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  /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;
  /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.
  /external/swiftshader/third_party/LLVM/include/llvm/CodeGen/
CalcSpillWeights.h 57 /// CalculateSpillWeights - Compute spill weights for all virtual register
  /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.
  /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.
  /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])
  /external/tensorflow/tensorflow/contrib/keras/api/keras/applications/
__init__.py 15 """Keras Applications are canned architectures with pre-trained weights."""
  /external/tensorflow/tensorflow/contrib/lite/toco/g3doc/
python_api.md 47 var = tf.get_variable("weights", dtype=tf.float32, shape=(1,64,64,3))
  /external/tensorflow/tensorflow/contrib/quantize/
README.md 2 model quantization of weights, biases and activations during both training and
  /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/
candidate_graph_runner.h 48 // Fills in the split in node with weights and threshold.
  /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."
  /external/tensorflow/tensorflow/core/kernels/
variable_ops_test.cc 39 g.NewName("VeryVeryLongRealistSoundingVariableName/weights"),
  /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];
  /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)"
  /external/tensorflow/tensorflow/python/keras/_impl/keras/applications/
__init__.py 15 """Keras Applications: models with automatic loading of pre-trained weights.
  /external/tensorflow/tensorflow/python/keras/applications/
__init__.py 15 """Keras Applications are canned architectures with pre-trained weights."""
  /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);
  /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
  /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
  /system/update_engine/payload_generator/
cycle_breaker.h 30 // sum of the weights of all cut cycles. In practice, it's intractable
  /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
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  /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).
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  /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).
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  /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())
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  /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())
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