| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | rmsprop.py | 65 rho=0.9, argument
111 self._set_hyper("rho", rho)
137 rho = self._get_hyper("rho", var_dtype)
150 rho,
161 rho,
167 rms_t = rho * rms + (1. - rho) * math_ops.square(grad)
172 mg_t = rho * mg + (1. - rho) * grad
182 rho = self._get_hyper("rho", var_dtype)
195 rho,
207 rho,
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| D | rmsprop_test.py | 60 def _rmsprop_update_numpy(self, var, g, mg, rms, mom, lr, rho, momentum, argument
62 rms_t = rms * rho + (1 - rho) * g * g
64 mg_t = mg * rho + (1 - rho) * g
78 lr, rho, momentum, epsilon, centered): argument
86 rms_t[gindex] = rms[gindex] * rho + (1 - rho) * gvalue * gvalue
88 mg_t[gindex] = mg_t[gindex] * rho + (1 - rho) * gvalue
103 for (dtype, learning_rate, rho, momentum, epsilon, centered) in _TESTPARAMS:
117 rho=rho,
160 var0_np, grads0_np, mg0_np, rms0_np, mom0_np, learning_rate, rho,
163 var1_np, grads1_np, mg1_np, rms1_np, mom1_np, learning_rate, rho,
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| D | adadelta_test.py | 59 rho = 0.95
64 rho=lambda: rho, # pylint: disable=cell-var-from-loop
68 learning_rate=lr, rho=rho, epsilon=epsilon)
103 accum = accum * rho + (grad**2) * (1 - rho)
108 accum_update * rho + (update[step]**2) * (1.0 - rho))
172 opt = adadelta.Adadelta(lr=1.0, rho=0.9, epsilon=1.)
173 opt_2 = adadelta.Adadelta(learning_rate=0.1, rho=0.9, epsilon=1., lr=1.0)
174 opt_3 = adadelta.Adadelta(learning_rate=0.1, rho=0.9, epsilon=1.)
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| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| D | ConstrainedConjGrad.h | 58 Scalar rho, rho_1, alpha; in pseudo_inverse() local
67 rho = 1.0; in pseudo_inverse()
72 while (rho >= 1e-38) in pseudo_inverse()
77 alpha = rho / p.dot(q); in pseudo_inverse()
80 rho_1 = rho; in pseudo_inverse()
81 rho = r.dot(r); in pseudo_inverse()
82 p = (rho/rho_1) * p + r; in pseudo_inverse()
114 Scalar rho = 1.0, rho_1, lambda, gamma; in constrained_cg() local
157 rho_1 = rho; in constrained_cg()
158 rho = r.dot(z); in constrained_cg()
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| /external/tensorflow/tensorflow/python/training/ |
| D | adadelta_test.py | 59 rho = 0.95
64 rho=lambda: rho, # pylint: disable=cell-var-from-loop
68 learning_rate=lr, rho=rho, epsilon=epsilon)
118 accum = accum * rho + (grad**2) * (1 - rho)
123 accum_update * rho + (update[step]**2) * (1.0 - rho))
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| D | adadelta.py | 36 def __init__(self, learning_rate=0.001, rho=0.95, epsilon=1e-8, argument
59 self._rho = rho
74 rho = self._call_if_callable(self._rho)
78 self._rho_t = ops.convert_to_tensor(rho, name="rho")
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| /external/mesa3d/src/gallium/auxiliary/gallivm/ |
| D | lp_bld_sample.c | 232 LLVMValueRef rho; in lp_build_rho() local
264 rho = lp_build_pack_aos_scalars(bld->gallivm, coord_bld->type, in lp_build_rho()
268 rho = lp_build_swizzle_scalar_aos(coord_bld, cube_rho, 0, 4); in lp_build_rho()
275 rho = lp_build_mul(rho_bld, cubesize, rho); in lp_build_rho()
311 rho = lp_build_max(coord_bld, rho_xvec, rho_yvec); in lp_build_rho()
315 rho = ddmax[0]; in lp_build_rho()
317 rho = lp_build_max(coord_bld, rho, ddmax[1]); in lp_build_rho()
319 rho = lp_build_max(coord_bld, rho, ddmax[2]); in lp_build_rho()
327 rho = lp_build_pack_aos_scalars(bld->gallivm, coord_bld->type, in lp_build_rho()
328 rho_bld->type, rho, 0); in lp_build_rho()
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | adadelta_test.py | 60 rho = 0.95
