protected void |
AbstractSession.addDependenciesForOp(String opName,
FrameIter depFrameIter) |
Suppose operation X has just been executed.
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boolean |
AbstractSession.contains(String variable,
String frame,
int iteration,
FrameIter parentFrameIter) |
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ExecutionResult |
InferenceSession.doExec(DifferentialFunction op,
OpContext opContext,
FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
Map<String,SDValue> otherPlaceHolders) |
|
SDValue |
AbstractSession.get(String variable,
String frame,
int iteration,
FrameIter parentFrameIter) |
Get a previously calculated output; throws an exception if the output does
not exist
|
SDValue |
AbstractSession.get(String variable,
String frame,
int iteration,
FrameIter parentFrameIter,
boolean enforceExistence) |
Get a previously calculated output
|
abstract O |
AbstractSession.getAndParameterizeOp(String opName,
FrameIter frameIter,
Set<AbstractSession.VarId> inputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
Map<String,T> placeholderValues,
Set<String> allReqVariables,
Map<String,SDValue> otherPlaceholders) |
Get the parameterized op to execute - for example, the
op/DifferentialFunction with all inputs set
|
Pair<SameDiffOp,OpContext> |
InferenceSession.getAndParameterizeOp(String opName,
FrameIter frameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
Map<String,INDArray> placeholderValues,
Set<String> allReqVariables,
Map<String,SDValue> otherPlaceholders) |
|
protected AbstractSession.ExecStep |
AbstractSession.getExecStepForVar(String varName,
FrameIter frameIter) |
Get the ExecStep for the given variable, given execution is happening at the
specified frame/iteration
|
abstract ExecutionResult |
AbstractSession.getOutputs(O op,
FrameIter outputFrameIter,
Set<AbstractSession.VarId> inputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables,
Map<String,SDValue> otherPlaceHolders) |
Execute the op - calculate INDArrays, or shape info, etc
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ExecutionResult |
InferenceSession.getOutputs(Pair<SameDiffOp,OpContext> opPair,
FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables,
Map<String,SDValue> otherPlaceHolders) |
|
ExecutionResult |
TrainingSession.getOutputs(Pair<SameDiffOp,OpContext> opPair,
FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Set<String> constAndPhInputs,
List<Listener> listeners,
At at,
MultiDataSet batch,
Set<String> allReqVariables,
Map<String,SDValue> otherPlaceHolders) |
|
ExecutionResult |
InferenceSession.getOutputsHelperTensorArrayOps(DifferentialFunction op,
FrameIter outputFrameIter,
Set<AbstractSession.VarId> opInputs,
Set<AbstractSession.VarId> allIterInputs,
Map<String,SDValue> otherPlaceHolders) |
Forward pass for TensorArray ops
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List<INDArray> |
AbstractSession.getTensorArraysInSession(String name,
String frame,
int iteration,
FrameIter parentFrame) |
Get the INDArray
associated with the given variable name |
protected void |
AbstractSession.updateDescendantDeps(AbstractSession.ExecStep justExecuted,
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)
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