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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 327273828
Change-Id: I1e007a23c2f7efa479513af83588ab25cb4d44e9
This commit is contained in:
A. Unique TensorFlower 2020-08-18 11:45:56 -07:00 committed by TensorFlower Gardener
parent 4dc7c6aa3e
commit f068a69cee
1 changed files with 67 additions and 27 deletions
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94
tensorflow/go/op/wrappers.go
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@ -13634,6 +13634,33 @@ func QueueDequeueV2(scope *Scope, handle tf.Output, component_types []tf.DataTyp
return components
}
// Returns the next record (key, value pair) produced by a Reader.
//
// Will dequeue from the input queue if necessary (e.g. when the
// Reader needs to start reading from a new file since it has finished
// with the previous file).
//
// Arguments:
// reader_handle: Handle to a Reader.
// queue_handle: Handle to a Queue, with string work items.
//
// Returns:
// key: A scalar.
// value: A scalar.
func ReaderReadV2(scope *Scope, reader_handle tf.Output, queue_handle tf.Output) (key tf.Output, value tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "ReaderReadV2",
Input: []tf.Input{
reader_handle, queue_handle,
},
}
op := scope.AddOperation(opspec)
return op.Output(0), op.Output(1)
}
// Return a slice from 'input'.
//
// The output tensor is a tensor with dimensions described by 'size'
@ -15927,6 +15954,46 @@ func Dilation2D(scope *Scope, input tf.Output, filter tf.Output, strides []int64
return op.Output(0)
}
// IsotonicRegressionAttr is an optional argument to IsotonicRegression.
type IsotonicRegressionAttr func(optionalAttr)
// IsotonicRegressionOutputDtype sets the optional output_dtype attribute to value.
//
// value: Dtype of output.
// If not specified, defaults to DT_FLOAT
func IsotonicRegressionOutputDtype(value tf.DataType) IsotonicRegressionAttr {
return func(m optionalAttr) {
m["output_dtype"] = value
}
}
// Solves a batch of isotonic regression problems.
//
// Arguments:
// input: A (batch_size, dim)-tensor holding a batch of inputs.
//
// Returns:
// output: A (batch_size, dim)-tensor holding the per-batch element solutions.
// segments: An int32 (batch_size, dim)-tensor with the segments.
func IsotonicRegression(scope *Scope, input tf.Output, optional ...IsotonicRegressionAttr) (output tf.Output, segments tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "IsotonicRegression",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0), op.Output(1)
}
// Computes softplus: `log(exp(features) + 1)`.
func Softplus(scope *Scope, features tf.Output) (activations tf.Output) {
if scope.Err() != nil {
@ -49688,33 +49755,6 @@ func LoadTPUEmbeddingMDLAdagradLightParameters(scope *Scope, parameters tf.Outpu
return scope.AddOperation(opspec)
}
// Returns the next record (key, value pair) produced by a Reader.
//
// Will dequeue from the input queue if necessary (e.g. when the
// Reader needs to start reading from a new file since it has finished
// with the previous file).
//
// Arguments:
// reader_handle: Handle to a Reader.
// queue_handle: Handle to a Queue, with string work items.
//
// Returns:
// key: A scalar.
// value: A scalar.
func ReaderReadV2(scope *Scope, reader_handle tf.Output, queue_handle tf.Output) (key tf.Output, value tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "ReaderReadV2",
Input: []tf.Input{
reader_handle, queue_handle,
},
}
op := scope.AddOperation(opspec)
return op.Output(0), op.Output(1)
}
// CumprodAttr is an optional argument to Cumprod.
type CumprodAttr func(optionalAttr)