63 learning_rate=lr, rho=rho, epsilon=epsilon)
105 accum = accum * rho + (grad**2) * (1 - rho)
110 accum_update * rho + (update[step]**2) * (1.0 - rho))
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ResourceApplyAdadelta.pbtxt | 28 name: "rho"
54 accum = rho() * accum + (1 - rho()) * grad.square();
56 update_accum = rho() * update_accum + (1 - rho()) * update.square();
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| D | api_def_ApplyAdadelta.pbtxt | 28 name: "rho"
60 accum = rho() * accum + (1 - rho()) * grad.square();
62 update_accum = rho() * update_accum + (1 - rho()) * update.square();
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| D | api_def_ApplyCenteredRMSProp.pbtxt | 34 name: "rho"
81 mg <- rho * mg_{t-1} + (1-rho) * grad
82 ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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| D | api_def_ResourceApplyCenteredRMSProp.pbtxt | 34 name: "rho"
75 mg <- rho * mg_{t-1} + (1-rho) * grad
76 ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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| D | api_def_ApplyRMSProp.pbtxt | 28 name: "rho"
68 ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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| D | api_def_ResourceApplyRMSProp.pbtxt | 28 name: "rho"
62 ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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| /external/ImageMagick/MagickCore/ |
| D | morphology.c | 272 args.rho = args.sigma; /* then width = height */ in ParseKernelArray()
273 if ( args.rho < 1.0 ) /* if width too small */ in ParseKernelArray()
274 args.rho = 1.0; /* then width = 1 */ in ParseKernelArray()
276 args.sigma = args.rho; /* then height = width */ in ParseKernelArray()
277 kernel->width = (size_t)args.rho; in ParseKernelArray()
418 flags, args.rho, args.sigma, args.xi, args.psi ); in ParseKernelName()
426 args.rho = 1.0; /* Default scale = 1.0, zero is valid */ in ParseKernelName()
443 args.rho = args.sigma; /* then width = height */ in ParseKernelName()
444 if ( args.rho < 1.0 ) /* if width too small */ in ParseKernelName()
445 args.rho = 3; /* then width = 3 */ in ParseKernelName()
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| D | geometry.c | 883 c=sscanf(geometry,"%lf%*[ ,]%lf%*[ ,]%lf%*[ ,]%lf",&coordinate.rho, in ParseGeometry()
890 geometry_info->rho=coordinate.rho; in ParseGeometry()
1019 geometry_info->rho=value; in ParseGeometry()
1129 geometry_info->rho*=PerceptibleReciprocal(geometry_info->sigma); in ParseGeometry()
1176 geometry_info->sigma=geometry_info->rho; in ParseGeometry()
1178 geometry_info->rho=geometry_info->sigma; in ParseGeometry()
1188 (void) fprintf(stderr,"Geometry: %lg,%lg,%lg,%lg,%lg\n",geometry_info->rho, in ParseGeometry()
1271 scale.x=geometry_info.rho; in ParseGravityGeometry()
1295 geometry_ratio=geometry_info.rho; in ParseGravityGeometry()
1410 scale.x=geometry_info.rho; in ParseMetaGeometry()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/direct/ |
| D | NelderMead.java | 36 private final double rho; field in NelderMead
52 this.rho = 1.0; in NelderMead()
64 public NelderMead(final double rho, final double khi, in NelderMead() argument
66 this.rho = rho; in NelderMead()
105 xR[j] = centroid[j] + rho * (centroid[j] - xWorst[j]); in iterateSimplex()
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| /external/eigen/Eigen/src/IterativeLinearSolvers/ |
| D | BiCGSTAB.h | 52 Scalar rho = 1; in bicgstab() local
69 Scalar rho_old = rho; in bicgstab()
71 rho = r0.dot(r); in bicgstab()
