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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 359677943
Change-Id: Ie9bf30af7452d2e7844e266a79aae97e7e8d2c5b
This commit is contained in:
A. Unique TensorFlower 2021-02-25 20:46:14 -08:00 committed by TensorFlower Gardener
parent bfbedbe71f
commit cc8896a755
1 changed files with 0 additions and 161 deletions
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161
tensorflow/go/op/wrappers.go
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@ -3764,123 +3764,6 @@ func BoostedTreesEnsembleResourceHandleOp(scope *Scope, optional ...BoostedTrees
return op.Output(0) return op.Output(0)
} }
// Deserializes a proto into the tree handle
//
// Arguments:
// tree_handle: Handle to the tree resource to be restored.
// tree_config: Serialied proto string of the boosted_trees.Tree proto.
//
// Returns the created operation.
func TensorForestTreeDeserialize(scope *Scope, tree_handle tf.Output, tree_config tf.Output) (o *tf.Operation) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "TensorForestTreeDeserialize",
Input: []tf.Input{
tree_handle, tree_config,
},
}
return scope.AddOperation(opspec)
}
// Serializes the tree handle to a proto
//
// Arguments:
// tree_handle: Handle to the tree resource to be serialized.
//
// Returns Serialied proto string of the tree resource.
func TensorForestTreeSerialize(scope *Scope, tree_handle tf.Output) (tree_config tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "TensorForestTreeSerialize",
Input: []tf.Input{
tree_handle,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Creates a tree resource and returns a handle to it.
//
// Arguments:
// tree_handle: Handle to the tree resource to be created.
// tree_config: Serialized proto string of the boosted_trees.Tree.
//
// Returns the created operation.
func TensorForestCreateTreeVariable(scope *Scope, tree_handle tf.Output, tree_config tf.Output) (o *tf.Operation) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "TensorForestCreateTreeVariable",
Input: []tf.Input{
tree_handle, tree_config,
},
}
return scope.AddOperation(opspec)
}
// Checks whether a tree has been initialized.
//
// Arguments:
// tree_handle: Handle to the tree.
//
// Returns Whether the tree is initialized.
func TensorForestTreeIsInitializedOp(scope *Scope, tree_handle tf.Output) (is_initialized tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "TensorForestTreeIsInitializedOp",
Input: []tf.Input{
tree_handle,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// TensorForestTreeResourceHandleOpAttr is an optional argument to TensorForestTreeResourceHandleOp.
type TensorForestTreeResourceHandleOpAttr func(optionalAttr)
// TensorForestTreeResourceHandleOpContainer sets the optional container attribute to value.
// If not specified, defaults to ""
func TensorForestTreeResourceHandleOpContainer(value string) TensorForestTreeResourceHandleOpAttr {
return func(m optionalAttr) {
m["container"] = value
}
}
// TensorForestTreeResourceHandleOpSharedName sets the optional shared_name attribute to value.
// If not specified, defaults to ""
func TensorForestTreeResourceHandleOpSharedName(value string) TensorForestTreeResourceHandleOpAttr {
return func(m optionalAttr) {
m["shared_name"] = value
}
}
// Creates a handle to a TensorForestTreeResource
func TensorForestTreeResourceHandleOp(scope *Scope, optional ...TensorForestTreeResourceHandleOpAttr) (resource tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "TensorForestTreeResourceHandleOp",
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// AllCandidateSamplerAttr is an optional argument to AllCandidateSampler. // AllCandidateSamplerAttr is an optional argument to AllCandidateSampler.
type AllCandidateSamplerAttr func(optionalAttr) type AllCandidateSamplerAttr func(optionalAttr)
@ -9914,30 +9797,6 @@ func DecodeProtoV2(scope *Scope, bytes tf.Output, message_type string, field_nam
return sizes, values return sizes, values
} }
// Output the logits for the given input data
//
// Arguments:
// tree_handle: Handle to the tree resource.
// dense_features: Rank 2 dense features tensor.
// logits_dimension: Scalar, dimension of the logits.
//
// Returns The logits predictions from the tree for each instance in the batch.
func TensorForestTreePredict(scope *Scope, tree_handle tf.Output, dense_features tf.Output, logits_dimension int64) (logits tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{"logits_dimension": logits_dimension}
opspec := tf.OpSpec{
Type: "TensorForestTreePredict",
Input: []tf.Input{
tree_handle, dense_features,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// EncodeProtoAttr is an optional argument to EncodeProto. // EncodeProtoAttr is an optional argument to EncodeProto.
type EncodeProtoAttr func(optionalAttr) type EncodeProtoAttr func(optionalAttr)
@ -32687,26 +32546,6 @@ func DeserializeManySparse(scope *Scope, serialized_sparse tf.Output, dtype tf.D
return op.Output(0), op.Output(1), op.Output(2) return op.Output(0), op.Output(1), op.Output(2)
} }
// Get the number of nodes in a tree
//
// Arguments:
// tree_handle: Handle to the tree resource.
//
// Returns The size of the tree.
func TensorForestTreeSize(scope *Scope, tree_handle tf.Output) (tree_size tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "TensorForestTreeSize",
Input: []tf.Input{
tree_handle,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Subtracts sparse updates from the variable referenced by `resource`. // Subtracts sparse updates from the variable referenced by `resource`.
// //
// This operation computes // This operation computes