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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 309147560
Change-Id: Ic591ce76811bbd7841ac63f6f2aae75f95070280
This commit is contained in:
A. Unique TensorFlower 2020-04-29 19:46:26 -07:00 committed by TensorFlower Gardener
parent b5f954b27d
commit 2d80f55c77
1 changed files with 38 additions and 24 deletions
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62
tensorflow/go/op/wrappers.go
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@ -11942,7 +11942,7 @@ func SampleDistortedBoundingBoxMinObjectCovered(value float32) SampleDistortedBo
//
// value: The cropped area of the image must have an aspect ratio =
// width / height within this range.
// If not specified, defaults to {f:0.75 f:1.33}
// If not specified, defaults to {f:0.75 f:1.33}
func SampleDistortedBoundingBoxAspectRatioRange(value []float32) SampleDistortedBoundingBoxAttr {
return func(m optionalAttr) {
m["aspect_ratio_range"] = value
@ -11953,7 +11953,7 @@ func SampleDistortedBoundingBoxAspectRatioRange(value []float32) SampleDistorted
//
// value: The cropped area of the image must contain a fraction of the
// supplied image within this range.
// If not specified, defaults to {f:0.05 f:1}
// If not specified, defaults to {f:0.05 f:1}
func SampleDistortedBoundingBoxAreaRange(value []float32) SampleDistortedBoundingBoxAttr {
return func(m optionalAttr) {
m["area_range"] = value
@ -16989,6 +16989,17 @@ func QuantizedAdd(scope *Scope, x tf.Output, y tf.Output, min_x tf.Output, max_x
return op.Output(0), op.Output(1), op.Output(2)
}
// ShuffleAndRepeatDatasetAttr is an optional argument to ShuffleAndRepeatDataset.
type ShuffleAndRepeatDatasetAttr func(optionalAttr)
// ShuffleAndRepeatDatasetReshuffleEachIteration sets the optional reshuffle_each_iteration attribute to value.
// If not specified, defaults to true
func ShuffleAndRepeatDatasetReshuffleEachIteration(value bool) ShuffleAndRepeatDatasetAttr {
return func(m optionalAttr) {
m["reshuffle_each_iteration"] = value
}
}
// Creates a dataset that shuffles and repeats elements from `input_dataset`
//
// pseudorandomly.
@ -17006,11 +17017,14 @@ func QuantizedAdd(scope *Scope, x tf.Output, y tf.Output, min_x tf.Output, max_x
// should be repeated. The default is `-1`, which results in infinite repetition.
//
//
func ShuffleAndRepeatDataset(scope *Scope, input_dataset tf.Output, buffer_size tf.Output, seed tf.Output, seed2 tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
func ShuffleAndRepeatDataset(scope *Scope, input_dataset tf.Output, buffer_size tf.Output, seed tf.Output, seed2 tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape, optional ...ShuffleAndRepeatDatasetAttr) (handle tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{"output_types": output_types, "output_shapes": output_shapes}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "ShuffleAndRepeatDataset",
Input: []tf.Input{
@ -18629,7 +18643,7 @@ func SampleDistortedBoundingBoxV2Seed2(value int64) SampleDistortedBoundingBoxV2
//
// value: The cropped area of the image must have an aspect ratio =
// width / height within this range.
// If not specified, defaults to {f:0.75 f:1.33}
// If not specified, defaults to {f:0.75 f:1.33}
func SampleDistortedBoundingBoxV2AspectRatioRange(value []float32) SampleDistortedBoundingBoxV2Attr {
return func(m optionalAttr) {
m["aspect_ratio_range"] = value
@ -18640,7 +18654,7 @@ func SampleDistortedBoundingBoxV2AspectRatioRange(value []float32) SampleDistort
//
// value: The cropped area of the image must contain a fraction of the
// supplied image within this range.
