| /packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
| D | log_softmax.mod.py | 19 def test(input0, output0, input_data, beta, axis, output_data): argument
20 model = Model().Operation("LOG_SOFTMAX", input0, beta, axis).To(output0)
31 beta=1.0,
44 beta=1.0,
57 beta=1.0,
68 beta=10.0,
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| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Softmax.cpp | 50 inline bool softmaxSlowFloat32(const float* inputData, const Shape& inputShape, const float beta, in softmaxSlowFloat32() argument
70 sum += std::exp((*p - maxValue) * beta); in softmaxSlowFloat32()
75 *pOut = std::exp((*p - maxValue) * beta) / sum; in softmaxSlowFloat32()
82 bool softmaxFloat32(const float* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxFloat32() argument
89 tflite::SoftmaxParams param = {.beta = beta}; in softmaxFloat32()
94 return softmaxSlowFloat32(inputData, inputShape, beta, axis, outputData, outputShape); in softmaxFloat32()
98 bool softmaxFloat16(const _Float16* inputData, const Shape& inputShape, const float beta, in softmaxFloat16() argument
105 softmaxFloat32(inputData_float32.data(), inputShape, beta, axis, outputData_float32.data(), in softmaxFloat16()
200 bool softmaxQuant8(const T* inputData, const Shape& inputShape, const float beta, int32_t axis, in softmaxQuant8() argument
215 std::min(1.0 * beta * inputShape.scale * (1 << (31 - kScaledDiffIntegerBits)), in softmaxQuant8()
[all …]
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| D | LocalResponseNormalization.cpp | 46 int32_t radius, float bias, float alpha, float beta, in localResponseNormFloat32Impl() argument
67 float multiplier = std::pow(bias + alpha * sum, -beta); in localResponseNormFloat32Impl()
77 T beta, int32_t axis, T* outputData, const Shape& outputShape);
81 float bias, float alpha, float beta, int32_t axis, float* outputData, in localResponseNorm() argument
90 .range = radius, .bias = bias, .alpha = alpha, .beta = beta}; in localResponseNorm()
96 return localResponseNormFloat32Impl(inputData, inputShape, radius, bias, alpha, beta, axis, in localResponseNorm()
103 _Float16 bias, _Float16 alpha, _Float16 beta, int32_t axis, in localResponseNorm() argument
110 localResponseNorm<float>(inputDataFloat32.data(), inputShape, radius, bias, alpha, beta, axis, in localResponseNorm()
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| D | InstanceNormalization.cpp | 39 inline bool instanceNormNhwc(const T* inputData, const Shape& inputShape, T gamma, T beta, in instanceNormNhwc() argument
73 outputData[ind] = (inputData[ind] - mean) * gamma / sigma + beta; in instanceNormNhwc()
82 inline bool instanceNorm(const T* inputData, const Shape& inputShape, T gamma, T beta, T epsilon, in instanceNorm() argument
88 NN_RET_CHECK(instanceNormNhwc(input.getNhwcBuffer(), input.getNhwcShape(), gamma, beta, epsilon, in instanceNorm()
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| D | LogSoftmax.cpp | 34 inline bool compute(const T* input, const Shape& shape, T beta, uint32_t axis, T* output) { in compute() argument
51 (input[(outer * axisSize + i) * innerSize + inner] - maxValue) * beta)); in compute()
57 (input[(outer * axisSize + i) * innerSize + inner] - maxValue) * beta - in compute()
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| /packages/apps/Launcher3/src/com/android/launcher3/anim/ |
| D | SpringAnimationBuilder.java | 58 private double beta; field in SpringAnimationBuilder
142 beta = 2 * mDampingRatio * naturalFreq; in computeParams()
145 b = beta * a / (2 * gamma) + mVelocity / gamma; in computeParams()
147 va = a * beta / 2 - b * gamma; in computeParams()
148 vb = a * gamma + beta * b / 2; in computeParams()
218 return Math.pow(Math.E, - beta * t / 2); in exponentialComponent()
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| D | softmax_quant8_signed.mod.py | 19 beta = Float32Scalar("beta", 0.00001) # close to 0 variable
23 model = model.Operation("SOFTMAX", i1, beta).To(output)
38 beta = Float32Scalar("beta", 1.) variable
42 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
