/external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
D | gamma_test.py | 30 from tensorflow.python.ops.distributions import gamma as gamma_lib 55 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta) 57 self.assertEqual(self.evaluate(gamma.batch_shape_tensor()), (5,)) 58 self.assertEqual(gamma.batch_shape, tensor_shape.TensorShape([5])) 59 self.assertAllEqual(self.evaluate(gamma.event_shape_tensor()), []) 60 self.assertEqual(gamma.event_shape, tensor_shape.TensorShape([])) 69 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta) 70 log_pdf = gamma.log_prob(x) 72 pdf = gamma.prob(x) 76 expected_log_pdf = stats.gamma.logpdf(x, alpha_v, scale=1 / beta_v) [all …]
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/external/python/cpython2/Lib/test/ |
D | math_testcases.txt | 170 -- lgamma: log of absolute value of the gamma function -- 250 -- inputs for which gamma(x) is tiny 275 -- gamma: Gamma function -- 279 gam0000 gamma 0.0 -> inf divide-by-zero 280 gam0001 gamma -0.0 -> -inf divide-by-zero 281 gam0002 gamma inf -> inf 282 gam0003 gamma -inf -> nan invalid 283 gam0004 gamma nan -> nan 286 gam0010 gamma -1 -> nan invalid 287 gam0011 gamma -2 -> nan invalid [all …]
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/external/ImageMagick/MagickCore/ |
D | composite-private.h | 57 gamma, in CompositePixelOver() local 68 gamma=Sa+Da-Sa*Da; in CompositePixelOver() 69 gamma=PerceptibleReciprocal(gamma); in CompositePixelOver() 86 composite[i]=ClampToQuantum(gamma*MagickOver_((double) p->red,alpha, in CompositePixelOver() 92 composite[i]=ClampToQuantum(gamma*MagickOver_((double) p->green,alpha, in CompositePixelOver() 98 composite[i]=ClampToQuantum(gamma*MagickOver_((double) p->blue,alpha, in CompositePixelOver() 104 composite[i]=ClampToQuantum(gamma*MagickOver_((double) p->black,alpha, in CompositePixelOver() 127 gamma, in CompositePixelInfoOver() local 135 gamma=Sa+Da-Sa*Da; in CompositePixelInfoOver() 136 composite->alpha=(double) QuantumRange*RoundToUnity(gamma); in CompositePixelInfoOver() [all …]
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D | composite.c | 383 gamma; in CompositeOverImage() local 497 gamma=PerceptibleReciprocal(alpha); in CompositeOverImage() 498 pixel=QuantumRange*gamma*(Sca+Dca*(1.0-Sa)); in CompositeOverImage() 1284 gamma; in CompositeImage() local 1729 gamma=PerceptibleReciprocal(1.0-alpha); in CompositeImage() 1734 gamma=PerceptibleReciprocal(alpha); in CompositeImage() 1754 pixel=gamma*(source_dissolve*Sa*Sc+canvas_dissolve*Da*Dc); in CompositeImage() 1795 pixel=QuantumRange*gamma*(Sa*Da+Dca*(1.0-Sa)); in CompositeImage() 1800 pixel=QuantumRange*gamma*(Dca*(1.0-Sa)); in CompositeImage() 1803 pixel=QuantumRange*gamma*(Sa*Da-Sa*Da*MagickMin(1.0,(1.0-DcaDa)* in CompositeImage() [all …]
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/external/python/cpython3/Lib/test/ |
D | math_testcases.txt | 170 -- lgamma: log of absolute value of the gamma function -- 250 -- inputs for which gamma(x) is tiny 275 -- gamma: Gamma function -- 279 gam0000 gamma 0.0 -> inf divide-by-zero 280 gam0001 gamma -0.0 -> -inf divide-by-zero 281 gam0002 gamma inf -> inf 282 gam0003 gamma -inf -> nan invalid 283 gam0004 gamma nan -> nan 286 gam0010 gamma -1 -> nan invalid 287 gam0011 gamma -2 -> nan invalid [all …]
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/external/skqp/src/core/ |
D | SkMaskGamma.cpp | 16 SkScalar toLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luminance) const override { in toLuma() argument 17 SkASSERT(SK_Scalar1 == gamma); in toLuma() 20 SkScalar fromLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luma) const override { in fromLuma() argument 21 SkASSERT(SK_Scalar1 == gamma); in fromLuma() 27 SkScalar toLuma(SkScalar gamma, SkScalar luminance) const override { in toLuma() argument 28 return SkScalarPow(luminance, gamma); in toLuma() 30 SkScalar fromLuma(SkScalar gamma, SkScalar luma) const override { in fromLuma() argument 31 return SkScalarPow(luma, SkScalarInvert(gamma)); in fromLuma() 36 SkScalar toLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luminance) const override { in toLuma() argument 37 SkASSERT(0 == gamma); in toLuma() [all …]
