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Searched refs:stddev (Results 1 – 25 of 171) sorted by relevance

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/external/tensorflow/tensorflow/contrib/kernel_methods/python/mappers/
Drandom_fourier_features_test.py49 def _compute_exact_rbf_kernel(x, y, stddev): argument
53 return math_ops.exp(-diff_squared_norm / (2 * stddev * stddev))
94 stddev = 3.0
99 rffm1 = RandomFourierFeatureMapper(3, 100, stddev)
100 rffm2 = RandomFourierFeatureMapper(3, 100, stddev)
114 stddev = 3.0
119 rffm = RandomFourierFeatureMapper(3, 100, stddev, seed=0)
122 exact_kernel_value = _compute_exact_rbf_kernel(x, y, stddev)
132 stddev = 5.0
147 rffm = RandomFourierFeatureMapper(input_dim, mapped_dim, stddev, seed=0)
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/external/fio/lib/
Dgauss.c14 if (!gs->stddev) in gauss_dev()
18 vr = gs->stddev * (r / (FRAND32_MAX + 1.0)); in gauss_dev()
20 return vr - gs->stddev / 2; in gauss_dev()
33 if (gs->stddev) { in gauss_next()
55 gs->stddev = ceil((double) (nranges * 100.0) / dev); in gauss_init()
56 if (gs->stddev > nranges / 2) in gauss_init()
57 gs->stddev = nranges / 2; in gauss_init()
/external/tensorflow/tensorflow/python/kernel_tests/
Dparameterized_truncated_normal_op_test.py41 stddev = None variable in TruncatedNormalMoments
45 def __init__(self, mean, stddev, minval, maxval): argument
48 self.stddev = np.double(stddev)
69 dist = scipy.stats.norm(loc=self.mean, scale=self.stddev)
76 m = ((k - 1) * self.stddev**2 * m_k_minus_2 + self.mean * m_k_minus_1 -
77 self.stddev * numerator / denominator)
112 def validateMoments(self, shape, mean, stddev, minval, maxval, seed=1618): argument
119 samples = random_ops.parameterized_truncated_normal(shape, mean, stddev,
124 expected_moments = TruncatedNormalMoments(mean, stddev, minval, maxval)
135 stddev, argument
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/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/
Dnoise.py52 def __init__(self, stddev, **kwargs): argument
55 self.stddev = stddev
61 shape=K.shape(inputs), mean=0., stddev=self.stddev)
66 config = {'stddev': self.stddev}
105 stddev = np.sqrt(self.rate / (1.0 - self.rate))
107 shape=K.shape(inputs), mean=1.0, stddev=stddev)
/external/tensorflow/tensorflow/examples/speech_commands/
Dmodels.py156 tf.truncated_normal([fingerprint_size, label_count], stddev=0.001))
225 stddev=0.01))
244 stddev=0.01))
264 [second_conv_element_count, label_count], stddev=0.01))
333 stddev=0.01))
356 [first_conv_element_count, first_fc_output_channels], stddev=0.01))
366 [first_fc_output_channels, second_fc_output_channels], stddev=0.01))
376 [second_fc_output_channels, label_count], stddev=0.01))
487 tf.truncated_normal([input_frequency_size, num_filters], stddev=0.01))
510 tf.truncated_normal([num_filters, input_time_size], stddev=0.01))
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/external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/python/layers/
Ddecisions_to_data.py44 mean=params.weight_init_mean, stddev=params.weight_init_std))
50 mean=params.weight_init_mean, stddev=params.weight_init_std))
85 mean=params.weight_init_mean, stddev=params.weight_init_std))
91 mean=params.weight_init_mean, stddev=params.weight_init_std))
130 mean=params.weight_init_mean, stddev=params.weight_init_std))
136 mean=params.weight_init_mean, stddev=params.weight_init_std))
168 mean=params.weight_init_mean, stddev=params.weight_init_std))
174 mean=params.weight_init_mean, stddev=params.weight_init_std))
220 mean=params.weight_init_mean, stddev=params.weight_init_std))
226 mean=params.weight_init_mean, stddev=params.weight_init_std))
