| /external/tensorflow/tensorflow/contrib/kfac/ |
| README.md | 22 are the weights for layer i?"). As such, you must add some additional code while
52 1. Registering layer inputs, weights, and pre-activations with a
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
| ops_test.py | 39 weights = constant_op.constant([[0.1, 0.1], [0.1, 0.1], [0.1, 0.1]])
42 prediction, loss = ops.softmax_classifier(features, labels, weights,
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| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| create_im2col_arrays.cc | 40 // We need to yield until weights dims have been resolved, because
41 // from the weights dims we determine whether an im2col array is
|
| lstm_utils.h | 86 // mostly used for spliting weights and bias for Lstm cell.
93 // mostly used for merging weights and bias for Lstm cell.
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| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| input_target.h | 25 // Base class for classes that hold labels and weights. Mostly for testing
51 // Holds labels/targets and weights. Assumes that tensors are passed as
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| /external/tensorflow/tensorflow/core/kernels/ |
| bincount_op_test.cc | 36 Tensor weights(DT_INT32, TensorShape({0}));
42 .Input(test::graph::Constant(g, weights))
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| bincount_op.h | 33 const typename TTypes<T, 1>::ConstTensor& weights,
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/applications/ |
| imagenet_utils.py | 253 weights=None):
264 weights: One of `None` (random initialization)
266 If weights='imagenet' input channels must be equal to 3.
274 if weights != 'imagenet' and input_shape and len(input_shape) == 3:
292 if weights == 'imagenet' and require_flatten:
296 'and loading `imagenet` weights, '
304 if input_shape[0] != 3 and weights == 'imagenet':
316 if input_shape[-1] != 3 and weights == 'imagenet':
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| local.py | 38 the `Conv1D` layer, except that weights are unshared,
69 kernel_initializer: Initializer for the `kernel` weights matrix.
72 the `kernel` weights matrix.
203 to the `Conv2D` layer, except that weights are unshared,
209 # apply a 3x3 unshared weights convolution with 64 output filters on a
218 # add a 3x3 unshared weights convolution on top, with 32 output filters:
250 kernel_initializer: Initializer for the `kernel` weights matrix.
253 the `kernel` weights matrix.
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| /frameworks/base/media/mca/filterpacks/java/android/filterpacks/imageproc/ |
| SepiaFilter.java | 103 float weights[] = { 805.0f / 2048.0f, 715.0f / 2048.0f, 557.0f / 2048.0f, local
106 mProgram.setHostValue("matrix", weights);
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| /frameworks/base/packages/SystemUI/src/com/android/systemui/classifier/ |
| HistoryEvaluator.java | 80 // All weights are multiplied by HISTORY_FACTOR after each INTERVAL milliseconds.
94 // Removing evaluations with such small weights that they do not matter anymore
|
| /frameworks/rs/tests/java_api/ImageProcessing/src/com/android/rs/image/ |
| threshold.rs | 35 // Compute gaussian weights for the blur
65 //Now we need to normalize the weights because all our coefficients need to add up to one
|
| /frameworks/rs/tests/java_api/ImageProcessing2/src/com/android/rs/image/ |
| threshold.rs | 35 // Compute gaussian weights for the blur
65 //Now we need to normalize the weights because all our coefficients need to add up to one
|
| /frameworks/rs/tests/java_api/ImageProcessing_jb/src/com/android/rs/image/ |
| threshold.rs | 35 // Compute gaussian weights for the blur
65 //Now we need to normalize the weights because all our coefficients need to add up to one
|
| threshold_half.rs | 35 // Compute gaussian weights for the blur
65 //Now we need to normalize the weights because all our coefficients need to add up to one
|
| /packages/apps/Dialer/java/com/android/incallui/answer/impl/classifier/ |
| HistoryEvaluator.java | 77 // All weights are multiplied by HISTORY_FACTOR after each INTERVAL milliseconds.
91 // Removing evaluations with such small weights that they do not matter anymore
|
| /external/deqp/framework/delibs/decpp/ |
| deRandom.cpp | 147 // chooseWeighted(first, last, weights)
151 static const float weights[] = { 0.4f, 0.6f, 1.5f, 0.5f, 1.2f, 0.3f, 0.2f, 1.4f };
152 DE_STATIC_ASSERT(DE_LENGTH_OF_ARRAY(items) == DE_LENGTH_OF_ARRAY(weights));
157 DE_TEST_ASSERT(expected[i] == rnd.chooseWeighted<int>(DE_ARRAY_BEGIN(items), DE_ARRAY_END(items), &weights[0]));
|
| /external/fio/tools/ |
| fiologparser.py | 139 weights = []
145 weights.append(end-start)
151 total += averages[i]*weights[i]
152 print('%0.3f' % (total/sum(weights)))
|
| /external/llvm/lib/Transforms/Scalar/ |
| LowerExpectIntrinsic.cpp | 72 SmallVector<uint32_t, 16> Weights(n + 1, UnlikelyBranchWeight);
75 Weights[0] = LikelyBranchWeight;
77 Weights[Case.getCaseIndex() + 1] = LikelyBranchWeight;
80 MDBuilder(CI->getContext()).createBranchWeights(Weights));
|
| /external/swiftshader/third_party/LLVM/lib/CodeGen/ |
| MachineBasicBlock.cpp | 344 // list, so we fill all Weights with 0's.
345 if (weight != 0 && Weights.empty())
346 Weights.resize(Successors.size());
348 if (weight != 0 || !Weights.empty())
349 Weights.push_back(weight);
361 if (!Weights.empty()) {
363 Weights.erase(WI);
374 if (!Weights.empty()) {
376 Weights.erase(WI);
389 if (!Weights.empty())
[all...] |
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/training/functions/ |
| gbdt_batch_test.py | 187 weights = array_ops.ones([4, 1], dtypes.float32)
191 _squared_loss(labels, weights, predictions)),
291 weights = array_ops.ones([4, 1], dtypes.float32)
295 _squared_loss(labels, weights, predictions)),
394 weights = array_ops.ones([4, 1], dtypes.float32)
398 _squared_loss(labels, weights, predictions)),
464 weights = array_ops.ones([4, 1], dtypes.float32)
468 _squared_loss(labels, weights, predictions)),
527 weights = array_ops.ones([4, 1], dtypes.float32)
531 _squared_loss(labels, weights, predictions))
[all...] |
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| estimator.py | 55 weights. It is used to down weight or boost examples during training. It
103 weights. It is used to down weight or boost examples during training. It
132 def loss_fn(labels, logits, weights=None):
144 weight=weights)
|
| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| clip_weights.py | 15 """Utilities to clip weights."""
|
| /external/tensorflow/tensorflow/contrib/lite/kernels/internal/ |
| kernel_utils.h | 24 // The RNN cell is specified by the pointers to its input and recurrent weights,
|
| /external/tensorflow/tensorflow/core/grappler/inputs/ |
| file_input_yielder.h | 17 // graphs stored in TensorFlow checkpoints. Note that at this point the weights
|