| D | softmax_quant8_2.mod.py | 5 beta = Float32Scalar("beta", 1.) variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | softmax_float_2.mod.py | 5 beta = Float32Scalar("beta", 1.) variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | softmax_quant8_1.mod.py | 5 beta = Float32Scalar("beta", 0.00001) # close to 0 variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | softmax_float_1.mod.py | 5 beta = Float32Scalar("beta", 0.000001) variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | local_response_norm_float_4.mod.py | 6 beta = Float32Scalar("beta", .5) variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
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| D | local_response_norm_float_1.mod.py | 6 beta = Float32Scalar("beta", .5) variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
| D | softmax_float_2_relaxed.mod.py | 21 beta = Float32Scalar("beta", 1.) variable
25 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | softmax_float_1_relaxed.mod.py | 21 beta = Float32Scalar("beta", 0.000001) variable
25 model = model.Operation("SOFTMAX", i1, beta).To(output)
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| D | local_response_norm_float_1_relaxed.mod.py | 22 beta = Float32Scalar("beta", .5) variable
25 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
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| D | local_response_norm_float_4_relaxed.mod.py | 22 beta = Float32Scalar("beta", .5) variable
25 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
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| /packages/modules/Bluetooth/system/audio/asrc/ |
| D | asrc_tables.py | 33 beta = KAISER_BETA variable
35 w = signal.kaiser(2 * a * q + 1, beta)
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| /packages/apps/Gallery2/jni/filters/ |
| D | edge.c | 30 float const beta = p; in JNIFUNCF() local
96 float ret = 1.0f - exp (- alpha * pow(mag, beta)); in JNIFUNCF()
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| /packages/apps/LegacyCamera/jni/feature_mos/src/mosaic/ |
| D | Delaunay.cpp | 148 EdgePointer alpha, beta, temp; in splice() local
150 beta = (EdgePointer) rot(onext(b)); in splice()
152 onext(alpha) = onext(beta); in splice()
153 onext(beta) = temp; in splice()
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| /packages/modules/NeuralNetworks/common/include/ |
| D | Operations.h | 67 float bias, float alpha, float beta, int32_t axis,
70 float bias, float alpha, float beta, int32_t axis, float* outputData,
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| /packages/screensavers/PhotoTable/src/com/android/dreams/phototable/ |
| D | PhotoTable.java | 366 final double beta = Math.toRadians(Math.min(angle, 180f) / 2f); in moveFocus() local
367 final double[] left = { Math.sin(alpha - beta), in moveFocus()
368 Math.cos(alpha - beta) }; in moveFocus()
369 final double[] right = { Math.sin(alpha + beta), in moveFocus()
370 Math.cos(alpha + beta) }; in moveFocus()
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| /packages/modules/NeuralNetworks/tools/api/ |
| D | README.md | 159 %{test alpha beta}
165 second is beta, first is alpha
171 error, but `%{test alpha beta gamma}` would not.
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| /packages/modules/Virtualization/docs/debug/ |
| D | README.md | 57 get a bug report from your QA team or from beta testers. To fix the bug, you
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| /packages/modules/NeuralNetworks/runtime/test/ |
| D | TestValidateOperations.cpp | 1704 ANeuralNetworksOperandType beta = {.type = (inputOperandCode == ANEURALNETWORKS_TENSOR_FLOAT32) in logSoftmaxOpTest() local
1723 OperationTestBase test(ANEURALNETWORKS_LOG_SOFTMAX, {input, beta, axis}, {output}); in logSoftmaxOpTest()
1836 ANeuralNetworksOperandType beta = getOpType(ANEURALNETWORKS_FLOAT32); in softmaxOpTest() local
1838 beta = getOpType(ANEURALNETWORKS_FLOAT16); in softmaxOpTest()
1841 OperationTestBase softmaxTest(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output}, in softmaxOpTest()
1846 OperationTestBase softmaxAxisTest(ANEURALNETWORKS_SOFTMAX, {input, beta, axis}, {output}, in softmaxOpTest()
3336 ANeuralNetworksOperandType beta = floatScalar; in instanceNormalizationOpTest() local
3342 {input, gamma, beta, epsilon, isNCHW}, {output}); in instanceNormalizationOpTest()
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