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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 212569958
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A. Unique TensorFlower 2018-09-11 19:52:46 -07:00 committed by TensorFlower Gardener
parent 210b4d82cf
commit cadd6b42bf
1 changed files with 58 additions and 58 deletions
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116
tensorflow/go/op/wrappers.go
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@ -3456,6 +3456,36 @@ func BoostedTreesSerializeEnsemble(scope *Scope, tree_ensemble_handle tf.Output)
return op.Output(0), op.Output(1)
}
// Debugging/model interpretability outputs for each example.
//
// It traverses all the trees and computes debug metrics for individual examples,
// such as getting split feature ids and logits after each split along the decision
// path used to compute directional feature contributions.
//
// Arguments:
//
// bucketized_features: A list of rank 1 Tensors containing bucket id for each
// feature.
// logits_dimension: scalar, dimension of the logits, to be used for constructing the protos in
// examples_debug_outputs_serialized.
//
// Returns Output rank 1 Tensor containing a proto serialized as a string for each example.
func BoostedTreesExampleDebugOutputs(scope *Scope, tree_ensemble_handle tf.Output, bucketized_features []tf.Output, logits_dimension int64) (examples_debug_outputs_serialized tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{"logits_dimension": logits_dimension}
opspec := tf.OpSpec{
Type: "BoostedTreesExampleDebugOutputs",
Input: []tf.Input{
tree_ensemble_handle, tf.OutputList(bucketized_features),
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Computes the sum along sparse segments of a tensor.
//
// Like `SparseSegmentSum`, but allows missing ids in `segment_ids`. If an id is
@ -13892,34 +13922,6 @@ func SparseSoftmaxCrossEntropyWithLogits(scope *Scope, features tf.Output, label
return op.Output(0), op.Output(1)
}
// Fast Fourier transform.
//
// Computes the 1-dimensional discrete Fourier transform over the inner-most
// dimension of `input`.
//
// Arguments:
// input: A complex64 tensor.
//
// Returns A complex64 tensor of the same shape as `input`. The inner-most
// dimension of `input` is replaced with its 1D Fourier transform.
//
// @compatibility(numpy)
// Equivalent to np.fft.fft
// @end_compatibility
func FFT(scope *Scope, input tf.Output) (output tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "FFT",
Input: []tf.Input{
input,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Transforms a serialized tensorflow.TensorProto proto into a Tensor.
//
// Arguments:
@ -26636,36 +26638,6 @@ func ConcatenateDataset(scope *Scope, input_dataset tf.Output, another_dataset t
return op.Output(0)
}
// Debugging/model interpretability outputs for each example.
//
// It traverses all the trees and computes debug metrics for individual examples,
// such as getting split feature ids and logits after each split along the decision
// path used to compute directional feature contributions.
//
// Arguments:
//
// bucketized_features: A list of rank 1 Tensors containing bucket id for each
// feature.
// logits_dimension: scalar, dimension of the logits, to be used for constructing the protos in
// examples_debug_outputs_serialized.
//
// Returns Output rank 1 Tensor containing a proto serialized as a string for each example.
func BoostedTreesExampleDebugOutputs(scope *Scope, tree_ensemble_handle tf.Output, bucketized_features []tf.Output, logits_dimension int64) (examples_debug_outputs_serialized tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{"logits_dimension": logits_dimension}
opspec := tf.OpSpec{
Type: "BoostedTreesExampleDebugOutputs",
Input: []tf.Input{
tree_ensemble_handle, tf.OutputList(bucketized_features),
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Adds a value to the current value of a variable.
//
// Any ReadVariableOp with a control dependency on this op is guaranteed to
@ -28153,6 +28125,34 @@ func IteratorGetNextAsOptional(scope *Scope, iterator tf.Output, output_types []
return op.Output(0)
}
// Fast Fourier transform.
//
// Computes the 1-dimensional discrete Fourier transform over the inner-most
// dimension of `input`.
//
// Arguments:
// input: A complex64 tensor.
//
// Returns A complex64 tensor of the same shape as `input`. The inner-most
// dimension of `input` is replaced with its 1D Fourier transform.
//
// @compatibility(numpy)
// Equivalent to np.fft.fft
// @end_compatibility
func FFT(scope *Scope, input tf.Output) (output tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "FFT",
Input: []tf.Input{
input,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Performs a padding as a preprocess during a convolution.
//
// Similar to FusedResizeAndPadConv2d, this op allows for an optimized