| /external/eigen/unsupported/test/ |
| D | cxx11_tensor_simple.cpp | 159 Tensor<int, 3> epsilon(3,3,3); in test_3d() local
160 epsilon.setZero(); in test_3d()
161 epsilon(0,1,2) = epsilon(2,0,1) = epsilon(1,2,0) = 1; in test_3d()
162 epsilon(2,1,0) = epsilon(0,2,1) = epsilon(1,0,2) = -1; in test_3d()
164 VERIFY_IS_EQUAL((epsilon.size()), 27); in test_3d()
165 VERIFY_IS_EQUAL((epsilon.dimensions()[0]), 3); in test_3d()
166 VERIFY_IS_EQUAL((epsilon.dimensions()[1]), 3); in test_3d()
167 VERIFY_IS_EQUAL((epsilon.dimensions()[2]), 3); in test_3d()
169 VERIFY_IS_EQUAL((epsilon(0,0,0)), 0); in test_3d()
170 VERIFY_IS_EQUAL((epsilon(0,0,1)), 0); in test_3d()
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| /external/skqp/src/pathops/ |
| D | SkPathOpsTypes.cpp | 12 static bool arguments_denormalized(float a, float b, int epsilon) { in arguments_denormalized() argument
13 float denormalizedCheck = FLT_EPSILON * epsilon / 2; in arguments_denormalized()
19 static bool equal_ulps(float a, float b, int epsilon, int depsilon) { in equal_ulps() argument
26 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps()
29 static bool equal_ulps_no_normal_check(float a, float b, int epsilon, int depsilon) { in equal_ulps_no_normal_check() argument
33 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps_no_normal_check()
36 static bool equal_ulps_pin(float a, float b, int epsilon, int depsilon) { in equal_ulps_pin() argument
46 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps_pin()
49 static bool d_equal_ulps(float a, float b, int epsilon) { in d_equal_ulps() argument
53 return aBits < bBits + epsilon && bBits < aBits + epsilon; in d_equal_ulps()
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| /external/skia/src/pathops/ |
| D | SkPathOpsTypes.cpp | 12 static bool arguments_denormalized(float a, float b, int epsilon) { in arguments_denormalized() argument
13 float denormalizedCheck = FLT_EPSILON * epsilon / 2; in arguments_denormalized()
19 static bool equal_ulps(float a, float b, int epsilon, int depsilon) { in equal_ulps() argument
26 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps()
29 static bool equal_ulps_no_normal_check(float a, float b, int epsilon, int depsilon) { in equal_ulps_no_normal_check() argument
33 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps_no_normal_check()
36 static bool equal_ulps_pin(float a, float b, int epsilon, int depsilon) { in equal_ulps_pin() argument
46 return aBits < bBits + epsilon && bBits < aBits + epsilon; in equal_ulps_pin()
49 static bool d_equal_ulps(float a, float b, int epsilon) { in d_equal_ulps() argument
53 return aBits < bBits + epsilon && bBits < aBits + epsilon; in d_equal_ulps()
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| /external/catch2/projects/SelfTest/UsageTests/ |
| D | Approx.tests.cpp | 46 REQUIRE( d == 1.2_a .epsilon(.1) );
47 REQUIRE( d != 1.2_a .epsilon(.001) );
48 REQUIRE( d == 1_a .epsilon(.3) );
73 REQUIRE( d == Approx( 1.231 ).epsilon( 0.1 ) );
83 REQUIRE( d <= Approx( 1.22 ).epsilon(0.1) );
93 REQUIRE( d >= Approx( 1.24 ).epsilon(0.1) );
125 Approx approx = Approx::custom().epsilon( 0.01 );
139 REQUIRE( divide( 22, 7 ) == Approx( 3.141 ).epsilon( 0.001 ) );
140 REQUIRE( divide( 22, 7 ) != Approx( 3.141 ).epsilon( 0.0001 ) );
170 REQUIRE_NOTHROW(Approx(0).epsilon(0));
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| /external/tensorflow/tensorflow/python/layers/ |
| D | normalization_test.py | 316 epsilon = 1e-3
318 axis=1, epsilon=epsilon, momentum=0.9)
336 normed_np_output = ((np_output - epsilon) * np_gamma) + np_beta
354 normed_np_output = ((np_output - epsilon) * np_gamma) + np_beta
359 epsilon = 1e-3
361 axis=2, epsilon=epsilon, momentum=0.9)
377 normed_np_output = ((np_output - epsilon) * np_gamma) + np_beta
395 normed_np_output = ((np_output - epsilon) * np_gamma) + np_beta
401 epsilon = 1e-3
403 axis=1, epsilon=epsilon, momentum=0.9)
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| /external/tensorflow/tensorflow/python/keras/ |
| D | optimizers.py | 243 def __init__(self, lr=0.001, rho=0.9, epsilon=None, decay=0., **kwargs): argument
250 if epsilon is None:
251 epsilon = K.epsilon()
252 self.epsilon = epsilon
271 new_p = p - lr * g / (K.sqrt(new_a) + self.epsilon)
285 'epsilon': self.epsilon
311 def __init__(self, lr=0.01, epsilon=None, decay=0., **kwargs): argument
317 if epsilon is None:
