Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 286371061
Change-Id: I2817748cc82f745cae8cc71f6d1f44dd7d7ba6cc
diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index d19bd97..451be22 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -6223,77 +6223,6 @@
return key, values
}
-// OrderedMapUnstageAttr is an optional argument to OrderedMapUnstage.
-type OrderedMapUnstageAttr func(optionalAttr)
-
-// OrderedMapUnstageCapacity sets the optional capacity attribute to value.
-// If not specified, defaults to 0
-//
-// REQUIRES: value >= 0
-func OrderedMapUnstageCapacity(value int64) OrderedMapUnstageAttr {
- return func(m optionalAttr) {
- m["capacity"] = value
- }
-}
-
-// OrderedMapUnstageMemoryLimit sets the optional memory_limit attribute to value.
-// If not specified, defaults to 0
-//
-// REQUIRES: value >= 0
-func OrderedMapUnstageMemoryLimit(value int64) OrderedMapUnstageAttr {
- return func(m optionalAttr) {
- m["memory_limit"] = value
- }
-}
-
-// OrderedMapUnstageContainer sets the optional container attribute to value.
-// If not specified, defaults to ""
-func OrderedMapUnstageContainer(value string) OrderedMapUnstageAttr {
- return func(m optionalAttr) {
- m["container"] = value
- }
-}
-
-// OrderedMapUnstageSharedName sets the optional shared_name attribute to value.
-// If not specified, defaults to ""
-func OrderedMapUnstageSharedName(value string) OrderedMapUnstageAttr {
- return func(m optionalAttr) {
- m["shared_name"] = value
- }
-}
-
-// Op removes and returns the values associated with the key
-//
-// from the underlying container. If the underlying container
-// does not contain this key, the op will block until it does.
-func OrderedMapUnstage(scope *Scope, key tf.Output, indices tf.Output, dtypes []tf.DataType, optional ...OrderedMapUnstageAttr) (values []tf.Output) {
- if scope.Err() != nil {
- return
- }
- attrs := map[string]interface{}{"dtypes": dtypes}
- for _, a := range optional {
- a(attrs)
- }
- opspec := tf.OpSpec{
- Type: "OrderedMapUnstage",
- Input: []tf.Input{
- key, indices,
- },
- Attrs: attrs,
- }
- op := scope.AddOperation(opspec)
- if scope.Err() != nil {
- return
- }
- var idx int
- var err error
- if values, idx, err = makeOutputList(op, idx, "values"); err != nil {
- scope.UpdateErr("OrderedMapUnstage", err)
- return
- }
- return values
-}
-
// OrderedMapPeekAttr is an optional argument to OrderedMapPeek.
type OrderedMapPeekAttr func(optionalAttr)
@@ -11720,7 +11649,7 @@
// 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
@@ -11977,7 +11906,7 @@
//
// 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
@@ -11988,7 +11917,7 @@
//
// 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
@@ -12194,7 +12123,7 @@
//
// 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
@@ -12205,7 +12134,7 @@
//
// 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
@@ -13545,58 +13474,6 @@
return op.Output(0)
}
-// RestoreSliceAttr is an optional argument to RestoreSlice.
-type RestoreSliceAttr func(optionalAttr)
-
-// RestoreSlicePreferredShard sets the optional preferred_shard attribute to value.
-//
-// value: Index of file to open first if multiple files match
-// `file_pattern`. See the documentation for `Restore`.
-// If not specified, defaults to -1
-func RestoreSlicePreferredShard(value int64) RestoreSliceAttr {
- return func(m optionalAttr) {
- m["preferred_shard"] = value
- }
-}
-
-// Restores a tensor from checkpoint files.
-//
-// This is like `Restore` except that restored tensor can be listed as filling
-// only a slice of a larger tensor. `shape_and_slice` specifies the shape of the
-// larger tensor and the slice that the restored tensor covers.
-//
-// The `shape_and_slice` input has the same format as the
-// elements of the `shapes_and_slices` input of the `SaveSlices` op.
-//
-// Arguments:
-// file_pattern: Must have a single element. The pattern of the files from
-// which we read the tensor.