/external/tensorflow/tensorflow/python/ops/
Dinit_ops.py280 def __init__(self, mean=0.0, stddev=1.0, seed=None, dtype=dtypes.float32): argument
282 self.stddev = stddev
290 shape, self.mean, self.stddev, dtype, seed=self.seed)
295 "stddev": self.stddev,
322 def __init__(self, mean=0.0, stddev=1.0, seed=None, dtype=dtypes.float32): argument
324 self.stddev = stddev
332 shape, self.mean, self.stddev, dtype, seed=self.seed)
337 "stddev": self.stddev,
466 stddev = math.sqrt(scale)
468 shape, 0.0, stddev, dtype, seed=self.seed)
Drandom_ops.py50 stddev=1.0, argument
72 with ops.name_scope(name, "random_normal", [shape, mean, stddev]) as name:
75 stddev_tensor = ops.convert_to_tensor(stddev, dtype=dtype, name="stddev")
143 stddev=1.0, argument
169 with ops.name_scope(name, "truncated_normal", [shape, mean, stddev]) as name:
172 stddev_tensor = ops.convert_to_tensor(stddev, dtype=dtype, name="stddev")
/external/tensorflow/tensorflow/core/kernels/
Dparameterized_truncated_normal_op_gpu.cu.cc86 T stddev; in TruncatedNormalKernel() local
93 stddev = -input_stddev; in TruncatedNormalKernel()
95 stddev = input_stddev; in TruncatedNormalKernel()
99 const T normMin = (minval - mean) / stddev; in TruncatedNormalKernel()
100 const T normMax = (maxval - mean) / stddev; in TruncatedNormalKernel()
150 data[offset] = z[i] * stddev + mean; in TruncatedNormalKernel()
175 data[offset] = z * stddev + mean; in TruncatedNormalKernel()
Dparameterized_truncated_normal_op.cc87 T stddev = stddevs((stddevs.dimension(0) == 1) ? 0 : b); in operator ()() local
99 stddev > T(0) && minval < maxval && in operator ()()
112 stddev = -stddev; in operator ()()
116 const T normMin = (minval - mean) / stddev; in operator ()()
117 const T normMax = (maxval - mean) / stddev; in operator ()()
155 output(sample) = z[i] * stddev + mean; in operator ()()
186 output(sample) = z * stddev + mean; in operator ()()
/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
Dcifar10_pruning.py105 def _variable_with_weight_decay(name, shape, stddev, wd): argument
124 stddev=stddev, dtype=dtype))
190 'weights', shape=[5, 5, 3, 64], stddev=5e-2, wd=0.0)
213 'weights', shape=[5, 5, 64, 64], stddev=5e-2, wd=0.0)
238 'weights', shape=[dim, 384], stddev=0.04, wd=0.004)
248 'weights', shape=[384, 192], stddev=0.04, wd=0.004)
261 'weights', [192, NUM_CLASSES], stddev=1 / 192.0, wd=0.0)
/external/tensorflow/tensorflow/python/profiler/internal/
Dmodel_analyzer_testlib.py44 initializer=init_ops.random_normal_initializer(stddev=0.001))
48 initializer=init_ops.random_normal_initializer(stddev=0.001))
53 initializer=init_ops.random_normal_initializer(stddev=0.001))
82 initializer=init_ops.random_normal_initializer(stddev=0.001))
88 initializer=init_ops.random_normal_initializer(stddev=0.001))
/external/libcxx/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/
Dctor_double_double.pass.cpp26 assert(d.stddev() == 1); in main()
32 assert(d.stddev() == 1); in main()
38 assert(d.stddev() == 5.25); in main()
Dparam_ctor.pass.cpp28 assert(p.stddev() == 1); in main()
35 assert(p.stddev() == 1); in main()
42 assert(p.stddev() == 5); in main()
/external/tensorflow/tensorflow/stream_executor/cuda/
Dcuda_rng.cc210 ElemT stddev, in DoPopulateRandGaussianInternal() argument
221 func(parent_, rng_, CUDAMemoryMutable(v), element_count, mean, stddev); in DoPopulateRandGaussianInternal()
232 bool CUDARng::DoPopulateRandGaussian(Stream *stream, float mean, float stddev, in DoPopulateRandGaussian() argument
234 return DoPopulateRandGaussianInternal(stream, mean, stddev, v, in DoPopulateRandGaussian()
238 bool CUDARng::DoPopulateRandGaussian(Stream *stream, double mean, double stddev, in DoPopulateRandGaussian() argument
