/external/skqp/src/effects/ |
GrCircleBlurFragmentProcessor.fp | 132 uint8_t* weights = new uint8_t[numSteps]; 153 weights[i] = eval_at(evalX, circleR, halfKernel, halfKernelSize, yEvals + i); 156 weights[numSteps - 1] = 0; 157 return weights;
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/external/skqp/src/gpu/effects/ |
GrGaussianConvolutionFragmentProcessor.h | 16 * A 1D Gaussian convolution effect. The kernel is computed as an array of 2 * half-width weights.
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/external/swiftshader/third_party/LLVM/include/llvm/CodeGen/ |
CalcSpillWeights.h | 57 /// CalculateSpillWeights - Compute spill weights for all virtual register
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/common/stats/ |
node-stats.h | 141 // The node weights are -(H+l2 I)^-1 g. 200 // Copy over weights to weight_contribution. 244 // The node weights are -(Hessian_and_regularization)^-1 g. 250 // Copy over weights to weight_contribution.
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/external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
multi_head_test.py | 373 training_loss, unreduced_losses, weights, _ = multi_head.create_loss( 398 # head-weighted example weights 400 [[1.], [2.]], weights['head1'].eval(), rtol=tol, atol=tol) 402 [[4.], [6.]], weights['head2'].eval(), rtol=tol, atol=tol) 421 training_loss, unreduced_losses, weights, _ = multi_head.create_loss( 446 # head-weighted example weights 448 [[1.], [2.]], weights['head1'].eval(), rtol=tol, atol=tol) 450 [[4.], [6.]], weights['head2'].eval(), rtol=tol, atol=tol) 498 # Average over classes, sum over weights.
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/external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
gmm_test.py | 87 """Tests the shape of the weights.""" 93 weights = gmm.weights() 94 self.assertAllEqual(list(weights.shape), [self.num_centers])
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/external/tensorflow/tensorflow/contrib/keras/api/keras/applications/ |
__init__.py | 15 """Keras Applications are canned architectures with pre-trained weights."""
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/external/tensorflow/tensorflow/contrib/lite/toco/g3doc/ |
python_api.md | 47 var = tf.get_variable("weights", dtype=tf.float32, shape=(1,64,64,3))
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/external/tensorflow/tensorflow/contrib/quantize/ |
README.md | 2 model quantization of weights, biases and activations during both training and
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/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
candidate_graph_runner.h | 48 // Fills in the split in node with weights and threshold.
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/external/tensorflow/tensorflow/core/framework/ |
op_def_builder_test.cc | 442 .Output("weights: float") 446 Note that indices, ids and weights are vectors of the same size and have 447 one-to-one correspondence between their elements. ids and weights are each 450 weight is assumed to be 1.0. Also for any j, if ids[j] and weights[j] were 457 weights: vector of weight extracted from the SparseFeatures proto. 476 name: "weights" 481 description: "Note that indices, ids and weights are vectors of the same size and have\none-to-one correspondence between their elements. ids and weights are each\nobtained by sequentially concatenating sf[i].id and sf[i].weight, for i in\n1...size(sf). Note that if sf[i].weight is not set, the default value for the\nweight is assumed to be 1.0. Also for any j, if ids[j] and weights[j] were\nextracted from sf[i], then index[j] is set to i."
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/external/tensorflow/tensorflow/core/kernels/ |
variable_ops_test.cc | 39 g.NewName("VeryVeryLongRealistSoundingVariableName/weights"),
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/external/tensorflow/tensorflow/examples/android/jni/object_tracking/ |
utils.h | 239 const float* const weights, const int num_vals); 290 const float* const weights, 295 sum += values[i] * weights[i]; 296 total_weight += weights[i];
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/external/tensorflow/tensorflow/examples/udacity/ |
2_fullyconnected.ipynb | 263 " weights = tf.Variable(\n", 272 " logits = tf.matmul(tf_train_dataset, weights) + biases\n", 285 " tf.matmul(tf_valid_dataset, weights) + biases)\n", 286 " test_prediction = tf.nn.softmax(tf.matmul(tf_test_dataset, weights) + biases)" 345 " # we described in the graph: random weights for the matrix, zeros for the\n", 444 " weights = tf.Variable(\n", 449 " logits = tf.matmul(tf_train_dataset, weights) + biases\n", 459 " tf.matmul(tf_valid_dataset, weights) + biases)\n", 460 " test_prediction = tf.nn.softmax(tf.matmul(tf_test_dataset, weights) + biases)"
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/external/tensorflow/tensorflow/python/keras/_impl/keras/applications/ |