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D | SkMaskGamma.h | 29 virtual SkScalar toLuma(SkScalar gamma, SkScalar luminance) const = 0; 31 virtual SkScalar fromLuma(SkScalar gamma, SkScalar luma) const = 0; 34 static U8CPU computeLuminance(SkScalar gamma, SkColor c) { in computeLuminance() argument 35 const SkColorSpaceLuminance& luminance = Fetch(gamma); in computeLuminance() 36 SkScalar r = luminance.toLuma(gamma, SkIntToScalar(SkColorGetR(c)) / 255); in computeLuminance() 37 SkScalar g = luminance.toLuma(gamma, SkIntToScalar(SkColorGetG(c)) / 255); in computeLuminance() 38 SkScalar b = luminance.toLuma(gamma, SkIntToScalar(SkColorGetB(c)) / 255); in computeLuminance() 43 return SkScalarRoundToInt(luminance.fromLuma(gamma, luma) * 255); in computeLuminance() 47 static const SkColorSpaceLuminance& Fetch(SkScalar gamma);
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/external/skia/src/core/ |
D | SkMaskGamma.cpp | 16 SkScalar toLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luminance) const override { in toLuma() argument 17 SkASSERT(SK_Scalar1 == gamma); in toLuma() 20 SkScalar fromLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luma) const override { in fromLuma() argument 21 SkASSERT(SK_Scalar1 == gamma); in fromLuma() 27 SkScalar toLuma(SkScalar gamma, SkScalar luminance) const override { in toLuma() argument 28 return SkScalarPow(luminance, gamma); in toLuma() 30 SkScalar fromLuma(SkScalar gamma, SkScalar luma) const override { in fromLuma() argument 31 return SkScalarPow(luma, SkScalarInvert(gamma)); in fromLuma() 36 SkScalar toLuma(SkScalar SkDEBUGCODE(gamma), SkScalar luminance) const override { in toLuma() argument 37 SkASSERT(0 == gamma); in toLuma() [all …]
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D | SkMaskGamma.h | 29 virtual SkScalar toLuma(SkScalar gamma, SkScalar luminance) const = 0; 31 virtual SkScalar fromLuma(SkScalar gamma, SkScalar luma) const = 0; 34 static U8CPU computeLuminance(SkScalar gamma, SkColor c) { in computeLuminance() argument 35 const SkColorSpaceLuminance& luminance = Fetch(gamma); in computeLuminance() 36 SkScalar r = luminance.toLuma(gamma, SkIntToScalar(SkColorGetR(c)) / 255); in computeLuminance() 37 SkScalar g = luminance.toLuma(gamma, SkIntToScalar(SkColorGetG(c)) / 255); in computeLuminance() 38 SkScalar b = luminance.toLuma(gamma, SkIntToScalar(SkColorGetB(c)) / 255); in computeLuminance() 43 return SkScalarRoundToInt(luminance.fromLuma(gamma, luma) * 255); in computeLuminance() 47 static const SkColorSpaceLuminance& Fetch(SkScalar gamma);
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/external/tensorflow/tensorflow/core/kernels/ |
D | smooth-hinge-loss.h | 45 (label - wx - gamma * current_dual) / in ComputeUpdatedDual() 46 (num_partitions * example_weight * weighted_example_norm + gamma); in ComputeUpdatedDual() 64 return (-y_alpha + 0.5 * gamma * current_dual * current_dual) * in ComputeDualLoss() 72 if (y_wx <= 1 - gamma) return (1 - y_wx - gamma / 2) * example_weight; in ComputePrimalLoss() 73 return (1 - y_wx) * (1 - y_wx) * example_weight * 0.5 / gamma; in ComputePrimalLoss() 97 if (label * wx <= 1 - gamma) { in PrimalLossDerivative() 100 return (wx - label) / gamma; in PrimalLossDerivative() 103 double SmoothnessConstant() const final { return gamma; } in SmoothnessConstant() 108 const double gamma = 1;
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D | batch_norm_op.cc | 49 const Tensor& gamma = context->input(4); in Compute() local 63 OP_REQUIRES(context, gamma.dims() == 1, in Compute() 65 gamma.shape().DebugString())); in Compute() 73 var.vec<T>(), beta.vec<T>(), gamma.vec<T>(), variance_epsilon_, in Compute() 98 const Tensor& gamma = context->input(3); in Compute() local 110 OP_REQUIRES(context, gamma.dims() == 1, in Compute() 112 gamma.shape().DebugString())); in Compute() 134 OP_REQUIRES_OK(context, context->allocate_output(4, gamma.shape(), &dg)); in Compute() 153 var.vec<T>(), gamma.vec<T>(), out_backprop.tensor<T, 4>(), in Compute() 183 typename TTypes<T>::ConstVec beta, typename TTypes<T>::ConstVec gamma, \ [all …]