-// tensor_name: Must have a single element. The name of the tensor to be
-// restored.
-// shape_and_slice: Scalar. The shapes and slice specifications to use when
-// restoring a tensors.
-// dt: The type of the tensor to be restored.
-//
-// Returns The restored tensor.
-func RestoreSlice(scope *Scope, file_pattern tf.Output, tensor_name tf.Output, shape_and_slice tf.Output, dt tf.DataType, optional ...RestoreSliceAttr) (tensor tf.Output) {
- if scope.Err() != nil {
- return
- }
- attrs := map[string]interface{}{"dt": dt}
- for _, a := range optional {
- a(attrs)
- }
- opspec := tf.OpSpec{
- Type: "RestoreSlice",
- Input: []tf.Input{
- file_pattern, tensor_name, shape_and_slice,
- },
- Attrs: attrs,
- }
- op := scope.AddOperation(opspec)
- return op.Output(0)
-}
-
// Saves the input tensors to disk.
//
// The size of `tensor_names` must match the number of tensors in `data`. `data[i]`
@@ -16590,6 +16467,174 @@
return op.Output(0)
}
+// RestoreSliceAttr is an optional argument to RestoreSlice.
+type RestoreSliceAttr func(optionalAttr)
+
+// RestoreSlicePreferredShard sets the optional preferred_shard attribute to value.
+//
+// value: Index of file to open first if multiple files match
+// `file_pattern`. See the documentation for `Restore`.
+// If not specified, defaults to -1
+func RestoreSlicePreferredShard(value int64) RestoreSliceAttr {
+ return func(m optionalAttr) {
+ m["preferred_shard"] = value
+ }
+}
+
+// Restores a tensor from checkpoint files.
+//
+// This is like `Restore` except that restored tensor can be listed as filling
+// only a slice of a larger tensor. `shape_and_slice` specifies the shape of the
+// larger tensor and the slice that the restored tensor covers.
+//
+// The `shape_and_slice` input has the same format as the
+// elements of the `shapes_and_slices` input of the `SaveSlices` op.
+//
+// Arguments:
+// file_pattern: Must have a single element. The pattern of the files from
+// which we read the tensor.
+// tensor_name: Must have a single element. The name of the tensor to be
+// restored.
+// shape_and_slice: Scalar. The shapes and slice specifications to use when
+// restoring a tensors.
+// dt: The type of the tensor to be restored.
+//
+// Returns The restored tensor.
+func RestoreSlice(scope *Scope, file_pattern tf.Output, tensor_name tf.Output, shape_and_slice tf.Output, dt tf.DataType, optional ...RestoreSliceAttr) (tensor tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ attrs := map[string]interface{}{"dt": dt}
+ for _, a := range optional {
+ a(attrs)
+ }
+ opspec := tf.OpSpec{
+ Type: "RestoreSlice",
+ Input: []tf.Input{
+ file_pattern, tensor_name, shape_and_slice,
+ },
+ Attrs: attrs,
+ }
+ op := scope.AddOperation(opspec)
+ return op.Output(0)
+}
+
+// OrderedMapUnstageAttr is an optional argument to OrderedMapUnstage.
+type OrderedMapUnstageAttr func(optionalAttr)
+
+// OrderedMapUnstageCapacity sets the optional capacity attribute to value.
+// If not specified, defaults to 0
+//
+// REQUIRES: value >= 0
+func OrderedMapUnstageCapacity(value int64) OrderedMapUnstageAttr {
+ return func(m optionalAttr) {
+ m["capacity"] = value
+ }
+}
+
+// OrderedMapUnstageMemoryLimit sets the optional memory_limit attribute to value.
+// If not specified, defaults to 0
+//
+// REQUIRES: value >= 0
+func OrderedMapUnstageMemoryLimit(value int64) OrderedMapUnstageAttr {
+ return func(m optionalAttr) {
+ m["memory_limit"] = value
+ }
+}
+
+// OrderedMapUnstageContainer sets the optional container attribute to value.