318 epsilon = K.epsilon()
319 self.epsilon = epsilon
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| D | backend_config_test.py | 32 epsilon = 1e-2
33 keras.backend_config.set_epsilon(epsilon)
34 self.assertEqual(keras.backend_config.epsilon(), epsilon)
36 self.assertEqual(keras.backend_config.epsilon(), 1e-7)
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| /external/deqp/external/openglcts/modules/glesext/tessellation_shader/ |
| D | esextcTessellationShaderUtils.cpp | 1325 const float epsilon = 1e-5f; in isOuterEdgeVertex() local
1332 …if (de::abs(tessellated_vertex_data[0]) < epsilon || de::abs(tessellated_vertex_data[0] - 1.0f) < … in isOuterEdgeVertex()
1333 …de::abs(tessellated_vertex_data[1]) < epsilon || de::abs(tessellated_vertex_data[1] - 1.0f) < epsi… in isOuterEdgeVertex()
1334 …de::abs(tessellated_vertex_data[2]) < epsilon || de::abs(tessellated_vertex_data[2] - 1.0f) < epsi… in isOuterEdgeVertex()
1350 …if (de::abs(tessellated_vertex_data[0]) < epsilon || de::abs(tessellated_vertex_data[0] - 1.0f) < … in isOuterEdgeVertex()
1351 …de::abs(tessellated_vertex_data[1]) < epsilon || de::abs(tessellated_vertex_data[1] - 1.0f) < epsi… in isOuterEdgeVertex()
1383 const float epsilon = 1e-5f; in isTriangleDefined() local
1389 if ((de::abs(triangle_vertex_data[0] - vertex_data[0]) < epsilon && in isTriangleDefined()
1390 de::abs(triangle_vertex_data[1] - vertex_data[1]) < epsilon && in isTriangleDefined()
1391 de::abs(triangle_vertex_data[2] - vertex_data[2]) < epsilon) || in isTriangleDefined()
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| D | esextcTessellationShaderPoints.cpp | 556 const float epsilon = (float)1.0f / 255.0f; in iterate() local
586 if (de::abs(expected_color_r - rendered_color_r) > epsilon || in iterate()
587 de::abs(expected_color_g - rendered_color_g) > epsilon || in iterate()
588 de::abs(expected_color_b - rendered_color_b) > epsilon || in iterate()
589 de::abs(expected_color_a - rendered_color_a) > epsilon) in iterate()
595 << ", " << rendered_color_a << ") epsilon: " << epsilon << tcu::TestLog::EndMessage; in iterate()
794 const float epsilon = 1e-5f; in verifyCorrectAmountOfVertices() local
852 if (de::abs(clamped_inner_levels[0] - 1.0f) < epsilon) in verifyCorrectAmountOfVertices()
860 if (de::abs(clamped_inner_levels[1] - 1.0f) < epsilon) in verifyCorrectAmountOfVertices()
914 if (de::abs(run.inner[0] - 1.0f) < epsilon && de::abs(run.outer[0] - 1.0f) < epsilon && in verifyCorrectAmountOfVertices()
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| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | adagrad.py | 61 epsilon=1e-7, argument
93 if epsilon is None:
94 epsilon = backend_config.epsilon()
95 if epsilon < 1e-7:
96 raise ValueError('epsilon must be larger than 1e-7: %s' % epsilon)
101 self._set_hyper('epsilon', epsilon)
145 epsilon = self._get_hyper('epsilon', var_dtype)
151 var, lr_t * grad / (math_ops.sqrt(acc_t) + epsilon))
163 epsilon = self._get_hyper('epsilon', var_dtype)
169 var, indices, -lr_t * grad / (math_ops.sqrt(acc_t_slice) + epsilon))
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| D | rmsprop.py | 67 epsilon=1e-7, argument
106 if epsilon is None:
107 epsilon = backend_config.epsilon()
120 self._set_hyper("epsilon", epsilon)
139 epsilon = self._get_hyper("epsilon", var_dtype)
152 epsilon,
163 epsilon,
175 var_t = var - lr_t * grad / (math_ops.sqrt(denom_t) + epsilon)
184 epsilon = self._get_hyper("epsilon", var_dtype)
197 epsilon,
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| D | rmsprop_test.py | 61 epsilon, centered): argument
70 mom_t = momentum * mom + lr * g / (np.sqrt(denom_t + epsilon))
74 var_t = var - lr * g / (np.sqrt(denom_t) + epsilon)
78 lr, rho, momentum, epsilon, centered): argument
94 epsilon)
98 var_t[gindex] = var[gindex] - lr * gvalue / (np.sqrt(denom_t) + epsilon)
103 for (dtype, learning_rate, rho, momentum, epsilon, centered) in _TESTPARAMS:
119 epsilon=epsilon,
161 momentum, epsilon, centered)
164 momentum, epsilon, centered)
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| D | adadelta_test.py | 60 epsilon = 1e-8
65 epsilon=lambda: epsilon) # pylint: disable=cell-var-from-loop
68 learning_rate=lr, rho=rho, epsilon=epsilon)
105 np.sqrt(accum_update + epsilon) *
106 (1. / np.sqrt(accum + epsilon)) * grad)
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.)