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/external/libpng/tests/ |
D | pngstest | 16 gamma="$1" 27 test "$gamma" = "linear" && g="$f";; 30 test "$gamma" = "sRGB" && g="$f";; 33 test "$gamma" = "1.8" && g="$f";; 36 test "$gamma" = "none" && g="$f";; 54 exec ./pngstest --tmpfile "${gamma}-${alpha}-" --log ${1+"$@"} $args
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/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
D | ChiSquaredDistributionImpl.java | 42 private GammaDistribution gamma; field in ChiSquaredDistributionImpl 81 gamma = new GammaDistributionImpl(df / 2.0, 2.0); in ChiSquaredDistributionImpl() 100 gamma.setAlpha(degreesOfFreedom / 2.0); in setDegreesOfFreedomInternal() 108 return gamma.getAlpha() * 2.0; in getDegreesOfFreedom() 132 return gamma.density(x); in density() 143 return gamma.cumulativeProbability(x); in cumulativeProbability() 182 return Double.MIN_VALUE * gamma.getBeta(); in getDomainLowerBound() 256 this.gamma = g; in setGammaInternal()
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/external/eigen/unsupported/test/ |
D | cxx11_tensor_sugar.cpp | 44 const float gamma = 0.14f; in test_scalar_sugar_add_mul() local 46 Tensor<float, 3> R = A.constant(gamma) + A * A.constant(alpha) + B * B.constant(beta); in test_scalar_sugar_add_mul() 47 Tensor<float, 3> S = A * alpha + B * beta + gamma; in test_scalar_sugar_add_mul() 48 Tensor<float, 3> T = gamma + alpha * A + beta * B; in test_scalar_sugar_add_mul() 64 const float gamma = 0.14f; in test_scalar_sugar_sub_div() local 67 Tensor<float, 3> R = A.constant(gamma) - A / A.constant(alpha) in test_scalar_sugar_sub_div() 69 Tensor<float, 3> S = gamma - A / alpha - beta / B - delta; in test_scalar_sugar_sub_div()
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/external/webrtc/modules/audio_processing/ns/ |
D | noise_estimator.cc | 155 float gamma = kNoiseUpdate; in PostUpdate() local 163 gamma * prev_noise_spectrum_[i] + in PostUpdate() 164 (1.f - gamma) * (prob_non_speech * signal_spectrum[i] + in PostUpdate() 168 float gamma_old = gamma; in PostUpdate() 172 gamma = prob_speech > kProbRange ? .99f : kNoiseUpdate; in PostUpdate() 181 if (gamma == gamma_old) { in PostUpdate() 185 gamma * prev_noise_spectrum_[i] + in PostUpdate() 186 (1.f - gamma) * (prob_non_speech * signal_spectrum[i] + in PostUpdate()
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/external/tensorflow/tensorflow/python/ops/linalg/sparse/ |
D | conjugate_gradient.py | 96 alpha = state.gamma / dot(state.p, z) 103 gamma = dot(r, q) 104 beta = gamma / state.gamma 106 return i + 1, cg_state(i + 1, x, r, p, gamma) 135 state = cg_state(i=i, x=x, r=r0, p=p0, gamma=gamma0) 143 gamma=state.gamma)
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/external/ImageMagick/coders/ |
D | hdr.c | 144 gamma; in ReadHDRImage() local 302 image->gamma=StringToDouble(value,(char **) NULL); in ReadHDRImage() 490 gamma=pow(2.0,pixel[3]-(128.0+8.0)); in ReadHDRImage() 491 SetPixelRed(image,ClampToQuantum(QuantumRange*gamma*pixel[0]),q); in ReadHDRImage() 492 SetPixelGreen(image,ClampToQuantum(QuantumRange*gamma*pixel[1]),q); in ReadHDRImage() 493 SetPixelBlue(image,ClampToQuantum(QuantumRange*gamma*pixel[2]),q); in ReadHDRImage() 728 if (image->gamma != 0.0) in WriteHDRImage() 731 image->gamma); in WriteHDRImage() 773 gamma; in WriteHDRImage() local 779 gamma=QuantumScale*GetPixelRed(image,p); in WriteHDRImage() [all …]
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/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/direct/ |
D | MultiDirectional.java | 40 private final double gamma; field in MultiDirectional 47 this.gamma = 0.5; in MultiDirectional() 54 public MultiDirectional(final double khi, final double gamma) { in MultiDirectional() argument 56 this.gamma = gamma; in MultiDirectional() 90 final RealPointValuePair contracted = evaluateNewSimplex(original, gamma, comparator); in iterateSimplex()