+// If not specified, defaults to ""
+func OrderedMapUnstageContainer(value string) OrderedMapUnstageAttr {
+ return func(m optionalAttr) {
+ m["container"] = value
+ }
+}
+
+// OrderedMapUnstageSharedName sets the optional shared_name attribute to value.
+// If not specified, defaults to ""
+func OrderedMapUnstageSharedName(value string) OrderedMapUnstageAttr {
+ return func(m optionalAttr) {
+ m["shared_name"] = value
+ }
+}
+
+// Op removes and returns the values associated with the key
+//
+// from the underlying container. If the underlying container
+// does not contain this key, the op will block until it does.
+func OrderedMapUnstage(scope *Scope, key tf.Output, indices tf.Output, dtypes []tf.DataType, optional ...OrderedMapUnstageAttr) (values []tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ attrs := map[string]interface{}{"dtypes": dtypes}
+ for _, a := range optional {
+ a(attrs)
+ }
+ opspec := tf.OpSpec{
+ Type: "OrderedMapUnstage",
+ Input: []tf.Input{
+ key, indices,
+ },
+ Attrs: attrs,
+ }
+ op := scope.AddOperation(opspec)
+ if scope.Err() != nil {
+ return
+ }
+ var idx int
+ var err error
+ if values, idx, err = makeOutputList(op, idx, "values"); err != nil {
+ scope.UpdateErr("OrderedMapUnstage", err)
+ return
+ }
+ return values
+}
+
+// SobolSampleAttr is an optional argument to SobolSample.
+type SobolSampleAttr func(optionalAttr)
+
+// SobolSampleDtype sets the optional dtype attribute to value.
+//
+// value: The type of the sample. One of: `float32` or `float64`.
+// If not specified, defaults to DT_DOUBLE
+func SobolSampleDtype(value tf.DataType) SobolSampleAttr {
+ return func(m optionalAttr) {
+ m["dtype"] = value
+ }
+}
+
+// Generates points from the Sobol sequence.
+//
+// Creates a Sobol sequence with `num_results` samples. Each sample has dimension
+// `dim`. Skips the first `skip` samples.
+//
+// Arguments:
+// dim: Positive scalar `Tensor` representing each sample's dimension.
+// num_results: Positive scalar `Tensor` of dtype int32. The number of Sobol points to return
+// in the output.
+// skip: Positive scalar `Tensor` of dtype int32. The number of initial points of the
+// Sobol sequence to skip.
+//
+// Returns `Tensor` of samples from Sobol sequence with `shape` [num_results, dim].
+func SobolSample(scope *Scope, dim tf.Output, num_results tf.Output, skip tf.Output, optional ...SobolSampleAttr) (samples tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ attrs := map[string]interface{}{}
+ for _, a := range optional {
+ a(attrs)
+ }
+ opspec := tf.OpSpec{
+ Type: "SobolSample",
+ Input: []tf.Input{
+ dim, num_results, skip,
+ },
+ Attrs: attrs,
+ }
+ op := scope.AddOperation(opspec)
+ return op.Output(0)
+}
+
// QuantizedReluAttr is an optional argument to QuantizedRelu.
type QuantizedReluAttr func(optionalAttr)
@@ -18895,7 +18940,7 @@
// 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
@@ -19890,7 +19935,7 @@
// 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
@@ -21187,7 +21232,7 @@
// 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
@@ -21895,7 +21940,7 @@
// 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
@@ -22091,7 +22136,7 @@
// 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
@@ -22160,7 +22205,7 @@
// 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
@@ -22275,7 +22320,7 @@
// 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
@@ -22334,7 +22379,7 @@
// 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
@@ -22508,7 +22553,7 @@
// 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
@@ -22699,7 +22744,7 @@
// 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
@@ -25273,7 +25318,7 @@
// 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
@@ -25330,7 +25375,7 @@
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
@@ -25662,7 +25707,7 @@
// 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
@@ -26285,7 +26330,7 @@
// 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
@@ -27306,7 +27351,7 @@
// 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
@@ -33684,7 +33729,7 @@
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
@@ -45111,7 +45156,7 @@
// 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
