| /external/tensorflow/tensorflow/python/kernel_tests/ |
| embedding_ops_test.py | 189 weights = []
228 weights.append(weight_aggregation)
231 weights = np.array(weights).astype(np.float32)
233 return values, weights, weights_squared
621 weights = 1 + np.random.rand(num_vals)
636 constant_op.constant(weights, dtypes.float32),
639 return sp_ids, sp_weights, ids, weights, vals_per_batch_entry
655 sp_ids, sp_weights, ids, weights, vals_per_batch_entry = (
659 grouped_weights = self._GroupByBatchEntry(weights, vals_per_batch_entry
[all...] |
| /external/opencv/cvaux/include/ |
| cvaux.h | 123 float* weight; /*array of mixture weights. Summ of all weights in state is 1. */
201 /* Function calculates means, variances, weights of every Gaussian mixture
361 // CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
366 // weights of vertices must be provided. If weight_vtx not zero
367 // these weights considered to be here, otherwise function assumes
371 // weights of edges ought to be supplied. If weight_edge is not zero
400 // CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
405 // weights of vertices must be provided. If weight_vtx not zero
406 // these weights considered to be here, otherwise function assume
[all...] |
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/ |
| prediction_ops_test.py | 581 # This test is when leafs have SPARSE weights stored (class id and
632 # This test is when leafs have DENSE weights stored (weight for each class)
684 # Add 1000 trees with some weights.
721 # we can check here the weights for dropped trees.
747 # Add 10 trees with some weights.
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/ |
| README.md | 102 weights = slim.variable('weights',
132 weights = slim.model_variable('weights',
174 2. Convolving the weights with the input from the previous layer
184 stddev=1e-1), name='weights')
416 of the model weights relative to the loss and updates the weights accordingly.
685 # Assuming than 'conv1/weights' should be restored from 'vgg16/conv1/weights'
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| dnn_linear_combined_test.py | 619 """Tests loss calculation with weights."""
633 # 4 rows, with different weights.
[all...] |
| /external/skia/include/core/ |
| SkPath.h | 58 /** By default, SkPath has no verbs, no SkPoint, and no weights.
67 and weights are copied when modified.
83 shares pointer values. The underlying verb array, SkPoint array and weights
90 @param path verb array, SkPoint array, weights, and SkPath::FillType to copy
95 /** Compares a and b; returns true if SkPath::FillType, verb array, SkPoint array, and weights
104 /** Compares a and b; returns true if SkPath::FillType, verb array, SkPoint array, and weights
115 /** Return true if SkPath contain equal verbs and equal weights.
116 If SkPath contain one or more conics, the weights must match.
123 @return true if SkPath verb array and weights are equivalent
128 Copy verb array and weights to out, and set out SkPoint array to a weighte
[all...] |
| /external/skia/src/core/ |
| SkPathRef.cpp | 16 // Conic weights must be 0 < weight <= finite
17 static bool validate_conic_weights(const SkScalar weights[], int count) {
19 if (weights[i] <= 0 || !SkScalarIsFinite(weights[i])) {
506 SkScalar** weights) {
576 SkASSERT(weights);
577 *weights = fConicWeights.append(numVbs);
|
| /external/skqp/include/core/ |
| SkPath.h | 58 /** By default, SkPath has no verbs, no points, and no weights.
67 and weights are copied when modified.
83 shares pointer values. The underlying verb array, SkPoint array and weights
90 @param path verb array, SkPoint array, weights, and SkPath::FillType to copy
95 /** Compares a and b; returns true if SkPath::FillType, verb array, SkPoint array, and weights
104 /** Compares a and b; returns true if SkPath::FillType, verb array, SkPoint array, and weights
115 /** Return true if paths contain equal verbs and equal weights.
116 If paths contain one or more conics, the weights must match.
123 @return true if paths verb array and weights are equivalent
128 Copy verb array and weights to out, and set out SkPoint array to a weighte
[all...] |
| /external/skqp/src/core/ |
| SkPathRef.cpp | 16 // Conic weights must be 0 < weight <= finite
17 static bool validate_conic_weights(const SkScalar weights[], int count) {
19 if (weights[i] <= 0 || !SkScalarIsFinite(weights[i])) {
490 SkScalar** weights) {
560 SkASSERT(weights);
561 *weights = fConicWeights.append(numVbs);
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| random_forest.py | 152 weights = None
154 weights = features.pop(weights_name)
190 features, labels, input_weights=weights,
195 # Put weights back in
196 if weights is not None:
197 features[weights_name] = weights
325 weights. Will be multiplied by the loss of the example. Used to
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| training.py | 49 (a) computes the loss, (b) applies the gradients to update the weights and
64 'conv0/weights': 1.2,
65 'fc8/weights': 3.4,
184 Rather than initializing all of the weights of a given model, we sometimes
185 only want to restore some of the weights from a checkpoint. To do this, one
214 One may want to initialize the weights of a model from values coming from an
217 weights being stored in the graph. For large models, this becomes prohibitively
|
| /hardware/interfaces/neuralnetworks/1.0/ |
| types.hal | 492 * outputs = activation(inputs * weights? + bias)
506 * weights, and "batch_size" is calculated by dividing the number of
508 * * 1: A 2-D tensor, specifying the weights, of shape
[all...] |
| /external/python/cpython3/Lib/ |
| random.py | 340 def choices(self, population, weights=None, *, cum_weights=None, k=1):
343 If the relative weights or cumulative weights are not specified,
349 if weights is None:
353 cum_weights = list(_itertools.accumulate(weights))
354 elif weights is not None:
355 raise TypeError('Cannot specify both weights and cumulative weights')
357 raise ValueError('The number of weights does not match the population')
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/kernels/ |
| training_ops.cc | 394 // weights of dropped and the last tree.
