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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 160172985
This commit is contained in:
A. Unique TensorFlower 2017-06-26 11:46:12 -07:00 committed by TensorFlower Gardener
parent ee3eaffe16
commit 0b9b09a853
1 changed files with 40 additions and 6 deletions
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46
tensorflow/go/op/wrappers.go
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@ -20544,23 +20544,40 @@ func Requantize(scope *Scope, input tf.Output, input_min tf.Output, input_max tf
return op.Output(0), op.Output(1), op.Output(2)
}
// ArgMinAttr is an optional argument to ArgMin.
type ArgMinAttr func(optionalAttr)
// ArgMinOutputType sets the optional output_type attribute to value.
// If not specified, defaults to DT_INT64
func ArgMinOutputType(value tf.DataType) ArgMinAttr {
return func(m optionalAttr) {
m["output_type"] = value
}
}
// Returns the index with the smallest value across dimensions of a tensor.
//
// Note that in case of ties the identity of the return value is not guaranteed.
//
// Arguments:
//
// dimension: int32, 0 <= dimension < rank(input). Describes which dimension
// of the input Tensor to reduce across. For vectors, use dimension = 0.
func ArgMin(scope *Scope, input tf.Output, dimension tf.Output) (output tf.Output) {
// dimension: int32 or int64, 0 <= dimension < rank(input). Describes
// which dimension of the input Tensor to reduce across. For vectors,
// use dimension = 0.
func ArgMin(scope *Scope, input tf.Output, dimension tf.Output, optional ...ArgMinAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "ArgMin",
Input: []tf.Input{
input, dimension,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
@ -21818,23 +21835,40 @@ func IsFinite(scope *Scope, x tf.Output) (y tf.Output) {
return op.Output(0)
}
// ArgMaxAttr is an optional argument to ArgMax.
type ArgMaxAttr func(optionalAttr)
// ArgMaxOutputType sets the optional output_type attribute to value.
// If not specified, defaults to DT_INT64
func ArgMaxOutputType(value tf.DataType) ArgMaxAttr {
return func(m optionalAttr) {
m["output_type"] = value
}
}
// Returns the index with the largest value across dimensions of a tensor.
//
// Note that in case of ties the identity of the return value is not guaranteed.
//
// Arguments:
//
// dimension: int32, 0 <= dimension < rank(input). Describes which dimension
// of the input Tensor to reduce across. For vectors, use dimension = 0.
func ArgMax(scope *Scope, input tf.Output, dimension tf.Output) (output tf.Output) {
// dimension: int32 or int64, 0 <= dimension < rank(input). Describes
// which dimension of the input Tensor to reduce across. For vectors,
// use dimension = 0.
func ArgMax(scope *Scope, input tf.Output, dimension tf.Output, optional ...ArgMaxAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "ArgMax",
Input: []tf.Input{
input, dimension,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)