From cadd6b42bf6b01c2668420463b0986acd7fd9009 Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Tue, 11 Sep 2018 19:52:46 -0700 Subject: Go: Update generated wrapper functions for TensorFlow ops. PiperOrigin-RevId: 212569958 --- tensorflow/go/op/wrappers.go | 116 +++++++++++++++++++++---------------------- 1 file changed, 58 insertions(+), 58 deletions(-) (limited to 'tensorflow/go') diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go index e755c37039..322b35dd91 100644 --- a/tensorflow/go/op/wrappers.go +++ b/tensorflow/go/op/wrappers.go @@ -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 -- cgit v1.2.3