BoostedTreesMakeStatsSummary

public final class BoostedTreesMakeStatsSummary

Makes the summary of accumulated stats for the batch.

The summary stats contains gradients and hessians accumulated into the corresponding node and bucket for each example.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output < TFloat32 >
asOutput ()
Returns the symbolic handle of the tensor.
static BoostedTreesMakeStatsSummary
create ( Scope scope, Operand < TInt32 > nodeIds, Operand < TFloat32 > gradients, Operand < TFloat32 > hessians, Iterable< Operand < TInt32 >> bucketizedFeaturesList, Long maxSplits, Long numBuckets)
Factory method to create a class wrapping a new BoostedTreesMakeStatsSummary operation.
Output < TFloat32 >
statsSummary ()
output Rank 4 Tensor (shape=[#features, #splits, #buckets, 2]) containing accumulated stats put into the corresponding node and bucket.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "BoostedTreesMakeStatsSummary"

Public Methods

public Output < TFloat32 > asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static BoostedTreesMakeStatsSummary create ( Scope scope, Operand < TInt32 > nodeIds, Operand < TFloat32 > gradients, Operand < TFloat32 > hessians, Iterable< Operand < TInt32 >> bucketizedFeaturesList, Long maxSplits, Long numBuckets)

Factory method to create a class wrapping a new BoostedTreesMakeStatsSummary operation.

Parameters
scope current scope
nodeIds int32 Rank 1 Tensor containing node ids, which each example falls into for the requested layer.
gradients float32; Rank 2 Tensor (shape=[#examples, 1]) for gradients.
hessians float32; Rank 2 Tensor (shape=[#examples, 1]) for hessians.
bucketizedFeaturesList int32 list of Rank 1 Tensors, each containing the bucketized feature (for each feature column).
maxSplits int; the maximum number of splits possible in the whole tree.
numBuckets int; equals to the maximum possible value of bucketized feature.
Returns
  • a new instance of BoostedTreesMakeStatsSummary

public Output < TFloat32 > statsSummary ()

output Rank 4 Tensor (shape=[#features, #splits, #buckets, 2]) containing accumulated stats put into the corresponding node and bucket. The first index of 4th dimension refers to gradients, and the second to hessians.