489 // weights didn't change.
490 std::vector<float> weights = ensemble_resource->GetTreeWeights(); local
494 dropout_seed, dropout_config_, trees_not_to_drop, weights,
500 // Now we have dropped trees, update their weights and the current tree
506 1 /* only 1 tree was added */, &weights, &increment_num_updates);
508 // Update the weights and num of updates for trees.
510 ensemble_resource->SetTreeWeight(i, weights[i],
552 // Helper method to merge leaf weights as the tree is being grown.
[all...] |
| /external/icu/icu4c/source/i18n/ |
| collationdatareader.h | 241 * The rootElements may contain secondary and tertiary weights below common=05.
243 * Where is occurs, there is also an explicit unit with common secondary & tertiary weights.
247 * does not necessarily have special, unique secondary/tertiary weights any more.
|
| /external/llvm/include/llvm/IR/ |
| MDBuilder.h | 57 /// \brief Return metadata containing two branch weights.
60 /// \brief Return metadata containing a number of branch weights.
61 MDNode *createBranchWeights(ArrayRef<uint32_t> Weights);
|
| /external/mesa3d/src/intel/common/ |
| gen_l3_config.c | 127 * L1-normalize a vector of L3 partition weights.
144 * Get the relative partition weights of the specified L3 configuration.
163 * Distance between two L3 configurations represented as vectors of weights.
|
| /external/tensorflow/tensorflow/core/protobuf/ |
| meta_graph.proto | 172 // value: "\n\017conv1/weights:0\022\024conv1/weights/Assign
173 // \032\024conv1/weights/read:0"
|
| /external/tensorflow/tensorflow/docs_src/tutorials/ |
| linear.md | 29 work for a population, a model can learn weights for each of those numbers so that
50 You can examine the weights assigned to each feature to figure out what's
119 Because linear models assign independent weights to separate features, they
|
| /external/tensorflow/tensorflow/python/feature_column/ |
| feature_column.py | 331 def weights(self): member in class:InputLayer
332 return self._input_layer_template.weights
391 [<tf.Variable 'linear_model/price2/weights:0' shape=(1, 1)>],
395 [<tf.Variable 'linear_model/price1/weights:0' shape=(2, 1)>]}
625 restore column weights. Required if `tensor_name_in_ckpt` is not `None`.
627 which to restore the column weights. Required if `ckpt_to_load_from` is
675 embedding columns that share the same embedding weights.
743 shared embedding weights are added. If not given, a reasonable name will
745 in `variable_scope` when creating shared embedding weights.
747 restore column weights. Required if `tensor_name_in_ckpt` is not `None`
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| advanced_activations.py | 89 alpha_initializer: initializer function for the weights.
90 alpha_regularizer: regularizer for the weights.
91 alpha_constraint: constraint for the weights.
|
| /external/trappy/trappy/ |
| plot_utils.py | 252 # Do nothing if we don't have actor weights for any run
262 for ax, run, weights in zip(axis, runs, actor_weights):
263 run.thermal_governor.plot_weighted_input_power(weights, title=run.name,
|
| /frameworks/ml/nn/runtime/include/ |
| NeuralNetworks.h | 516 * outputs = activation(inputs * weights? + bias)
530 * weights, and "batch_size" is calculated by dividing the number of
532 * * 1: A 2-D tensor, specifying the weights, of shape
[all...] |
| /prebuilts/clang/host/darwin-x86/clang-4053586/prebuilt_include/llvm/include/llvm/IR/ |
| MDBuilder.h | 59 /// \brief Return metadata containing two branch weights.
62 /// \brief Return metadata containing a number of branch weights.
63 MDNode *createBranchWeights(ArrayRef<uint32_t> Weights);
|
| /prebuilts/clang/host/darwin-x86/clang-4393122/include/llvm/IR/ |
| MDBuilder.h | 59 /// \brief Return metadata containing two branch weights.
62 /// \brief Return metadata containing a number of branch weights.
63 MDNode *createBranchWeights(ArrayRef<uint32_t> Weights);
|
