Package | Description |
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org.nd4j.autodiff.samediff.internal |
Modifier and Type | Field and Description |
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protected AbstractSession.FrameIter |
AbstractSession.ExecStepPredicate.currParentFrame |
protected AbstractSession.FrameIter |
AbstractSession.ExecStep.frameIter |
protected AbstractSession.FrameIter |
InferenceSession.Dep.parentFrame |
Modifier and Type | Method and Description |
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AbstractSession.FrameIter |
AbstractSession.FrameIter.clone() |
AbstractSession.FrameIter |
AbstractSession.VarId.toFrameIter() |
Modifier and Type | Method and Description |
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protected void |
AbstractSession.addDependenciesForOp(String opName,
AbstractSession.FrameIter depFrameIter)
Suppose operation X has just been executed.
|
boolean |
AbstractSession.contains(String variable,
String frame,
int iteration,
AbstractSession.FrameIter parentFrameIter) |
INDArray[] |
InferenceSession.doExec(DifferentialFunction op,
AbstractSession.FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs) |
T |
AbstractSession.get(String variable,
String frame,
int iteration,
AbstractSession.FrameIter parentFrameIter)
Get a previously calculated output; throws an exception if the output does not exist
|
T |
AbstractSession.get(String variable,
String frame,
int iteration,
AbstractSession.FrameIter parentFrameIter,
boolean enforceExistence)
Get a previously calculated output
|
SameDiffOp |
InferenceSession.getAndParameterizeOp(String opName,
AbstractSession.FrameIter frameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
Map<String,INDArray> placeholderValues,
Set<String> allReqVariables) |
abstract O |
AbstractSession.getAndParameterizeOp(String opName,
AbstractSession.FrameIter frameIter,
Set<AbstractSession.VarId> inputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
Map<String,T> placeholderValues,
Set<String> allReqVariables)
Get the parameterized op to execute - for example, the op/DifferentialFunction with all inputs set
|
protected AbstractSession.ExecStep |
AbstractSession.getExecStepForVar(String varName,
AbstractSession.FrameIter frameIter)
Get the ExecStep for the given variable, given execution is happening at the specified frame/iteration
|
abstract T[] |
AbstractSession.getOutputs(O op,
AbstractSession.FrameIter outputFrameIter,
Set<AbstractSession.VarId> inputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables)
Execute the op - calculate INDArrays, or shape info, etc
|
INDArray[] |
TrainingSession.getOutputs(SameDiffOp op,
AbstractSession.FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables) |
INDArray[] |
InferenceSession.getOutputs(SameDiffOp op,
AbstractSession.FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables) |
INDArray[] |
InferenceSession.getOutputsHelperTensorArrayOps(DifferentialFunction op,
AbstractSession.FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs)
Forward pass for TensorArray ops
|
protected void |
AbstractSession.updateDescendantDeps(AbstractSession.ExecStep justExecuted,
AbstractSession.FrameIter outFrameIter)
Update the descendant dependencies
So if the graph structure is X -> A, then add all (X,Y,Z,...) -> A to the dependency tracker
This is for a specific frame and iteration, for both sides of the dependency (in and out)
|
Constructor and Description |
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ExecStep(AbstractSession.ExecType execType,
String name,
AbstractSession.FrameIter frameIter) |
OpDep(String opName,
String frame,
int iter,
AbstractSession.FrameIter parentFrame) |
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