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