// If not specified, defaults to {f:0.05 f:1}
// If not specified, defaults to {f:0.05 f:1}
func SampleDistortedBoundingBoxV2AreaRange(value []float32) SampleDistortedBoundingBoxV2Attr {
return func(m optionalAttr) {
m["area_range"] = value
@ -19044,7 +19058,7 @@ func ImageSummaryMaxImages(value int64) ImageSummaryAttr {
// ImageSummaryBadColor sets the optional bad_color attribute to value.
//
// value: Color to use for pixels with non-finite values.
// If not specified, defaults to {dtype:DT_UINT8 tensor_shape:{dim:{size:4}} int_val:255 int_val:0 int_val:0 int_val:255}
// If not specified, defaults to {dtype:DT_UINT8 tensor_shape:{dim:{size:4}} int_val:255 int_val:0 int_val:0 int_val:255}
func ImageSummaryBadColor(value tf.Tensor) ImageSummaryAttr {
return func(m optionalAttr) {
m["bad_color"] = value
@ -20115,7 +20129,7 @@ func Conv3DBackpropFilterV2DataFormat(value string) Conv3DBackpropFilterV2Attr {
// filter element on that dimension. The dimension order is determined by the
// value of `data_format`, see above for details. Dilations in the batch and
// depth dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
func Conv3DBackpropFilterV2Dilations(value []int64) Conv3DBackpropFilterV2Attr {
return func(m optionalAttr) {
m["dilations"] = value
@ -21287,7 +21301,7 @@ func Conv2DBackpropInputDataFormat(value string) Conv2DBackpropInputAttr {
// element on that dimension. The dimension order is determined by the value of
// `data_format`, see above for details. Dilations in the batch and depth
// dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func Conv2DBackpropInputDilations(value []int64) Conv2DBackpropInputAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -21995,7 +22009,7 @@ func Conv2DDataFormat(value string) Conv2DAttr {
// filter element on that dimension. The dimension order is determined by the
// value of `data_format`, see above for details. Dilations in the batch and
// depth dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func Conv2DDilations(value []int64) Conv2DAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22191,7 +22205,7 @@ func QuantizedDepthwiseConv2DWithBiasAndReluAndRequantizeOutType(value tf.DataTy
// QuantizedDepthwiseConv2DWithBiasAndReluAndRequantizeDilations sets the optional dilations attribute to value.
//
// value: List of dilation values.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedDepthwiseConv2DWithBiasAndReluAndRequantizeDilations(value []int64) QuantizedDepthwiseConv2DWithBiasAndReluAndRequantizeAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22260,7 +22274,7 @@ func QuantizedDepthwiseConv2DWithBiasAndReluOutType(value tf.DataType) Quantized
// QuantizedDepthwiseConv2DWithBiasAndReluDilations sets the optional dilations attribute to value.
//
// value: List of dilation values.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedDepthwiseConv2DWithBiasAndReluDilations(value []int64) QuantizedDepthwiseConv2DWithBiasAndReluAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22375,7 +22389,7 @@ func QuantizedDepthwiseConv2DWithBiasOutType(value tf.DataType) QuantizedDepthwi
// QuantizedDepthwiseConv2DWithBiasDilations sets the optional dilations attribute to value.
//
// value: List of dilation values.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedDepthwiseConv2DWithBiasDilations(value []int64) QuantizedDepthwiseConv2DWithBiasAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22434,7 +22448,7 @@ func QuantizedDepthwiseConv2DOutType(value tf.DataType) QuantizedDepthwiseConv2D
// QuantizedDepthwiseConv2DDilations sets the optional dilations attribute to value.
//
// value: List of dilation values.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedDepthwiseConv2DDilations(value []int64) QuantizedDepthwiseConv2DAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22608,7 +22622,7 @@ func QuantizedConv2DPerChannelOutType(value tf.DataType) QuantizedConv2DPerChann
// QuantizedConv2DPerChannelDilations sets the optional dilations attribute to value.