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D | NelderMead.java | 42 private final double gamma; field in NelderMead 54 this.gamma = 0.5; in NelderMead() 65 final double gamma, final double sigma) { in NelderMead() argument 68 this.gamma = gamma; in NelderMead() 139 xC[j] = centroid[j] + gamma * (xR[j] - centroid[j]); in iterateSimplex() 154 xC[j] = centroid[j] - gamma * (centroid[j] - xWorst[j]); in iterateSimplex()
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/external/libpng/contrib/libtests/ |
D | gentests.sh | 68 for gamma in "" --sRGB --linear --1.8 70 case "$gamma" in 80 gname="-$gamma";; 82 "$mp" $gamma "$1" "$2" "test-$1-$2$gname.png"
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/external/llvm-project/lld/test/COFF/ |
D | duplicate.test | 11 RUN: llc -mtriple x86_64-windows-msvc -filetype obj -o gamma.obj %S/Inputs/gamma.ll 12 RUN: not lld-link /out:gamma.exe /subsystem:console /entry:mainCRTStartup gamma.obj alpha.lib 2>&1 … 15 CHECK-GAMMA: defined at {{.*}}gamma.obj
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/external/libaom/libaom/av1/common/x86/ |
D | warp_plane_sse4.c | 470 static INLINE void prepare_vertical_filter_coeffs(int gamma, int sy, in prepare_vertical_filter_coeffs() argument 474 ((sy + 0 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 477 ((sy + 2 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 480 ((sy + 4 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 483 ((sy + 6 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 498 ((sy + 1 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 501 ((sy + 3 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 504 ((sy + 5 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 507 ((sy + 7 * gamma) >> WARPEDDIFF_PREC_BITS))); in prepare_vertical_filter_coeffs() 678 uint8_t *pred, __m128i *tmp, ConvolveParams *conv_params, int16_t gamma, in warp_vertical_filter() argument [all …]
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/external/mesa3d/docs/ |
D | xlibdriver.rst | 90 displayed intensities, there is a gamma correction feature in Mesa. Some 91 systems, such as Silicon Graphics, support gamma correction in hardware 92 (man gamma) so you won't need to use Mesa's gamma facility. Other 93 systems, however, may need gamma adjustment to produce images which look 98 is the red gamma value, Gg is the green gamma value, Gb is the blue 99 gamma value and G is one gamma value to use for all three channels. Each 101 defaults are all 1.0, effectively disabling gamma correction. Examples: 106 % export MESA_GAMMA="2.0" // same gamma for R,G,B 108 The ``demos/gamma.c`` program in mesa/demos repository may help you to 109 determine reasonable gamma value for your display. With correct gamma [all …]
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/external/libaom/libaom/test/ |
D | warp_filter_test_util.cc | 30 int16_t *alpha, int16_t *beta, int16_t *gamma, in generate_warped_model() argument 69 *gamma = static_cast<int16_t>(clamp64( in generate_warped_model() 79 (4 * abs(*gamma) + 4 * abs(*delta) >= (1 << WARPEDMODEL_PREC_BITS))) in generate_warped_model() 86 *gamma = ROUND_POWER_OF_TWO_SIGNED(*gamma, WARP_PARAM_REDUCE_BITS) * in generate_warped_model() 135 int16_t alpha, beta, gamma, delta; in RunSpeedTest() local 138 generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, in RunSpeedTest() 161 sub_x, sub_y, &conv_params, alpha, beta, gamma, delta); in RunSpeedTest() 195 int16_t alpha, beta, gamma, delta; in RunCheckOutput() local 212 generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, in RunCheckOutput() 234 beta, gamma, delta); in RunCheckOutput() [all …]
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/external/igt-gpu-tools/tests/ |
D | kms_color.c | 115 gamma_lut_t *gamma; in alloc_lut() local 119 gamma = malloc(sizeof(*gamma) + lut_size * sizeof(gamma->coeffs[0])); in alloc_lut() 120 igt_assert(gamma); in alloc_lut() 121 gamma->size = lut_size; in alloc_lut() 123 return gamma; in alloc_lut() 126 static void free_lut(gamma_lut_t *gamma) in free_lut() argument 128 if (!gamma) in free_lut() 131 free(gamma); in free_lut() 136 gamma_lut_t *gamma = alloc_lut(lut_size); in generate_table() local 139 gamma->coeffs[0] = 0.0; in generate_table() [all …]
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