| /external/tensorflow/tensorflow/python/keras/ |
| D | regularizers.py | 59 regularization = 0.
61 regularization += math_ops.reduce_sum(self.l1 * math_ops.abs(x))
63 regularization += math_ops.reduce_sum(self.l2 * math_ops.square(x))
64 return regularization
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| /external/libopus/silk/float/ |
| D | residual_energy_FLP.c | 47 silk_float tmp, nrg = 0.0f, regularization; in silk_residual_energy_covar_FLP() local
52 regularization = REGULARIZATION_FACTOR * ( wXX[ 0 ] + wXX[ D * D - 1 ] ); in silk_residual_energy_covar_FLP()
75 matrix_c_ptr( wXX, i, i, D ) += regularization; in silk_residual_energy_covar_FLP()
78 regularization *= 2.0f; in silk_residual_energy_covar_FLP()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SdcaShrinkL1.pbtxt | 19 Symmetric l1 regularization strength.
25 Symmetric l2 regularization strength. Should be a positive float.
28 summary: "Applies L1 regularization shrink step on the parameters."
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| D | api_def_ResourceApplyProximalGradientDescent.pbtxt | 18 L1 regularization. Must be a scalar.
24 L2 regularization. Must be a scalar.
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| D | api_def_ApplyProximalGradientDescent.pbtxt | 18 L1 regularization. Must be a scalar.
24 L2 regularization. Must be a scalar.
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| D | api_def_BoostedTreesCenterBias.pbtxt | 25 l1 regularization factor on leaf weights, per instance based.
31 l2 regularization factor on leaf weights, per instance based.
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| D | api_def_ResourceApplyProximalAdagrad.pbtxt | 24 L1 regularization. Must be a scalar.
30 L2 regularization. Must be a scalar.
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| D | api_def_ResourceApplyAdagradDA.pbtxt | 36 L1 regularization. Must be a scalar.
42 L2 regularization. Must be a scalar.
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| D | api_def_ApplyProximalAdagrad.pbtxt | 24 L1 regularization. Must be a scalar.
30 L2 regularization. Must be a scalar.
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| D | api_def_ResourceSparseApplyProximalGradientDescent.pbtxt | 18 L1 regularization. Must be a scalar.
24 L2 regularization. Must be a scalar.
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| D | api_def_ApplyAdagradDA.pbtxt | 36 L1 regularization. Must be a scalar.
42 L2 regularization. Must be a scalar.
|
| D | api_def_SparseApplyProximalGradientDescent.pbtxt | 18 L1 regularization. Must be a scalar.
24 L2 regularization. Must be a scalar.
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| D | api_def_SparseApplyAdagradDA.pbtxt | 42 L1 regularization. Must be a scalar.
48 L2 regularization. Must be a scalar.
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| D | api_def_ResourceSparseApplyProximalAdagrad.pbtxt | 24 L1 regularization. Must be a scalar.
30 L2 regularization. Must be a scalar.
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| D | api_def_ResourceSparseApplyAdagradDA.pbtxt | 42 L1 regularization. Must be a scalar.
48 L2 regularization. Must be a scalar.
|
| D | api_def_SparseApplyProximalAdagrad.pbtxt | 24 L1 regularization. Must be a scalar.
30 L2 regularization. Must be a scalar.
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| D | api_def_ResourceSparseApplyFtrl.pbtxt | 42 L1 regularization. Must be a scalar.
48 L2 regularization. Must be a scalar.
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| D | api_def_SparseApplyFtrl.pbtxt | 42 L1 regularization. Must be a scalar.
48 L2 regularization. Must be a scalar.
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | sdca_internal.cc | 156 const Regularizations& regularization, const int num_weight_vectors) const { in ComputeWxAndWeightedExampleNorm() argument
160 squared_norm_ / regularization.symmetric_l2(); in ComputeWxAndWeightedExampleNorm()
180 feature_value * regularization.Shrink(sparse_weight); in ComputeWxAndWeightedExampleNorm()
181 result.wx[l] += feature_value * regularization.Shrink(feature_weight); in ComputeWxAndWeightedExampleNorm()
200 regularization.EigenShrinkVector( in ComputeWxAndWeightedExampleNorm()
207 regularization.EigenShrinkVector( in ComputeWxAndWeightedExampleNorm()
217 regularization.EigenShrinkMatrix(dense_weights.nominals()) in ComputeWxAndWeightedExampleNorm()
220 regularization.EigenShrinkMatrix(feature_weights) in ComputeWxAndWeightedExampleNorm()
236 const int num_loss_partitions, const Regularizations& regularization, in SampleAdaptiveProbabilities() argument
254 model_weights, regularization, in SampleAdaptiveProbabilities()
[all …]
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
| D | gbdt_batch_test.py | 222 learner_config.regularization.l1 = 0
223 learner_config.regularization.l2 = 0
325 learner_config.regularization.l1 = 0
326 learner_config.regularization.l2 = 0
482 learner_config.regularization.l1 = 0
483 learner_config.regularization.l2 = 0
589 learner_config.regularization.l1 = 0
590 learner_config.regularization.l2 = 0
694 learner_config.regularization.l1 = 0
695 learner_config.regularization.l2 = 0
[all …]
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | factorization_ops_test.py | 176 regularization=0.01,
199 (_, process_input_op, unregularized_loss, regularization,
202 factor_loss = unregularized_loss + regularization
271 (_, process_input_op, unregularized_loss, regularization,
274 factor_loss = unregularized_loss + regularization
345 regularization=0.01,
374 (_, process_input_op, unregularized_loss, regularization,
377 factor_loss = unregularized_loss + regularization
450 (_, process_input_op, unregularized_loss, regularization,
453 factor_loss = unregularized_loss + regularization
[all …]
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| D | factorization_ops_test_utils.py | 98 def calculate_loss(input_mat, row_factors, col_factors, regularization=None, argument
122 reg = (regularization if regularization is not None
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| D | factorization_ops.py | 192 regularization=None, argument
252 self._regularization = regularization
254 regularization * linalg_ops.eye(self._n_components)
255 if regularization is not None else None)
1000 regularization = self._regularization * (
1004 regularization = constant_op.constant(0.)
1016 return (new_left_values, update_op, unregularized_loss, regularization,
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| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| D | estimator_test.py | 405 learner_config.regularization.l2 = 1.0 / _QUANTILE_REGRESSION_SIZE
406 learner_config.regularization.l1 = 1.0 / _QUANTILE_REGRESSION_SIZE
407 learner_config.regularization.tree_complexity = (
438 learner_config.regularization.l2 = 1.0 / _QUANTILE_REGRESSION_SIZE
439 learner_config.regularization.l1 = 1.0 / _QUANTILE_REGRESSION_SIZE
440 learner_config.regularization.tree_complexity = (
675 learner_config.regularization.l2 = 1.0 / _QUANTILE_REGRESSION_SIZE
676 learner_config.regularization.l1 = 1.0 / _QUANTILE_REGRESSION_SIZE
677 learner_config.regularization.tree_complexity = (
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| /external/tensorflow/tensorflow/contrib/image/python/kernel_tests/ |
| D | sparse_image_warp_test.py | 77 for regularization in (0, 0.01):
79 self.assertZeroShift(order, regularization, num_boundary_points)
81 def assertZeroShift(self, order, regularization, num_boundary_points): argument
107 regularization_weight=regularization,
|