72 if (abs(rho) < eps2*r0_sqnorm) in bicgstab()
78 rho = r0_sqnorm = r.squaredNorm(); in bicgstab()
82 Scalar beta = (rho/rho_old) * (alpha / w); in bicgstab()
89 alpha = rho / r0.dot(v); in bicgstab()
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| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| D | adadelta_test.py | 58 rho = 0.95
60 adadelta_opt = adadelta.AdadeltaOptimizer(lr, rho, epsilon)
105 accum = accum * rho + (grad**2) * (1 - rho)
108 accum_update = (accum_update * rho + (update[step]**2) *
109 (1.0 - rho))
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| /external/libcxx/test/std/numerics/complex.number/complex.value.ops/ |
| D | polar.pass.cpp | 23 test(const T& rho, std::complex<T> x) in test() argument
25 assert(std::polar(rho) == x); in test()
30 test(const T& rho, const T& theta, std::complex<T> x) in test() argument
32 assert(std::polar(rho, theta) == x); in test()
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| /external/iproute2/netem/ |
| D | maketable.c | 51 arraystats(double *x, int limit, double *mu, double *sigma, double *rho) in arraystats() argument
70 *rho = top/sigma2; in arraystats()
202 double mu, sigma, rho; in main() local
221 arraystats(x, limit, &mu, &sigma, &rho); in main()
224 limit, mu, sigma, rho); in main()
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| D | stats.c | 24 double mu=0.0, sigma=0.0, sumsquare=0.0, sum=0.0, top=0.0, rho=0.0; in stats() local
51 rho = top/sigma2; in stats()
55 printf("rho = %12.6f\n", rho); in stats()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | training_ops_gpu.cu.cc | 62 typename TTypes<T>::ConstScalar rho, in operator ()()
69 accum.device(d) = accum * rho.reshape(single).broadcast(bcast) + in operator ()()
71 rho.reshape(single).broadcast(bcast)); in operator ()()
77 accum_update * rho.reshape(single).broadcast(bcast) + in operator ()()
79 (grad.constant(T(1)) - rho.reshape(single).broadcast(bcast)); in operator ()()
232 typename TTypes<T>::ConstScalar rho, in operator ()()
241 ms + (rho.constant(one) - rho).reshape(single).broadcast(bcast) * in operator ()()
257 typename TTypes<T>::ConstScalar rho, in operator ()()
266 (rho.constant(one) - rho).reshape(single).broadcast(bcast); in operator ()()
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| /external/eigen/bench/ |
| D | eig33.cpp | 76 Scalar rho = std::sqrt(-a_over_3); in computeRoots() local
80 roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta; in computeRoots()
81 roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta); in computeRoots()
82 roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta); in computeRoots()
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| /external/ImageMagick/MagickWand/ |
| D | operation.c | 86 flags, info.rho, info.sigma, info.xi, info.psi )
1733 new_image=AdaptiveBlurImage(_image,geometry_info.rho, in CLISimpleOperatorImage()
1754 new_image=AdaptiveSharpenImage(_image,geometry_info.rho, in CLISimpleOperatorImage()
1778 geometry_info.sigma=geometry_info.rho; in CLISimpleOperatorImage()
1784 fmod(geometry_info.rho,360.0))); in CLISimpleOperatorImage()
1786 fmod(geometry_info.rho,360.0))); in CLISimpleOperatorImage()
1833 geometry_info.rho=1.5; in CLISimpleOperatorImage()
1839 new_image=BlueShiftImage(_image,geometry_info.rho,_exception); in CLISimpleOperatorImage()
1849 new_image=BlurImage(_image,geometry_info.rho,geometry_info.sigma, in CLISimpleOperatorImage()
1887 brightness=geometry_info.rho; in CLISimpleOperatorImage()
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