytorch/torch/distributions/ |
| D | continuous_bernoulli.py | 119 torch.abs(torch.log1p(-cut_probs) - torch.log(cut_probs)) 122 torch.log1p(-2.0 * cut_probs_below_half), 133 torch.log1p(-cut_probs) - torch.log(cut_probs) 148 ) + 1.0 / torch.pow(torch.log1p(-cut_probs) - torch.log(cut_probs), 2) 206 torch.log1p(-cut_probs + value * (2.0 * cut_probs - 1.0)) 207 - torch.log1p(-cut_probs) 209 / (torch.log(cut_probs) - torch.log1p(-cut_probs)), 214 log_probs0 = torch.log1p(-self.probs)
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| /external/trusty/musl/src/math/i386/ |
| D | log1p.s | 1 .global log1p symbol 2 .type log1p,@function 3 log1p: label
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| /external/musl/src/math/i386/ |
| D | log1p.s | 1 .global log1p symbol 2 .type log1p,@function 3 log1p: label
|