List of forEach() Examples

Examples of forEach()

com.android.dx.cf.code.BytecodeArray.forEach()
Parses each instruction in the array, in order. @param visitor {@code null-ok;} visitor to call back to for each instruction
com.carrotsearch.hppc.CharIntOpenHashMap.forEach()
{@inheritDoc}
com.carrotsearch.hppc.IntArrayDeque.forEach()
{@inheritDoc}
com.carrotsearch.hppc.IntArrayList.forEach()
{@inheritDoc}
com.carrotsearch.hppc.IntCharOpenHashMap.forEach()
{@inheritDoc}
com.carrotsearch.hppc.IntIntOpenHashMap.forEach()
{@inheritDoc}
com.carrotsearch.hppc.IntOpenHashSet.forEach()
{@inheritDoc}
com.fasterxml.jackson.databind.node.ArrayNode.forEach()
com.github.neuralnetworks.tensor.Tensor.forEach()
Iterate over all indexes @param action
com.goodow.realtime.json.JsonArray.forEach()
com.sun.codemodel.JBlock.forEach()
Creates an enhanced For statement based on j2se 1.5 JLS and add it to this block @return Newly generated enhanced For statement per j2se 1.5specification
com.volantis.mcs.dom.NodeSequence.forEach()
Iterate over the nodes within the sequence, calling the supplied iteratee for each one.
This is an application of the Internal Iterator pattern in the GOF book.

The nodes being iterated over can be safely modified in the following ways, all other modifications have undefined behaviour:
- Node can be removed.
- Node can be changed.
- Nodes can be inserted immediately before and immediately after the node. The inserted nodes will not be iterated over during this iteration.
@param nodeIteratee called for each node within this sequence.
com.volantis.mcs.dom.impl.NodeSequenceImpl.forEach()
gnu.trove.TIntArrayList.forEach()
Applies the procedure to each value in the list in ascending (front to back) order. @param procedure a TIntProcedure value @return true if the procedure did not terminate prematurely.
gnu.trove.TLongCollection.forEach()
Executes procedure for each element in the collection. @param procedure a TLongProcedure value @return false if the loop over the collection terminated becausethe procedure returned false for some value.
gnu.trove.list.TIntList.forEach()
Applies the procedure to each value in the list in ascending (front to back) order. @param procedure a TIntProcedure value @return true if the procedure did not terminate prematurely.
gnu.trove.list.array.TIntArrayList.forEach()
{@inheritDoc}
gnu.trove.set.TIntSet.forEach()
Executes procedure for each element in the set. @param procedure a TIntProcedure value @return false if the loop over the set terminated becausethe procedure returned false for some value.
gnu.trove.set.TLongSet.forEach()
Executes procedure for each element in the set. @param procedure a TLongProcedure value @return false if the loop over the set terminated becausethe procedure returned false for some value.
gnu.trove.set.hash.TLongHashSet.forEach()
java.util.Properties.forEach()
org.jboss.errai.codegen.builder.ContextualStatementBuilder.foreach()
org.jsoup.select.Elements.forEach()

Examples of com.github.neuralnetworks.tensor.Tensor.forEach()

  float[] e6 = t.getElements();
  t.forEach(i -> e6[i] = 0.5f);


  t = ((FullyConnected) secondAE.getConnection(secondAE.getHiddenLayer(), secondAE.getOutputLayer())).getWeights();
  float[] e7 = t.getElements();
  t.forEach(i -> e7[i] = 0.7f);


  t = ((FullyConnected) secondAE.getConnection(secondAE.getOutputBiasLayer(), secondAE.getOutputLayer())).getWeights();
  float[] e8 = t.getElements();
  t.forEach(i -> e8[i] = 0.9f);

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()

  float[] e7 = t.getElements();
  t.forEach(i -> e7[i] = 0.7f);


  t = ((FullyConnected) secondAE.getConnection(secondAE.getOutputBiasLayer(), secondAE.getOutputLayer())).getWeights();
  float[] e8 = t.getElements();
  t.forEach(i -> e8[i] = 0.9f);


  Set<Layer> calculatedLayers = new HashSet<>();
  calculatedLayers.add(sae.getInputLayer());


  ValuesProvider results = TensorFactory.tensorProvider(sae, 1, true);

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()

    }


    @Override
    public void calculate(List<Connections> connections, ValuesProvider valuesProvider, Layer targetLayer) {
  Tensor t = TensorFactory.tensor(targetLayer, connections, valuesProvider);
  t.forEach(i -> t.getElements()[i] = value);
    }


    public float getValue() {
        return value;
    }

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()


    protected void calculateBias(Conv2DConnection bias, ValuesProvider vp) {
  if (bias != null) {
      Tensor biasValue = TensorFactory.tensor(bias.getInputLayer(), bias, vp);
      if (biasValue.getElements()[biasValue.getStartIndex()] == 0) {
    biasValue.forEach(i -> biasValue.getElements()[i] = 1);
      }


      Tensor v = TensorFactory.tensor(bias.getOutputLayer(), bias, vp);
      Tensor w = bias.getWeights();
      TensorIterator it = v.iterator();

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()


  for (Layer l : nn.getLayers()) {
      if (Util.isBias(l)) {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertEquals(0.5, elements[i], 0f));
      } else {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= -0.1f && elements[i] <= 0.1f && elements[i] != 0));
      }

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()

    float[] elements = t.getElements();
    t.forEach(i -> assertEquals(0.5, elements[i], 0f));
      } else {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= -0.1f && elements[i] <= 0.1f && elements[i] != 0));
      }
  }


  rand = new NNRandomInitializer(new MersenneTwisterRandomInitializer(2f, 3f), new MersenneTwisterRandomInitializer(-2f, -1f));
  rand.initialize(nn);

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()


  for (Layer l : nn.getLayers()) {
      if (Util.isBias(l)) {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= -2f && elements[i] <= -1f));
      } else {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= 2f && elements[i] <= 3f));
      }

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()

    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= -2f && elements[i] <= -1f));
      } else {
    Tensor t = ((FullyConnected) l.getConnections().get(0)).getWeights();
    float[] elements = t.getElements();
    t.forEach(i -> assertTrue(elements[i] >= 2f && elements[i] <= 3f));
      }
  }
    }


    @Test

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Examples of com.github.neuralnetworks.tensor.Tensor.forEach()


    protected void calculateBias(Connections bias, ValuesProvider valuesProvider) {
  if (bias != null) {
      Tensor biasValue = TensorFactory.tensor(bias.getInputLayer(), bias, valuesProvider);
      if (biasValue.get(new int[biasValue.getDimensions().length]) == 0) {
    biasValue.forEach(i -> biasValue.getElements()[i] = 1);
      }


      Matrix weights = ((FullyConnected) bias).getWeights();
      Matrix output = TensorFactory.tensor(bias.getOutputLayer(), bias, valuesProvider);

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Examples of com.goodow.realtime.json.JsonArray.forEach()

            components.push(component.toJson());
          }
        }
      }
    });
    components.forEach(new ListIterator<JsonElement>() {
      @Override
      public void call(int index, JsonElement component) {
        createComponents.push(component);
      }
    });

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