//
// value: list of dilation values.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedConv2DPerChannelDilations(value []int64) QuantizedConv2DPerChannelAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -22985,7 +22999,7 @@ func Conv3DBackpropInputV2DataFormat(value string) Conv3DBackpropInputV2Attr {
// filter element on that dimension. The dimension order is determined by the
// value of `data_format`, see above for details. Dilations in the batch and
// depth dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
func Conv3DBackpropInputV2Dilations(value []int64) Conv3DBackpropInputV2Attr {
return func(m optionalAttr) {
m["dilations"] = value
@ -25305,7 +25319,7 @@ func AvgPool3DGrad(scope *Scope, orig_input_shape tf.Output, grad tf.Output, ksi
type Conv3DBackpropFilterAttr func(optionalAttr)
// Conv3DBackpropFilterDilations sets the optional dilations attribute to value.
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
func Conv3DBackpropFilterDilations(value []int64) Conv3DBackpropFilterAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -25368,7 +25382,7 @@ func Conv3DDataFormat(value string) Conv3DAttr {
// filter element on that dimension. The dimension order is determined by the
// value of `data_format`, see above for details. Dilations in the batch and
// depth dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
func Conv3DDilations(value []int64) Conv3DAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -25619,7 +25633,7 @@ func DepthwiseConv2dNativeBackpropInputDataFormat(value string) DepthwiseConv2dN
// element on that dimension. The dimension order is determined by the value of
// `data_format`, see above for details. Dilations in the batch and depth
// dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func DepthwiseConv2dNativeBackpropInputDilations(value []int64) DepthwiseConv2dNativeBackpropInputAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -26103,7 +26117,7 @@ func QuantizedConv2DOutType(value tf.DataType) QuantizedConv2DAttr {
// filter element on that dimension. The dimension order is determined by the
// value of `data_format`, see above for details. Dilations in the batch and
// depth dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func QuantizedConv2DDilations(value []int64) QuantizedConv2DAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -26814,7 +26828,7 @@ func Reverse(scope *Scope, tensor tf.Output, dims tf.Output) (output tf.Output)
//
// @tf.function
// def foo(x, y):
// return = mlir_passthrough_op([x, y], mlir_module, Toutputs=[tf.float32])
// return mlir_passthrough_op([x, y], mlir_module, Toutputs=[tf.float32])
//
// graph_def = foo.get_concrete_function(tf.TensorSpec([10], tf.float32), tf.TensorSpec([10], tf.float32)).graph.as_graph_def()
// ```
@ -40356,7 +40370,7 @@ func DepthwiseConv2dNativeBackpropFilterDataFormat(value string) DepthwiseConv2d
// element on that dimension. The dimension order is determined by the value of
// `data_format`, see above for details. Dilations in the batch and depth
// dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func DepthwiseConv2dNativeBackpropFilterDilations(value []int64) DepthwiseConv2dNativeBackpropFilterAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -45853,7 +45867,7 @@ func Conv2DBackpropFilterDataFormat(value string) Conv2DBackpropFilterAttr {
// element on that dimension. The dimension order is determined by the value of
// `data_format`, see above for details. Dilations in the batch and depth
// dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func Conv2DBackpropFilterDilations(value []int64) Conv2DBackpropFilterAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -46845,7 +46859,7 @@ func CreateJob(scope *Scope, dataset_id tf.Output, address tf.Output, protocol t
type Conv3DBackpropInputAttr func(optionalAttr)
// Conv3DBackpropInputDilations sets the optional dilations attribute to value.
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1 i:1}
func Conv3DBackpropInputDilations(value []int64) Conv3DBackpropInputAttr {
return func(m optionalAttr) {
m["dilations"] = value
@ -46916,7 +46930,7 @@ func DepthwiseConv2dNativeDataFormat(value string) DepthwiseConv2dNativeAttr {
// element on that dimension. The dimension order is determined by the value of
// `data_format`, see above for details. Dilations in the batch and depth
// dimensions must be 1.
// If not specified, defaults to {i:1 i:1 i:1 i:1}
// If not specified, defaults to {i:1 i:1 i:1 i:1}
func DepthwiseConv2dNativeDilations(value []int64) DepthwiseConv2dNativeAttr {
return func(m optionalAttr) {
m["dilations"] = value