240 return DoPopulateRandGaussianInternal(stream, mean, stddev, v, in DoPopulateRandGaussian()
Dcuda_rng.h64 bool DoPopulateRandGaussian(Stream *stream, float mean, float stddev,
66 bool DoPopulateRandGaussian(Stream *stream, double mean, double stddev,
77 bool DoPopulateRandGaussianInternal(Stream *stream, ElemT mean, ElemT stddev,
/external/tensorflow/tensorflow/python/ops/linalg/
Dlinear_operator_test_util.py490 def random_normal(shape, mean=0.0, stddev=1.0, dtype=dtypes.float32, seed=None): argument
514 shape, mean=mean, stddev=stddev, dtype=dtype.real_dtype, seed=seed)
519 shape, mean=mean, stddev=stddev, dtype=dtype.real_dtype, seed=seed)
605 stddev=1.0, argument
660 shape, mean=mean, stddev=stddev, dtype=dtype, seed=seed)
675 smaller_shape, mean=0.0, stddev=stddev_mat, dtype=dtype, seed=seed)
687 return embedded + random_normal(shape, stddev=eps, dtype=dtype) + mean_mat
/external/tensorflow/tensorflow/examples/tutorials/mnist/
Dmnist.py60 stddev=1.0 / math.sqrt(float(IMAGE_PIXELS))),
69 stddev=1.0 / math.sqrt(float(hidden1_units))),
78 stddev=1.0 / math.sqrt(float(hidden2_units))),
/external/tensorflow/tensorflow/python/grappler/
Dcost_analyzer_test.py68 random_ops.truncated_normal([5, 5, 1, 32], stddev=0.1))
69 b = variables.Variable(random_ops.truncated_normal([32], stddev=0.1))
75 random_ops.truncated_normal([25088, 10], stddev=0.1))
76 b_fc = variables.Variable(random_ops.truncated_normal([10], stddev=0.1))
/external/skia/tools/skpbench/
Dskpbench.py221 if not self.best_result or result.stddev <= self.best_result.stddev:
226 (result.config, result.bench, self.best_result.stddev,
227 result.stddev), file=sys.stderr)
228 if self.max_stddev and self.best_result.stddev > self.max_stddev:
275 skpbench.best_result.stddev, skpbench.max_stddev,
/external/skqp/tools/skpbench/
Dskpbench.py221 if not self.best_result or result.stddev <= self.best_result.stddev:
226 (result.config, result.bench, self.best_result.stddev,
227 result.stddev), file=sys.stderr)
228 if self.max_stddev and self.best_result.stddev > self.max_stddev:
275 skpbench.best_result.stddev, skpbench.max_stddev,
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Drandom_ops.cc135 xla::ComputationDataHandle stddev = XlaHelpers::One(b, dtype); in Compile() local
137 b->RngNormal(mean, stddev, xla_shape); in Compile()
173 xla::ComputationDataHandle stddev = XlaHelpers::One(b, dtype); in Compile() local
174 b->Select(to_resample, b->RngNormal(mean, stddev, xla_shape), candidate); in Compile()
/external/tensorflow/tensorflow/contrib/training/python/training/
Dresample_test.py169 def get_weights(self, n, mean=10.0, stddev=5): argument
174 v = numpy.random.normal(mean, stddev)
196 stddev = math.sqrt(len(weights) * n * overall_rate * (1 - overall_rate))
201 delta=(stddev * tol + abs_delta))
/external/tensorflow/tensorflow/compiler/xla/tests/
Dliteral_test_util.h226 const Shape& shape, E* engine, T mean, T stddev);
236 const Shape& shape, T mean, T stddev);
364 T stddev) { in CreateRandomLiteral() argument
366 std::normal_distribution<NativeT> generator(mean, stddev); in CreateRandomLiteral()
375 LiteralTestUtil::CreateRandomLiteral(const Shape& shape, T mean, T stddev) { in CreateRandomLiteral() argument
377 return CreateRandomLiteral<type>(shape, &engine, mean, stddev); in CreateRandomLiteral()
/external/tensorflow/tensorflow/stream_executor/
Drng.h65 virtual bool DoPopulateRandGaussian(Stream *stream, float mean, float stddev, in DoPopulateRandGaussian() argument
72 double stddev, DeviceMemory<double> *v) { in DoPopulateRandGaussian() argument

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