185 opt = adadelta.Adadelta(epsilon=None)
189 opt = adadelta.Adadelta(epsilon=1e-8)
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/linear/ |
| D | SimplexSolver.java | 39 protected final double epsilon; field in SimplexSolver
52 public SimplexSolver(final double epsilon) { in SimplexSolver() argument
53 this.epsilon = epsilon; in SimplexSolver()
65 if (MathUtils.compareTo(tableau.getEntry(0, i), minValue, epsilon) < 0) { in getPivotColumn()
86 if (MathUtils.compareTo(entry, 0, epsilon) > 0) { in getPivotRow()
88 if (MathUtils.equals(ratio, minRatio, epsilon)) { in getPivotRow()
106 if (MathUtils.equals(tableau.getEntry(row, column), 1, epsilon) && in getPivotRow()
165 if (!MathUtils.equals(tableau.getEntry(0, tableau.getRhsOffset()), 0, epsilon)) { in solvePhase1()
174 new SimplexTableau(function, linearConstraints, goal, nonNegative, epsilon); in doOptimize()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | fused_batch_norm_op.cu.cc | 30 double epsilon, T* output) { in VarianceToInvVarianceKernel() argument
32 output[index] = rsqrt(input[index] + T(epsilon)); in VarianceToInvVarianceKernel()
38 const T* variance, double epsilon, in operator ()() argument
43 variance, epsilon, inv_variance); in operator ()()
47 __global__ void InvVarianceToVarianceKernel(int nthreads, double epsilon, in InvVarianceToVarianceKernel() argument
51 T var = __fdividef(1, inv_var * inv_var) - T(epsilon); in InvVarianceToVarianceKernel()
60 double epsilon, int sample_size, in operator ()() argument
65 epsilon, sample_size, variance); in operator ()()
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| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| D | cudnn_batchnorm_rewriter.cc | 51 return batch_norm->epsilon() >= 1e-5; in EpsilonInRange()
70 HloInstruction* epsilon = in HandleBatchNormInference() local
72 LiteralUtil::CreateR0(batch_norm->epsilon()))); in HandleBatchNormInference()
79 operands.push_back(epsilon); in HandleBatchNormInference()
106 HloInstruction* epsilon = in HandleBatchNormTraining() local
108 LiteralUtil::CreateR0(batch_norm->epsilon()))); in HandleBatchNormTraining()
115 operands.push_back(epsilon); in HandleBatchNormTraining()
142 variance_plus_epsilon->shape(), epsilon, {})))); in HandleBatchNormTraining()
175 HloInstruction* epsilon = in HandleBatchNormGrad() local
177 LiteralUtil::CreateR0(batch_norm->epsilon()))); in HandleBatchNormGrad()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| D | PoissonDistributionImpl.java | 70 private double epsilon = DEFAULT_EPSILON; field in PoissonDistributionImpl
92 public PoissonDistributionImpl(double p, double epsilon, int maxIterations) { in PoissonDistributionImpl() argument
94 this.epsilon = epsilon; in PoissonDistributionImpl()
105 public PoissonDistributionImpl(double p, double epsilon) { in PoissonDistributionImpl() argument
107 this.epsilon = epsilon; in PoissonDistributionImpl()
219 return Gamma.regularizedGammaQ((double) x + 1, mean, epsilon, maxIterations); in cumulativeProbability()
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| /external/protobuf/js/binary/ |
| D | decoder_test.js | 60 writeValue, epsilon, upperLimit, filter) { argument
65 writeValue.call(encoder, filter(epsilon));
69 for (var cursor = epsilon; cursor < upperLimit; cursor *= 1.1) {
77 assertEquals(filter(epsilon), readValue.call(decoder));
81 for (var cursor = epsilon; cursor < upperLimit; cursor *= 1.1) {
102 writeValue, epsilon, lowerLimit, upperLimit, filter) { argument
107 writeValue.call(encoder, filter(-epsilon));
109 writeValue.call(encoder, filter(epsilon));
115 for (var cursor = lowerLimit; cursor < -epsilon; cursor /= 1.1) {
122 for (var cursor = epsilon; cursor < upperLimit; cursor *= 1.1) {
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | fused_batchnorm_test.py | 40 def _reference_training(self, x, scale, offset, epsilon, data_format): argument
49 normalized = (x - mean) / np.sqrt(var + epsilon)
52 def _reference_grad(self, x, grad_y, scale, mean, var, epsilon, data_format): argument
67 (var + epsilon)) / np.sqrt(var + epsilon)