__init__.py | 15 """Keras Applications: models with automatic loading of pre-trained weights.
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/external/tensorflow/tensorflow/python/keras/applications/ |
__init__.py | 15 """Keras Applications are canned architectures with pre-trained weights."""
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/packages/apps/Launcher3/src/com/android/launcher3/ |
InvariantDeviceProfile.java | 54 // used to offset float not being able to express extremely small weights in extreme cases. 281 float weights = 0; local 292 weights += w; 295 return out.multiply(1.0f/weights);
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/prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.15-4.8/sysroot/usr/include/i386-linux-gnu/bits/ |
posix2_lim.h | 39 /* The maximum number of weights that can be assigned to an entry of
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/prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.15-4.8/sysroot/usr/include/x86_64-linux-gnu/bits/ |
posix2_lim.h | 39 /* The maximum number of weights that can be assigned to an entry of
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/system/update_engine/payload_generator/ |
cycle_breaker.h | 30 // sum of the weights of all cut cycles. In practice, it's intractable
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/external/tensorflow/tensorflow/python/keras/_impl/keras/engine/ |
training.py | 212 def _check_array_lengths(inputs, targets, weights=None): 218 weights: list of Numpy arrays of sample weights. 234 set_w = set_of_lengths(weights) 251 str([w.shape for w in weights])) 373 `fn(y_true, y_pred, weights, mask)`. 380 A function with signature `fn(y_true, y_pred, weights, mask)`. 385 def weighted(y_true, y_pred, weights, mask=None): 391 weights: Weights tensor [all...] |
/external/icu/android_icu4j/src/main/java/android/icu/impl/coll/ |
CollationBuilder.java | 243 // Collect the root CE weights if this node is for a root CE. 293 // Non-zero quaternary weights are possible only on tertiary or stronger CEs. 391 // and non-common secondary/tertiary weights. 491 // The CE data structure does not support non-zero quaternary weights 566 // Find or insert the node for each of the root CE's weights, 568 // Root CEs must have common=zero quaternary weights (for which we never insert any nodes). [all...] |
/external/icu/icu4j/main/classes/collate/src/com/ibm/icu/impl/coll/ |
CollationBuilder.java | 239 // Collect the root CE weights if this node is for a root CE. 289 // Non-zero quaternary weights are possible only on tertiary or stronger CEs. 387 // and non-common secondary/tertiary weights. 487 // The CE data structure does not support non-zero quaternary weights 562 // Find or insert the node for each of the root CE's weights, 564 // Root CEs must have common=zero quaternary weights (for which we never insert any nodes). [all...] |
/frameworks/ml/nn/runtime/test/ |
TestPartitioningRandom.cpp | 57 // (1) Randomly generate a model (graph and weights), randomly generate input 73 // For simplicity, all data (model inputs, model outputs, weights, 120 // note that the API promotes by-value weights larger than 128 to by-reference, 131 // Force all graph weights into a single pool (as we recommend to users) 134 // Forcing all graph weights into a single pool may be necessary to 578 // Each region in weights is a problem-sized 2-D TENSOR_FLOAT32. 579 TestMemories weights; local 586 // region index in "weights" 774 if ((weights.memoryCount() != 0) && 776 memoryIndex = randUInt(weights.memoryCount()) [all...] |
/external/clang/lib/CodeGen/ |
CodeGenPGO.cpp | 823 /// \brief Calculate what to divide by to scale weights. 826 /// weights to strictly less than UINT32_MAX. 849 // Check for empty weights. 862 CodeGenFunction::createProfileWeights(ArrayRef<uint64_t> Weights) { 863 // We need at least two elements to create meaningful weights. 864 if (Weights.size() < 2) 867 // Check for empty weights. 868 uint64_t MaxWeight = *std::max_element(Weights.begin(), Weights.end()); 876 ScaledWeights.reserve(Weights.size()) [all...] |