69 grad_y * (x - mean) / np.sqrt(var + epsilon), axis=(0, 1, 2))
81 epsilon = 0.001
84 x_val, scale_val, offset_val, epsilon, data_format_src)
104 epsilon=epsilon,
124 epsilon = 0.001
127 x_val, scale_val, offset_val, epsilon, data_format_src)
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| /external/catch2/include/internal/ |
| D | catch_approx.cpp | 29 : m_epsilon( std::numeric_limits<float>::epsilon()*100 ), in Approx()
65 void Approx::setEpsilon(double epsilon) { in setEpsilon() argument
66 CATCH_ENFORCE(epsilon >= 0 && epsilon <= 1.0, in setEpsilon()
67 "Invalid Approx::epsilon: " << epsilon << '.' in setEpsilon()
69 m_epsilon = epsilon; in setEpsilon()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/special/ |
| D | Beta.java | 73 double epsilon) throws MathException in regularizedBeta() argument
75 return regularizedBeta(x, a, b, epsilon, Integer.MAX_VALUE); in regularizedBeta()
118 final double b, double epsilon, int maxIterations) throws MathException in regularizedBeta() argument
127 ret = 1.0 - regularizedBeta(1.0 - x, b, a, epsilon, maxIterations); in regularizedBeta()
153 FastMath.log(a) - logBeta(a, b, epsilon, maxIterations)) * in regularizedBeta()
154 1.0 / fraction.evaluate(x, epsilon, maxIterations); in regularizedBeta()
188 public static double logBeta(double a, double b, double epsilon, in logBeta() argument
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| /external/eigen/Eigen/src/SparseCore/ |
| D | SparseView.h | 55 const RealScalar &epsilon = NumTraits<Scalar>::dummy_precision())
56 : m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {}
69 RealScalar epsilon() const { return m_epsilon; }
117 … while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon()))
186 …(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon()))
226 … const typename NumTraits<Scalar>::Real& epsilon) const
228 return SparseView<Derived>(derived(), reference, epsilon);
246 const RealScalar& epsilon) const
248 return SparseView<Derived>(derived(), reference, epsilon);
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| D | OpenMapRealVector.java | 47 private final double epsilon; field in OpenMapRealVector
75 public OpenMapRealVector(int dimension, double epsilon) { in OpenMapRealVector() argument
78 this.epsilon = epsilon; in OpenMapRealVector()
89 epsilon = v.epsilon; in OpenMapRealVector()
107 public OpenMapRealVector(int dimension, int expectedSize, double epsilon) { in OpenMapRealVector() argument
110 this.epsilon = epsilon; in OpenMapRealVector()
128 public OpenMapRealVector(double[] values, double epsilon) { in OpenMapRealVector() argument
131 this.epsilon = epsilon; in OpenMapRealVector()
155 public OpenMapRealVector(Double[] values, double epsilon) { in OpenMapRealVector() argument
158 this.epsilon = epsilon; in OpenMapRealVector()
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| /external/deqp/external/openglcts/modules/glesext/draw_buffers_indexed/ |
| D | esextcDrawBuffersIndexedColorMasks.cpp | 206 tcu::RGBA epsilon = GetEpsilon(); in iterate() local
230 if (!VerifyImg(textureLevel, expected, epsilon)) in iterate()
252 if (!VerifyImg(textureLevel, expected, epsilon)) in iterate()
274 if (!VerifyImg(textureLevel, expected, epsilon)) in iterate()
409 tcu::UVec4 epsilon; in GetEpsilon() local
414 epsilon[i] = de::min( in GetEpsilon()
418 return tcu::RGBA(epsilon.x(), epsilon.y(), epsilon.z(), epsilon.w()); in GetEpsilon()
422 tcu::RGBA epsilon) in VerifyImg() argument
431 if (!tcu::compareThreshold(pixel, expectedColor, epsilon)) in VerifyImg()
435 << "Epsilon: " << epsilon << tcu::TestLog::EndMessage; in VerifyImg()
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| /external/eigen/Eigen/src/Core/ |
| D | NumTraits.h | 34 return int(ceil(-log10(NumTraits<Real>::epsilon())));
110 static inline Real epsilon()
112 return numext::numeric_limits<T>::epsilon();
186 static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
215 static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
235 static inline std::string epsilon();
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