Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 296521494
Change-Id: Ife15f953f44a36cb7e2b5cb5e4430f78d3460f94
diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index b97c273..449a957 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -11611,7 +11611,7 @@
// 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
@@ -11868,7 +11868,7 @@
//
// 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
@@ -11879,7 +11879,7 @@
//
// 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
@@ -12085,7 +12085,7 @@
//
// 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
@@ -12096,7 +12096,7 @@
//
// 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
@@ -18937,7 +18937,7 @@
// 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
@@ -20077,7 +20077,7 @@
// 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
@@ -21345,7 +21345,7 @@
// 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
@@ -22053,7 +22053,7 @@
// 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
@@ -22249,7 +22249,7 @@
// 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
@@ -22318,7 +22318,7 @@
// 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
@@ -22433,7 +22433,7 @@
// 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
@@ -22492,7 +22492,7 @@
// 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
@@ -22666,7 +22666,7 @@
// 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
@@ -22857,7 +22857,7 @@
// 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
@@ -25297,7 +25297,7 @@
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
@@ -25629,7 +25629,7 @@
// 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
@@ -25679,7 +25679,7 @@
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
@@ -25929,7 +25929,7 @@
// 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
@@ -26559,7 +26559,7 @@
// 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
@@ -27624,7 +27624,7 @@
// 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
@@ -37603,40 +37603,6 @@
return outputs
}
-// QuantizeAndDequantizeV2GradAttr is an optional argument to QuantizeAndDequantizeV2Grad.
-type QuantizeAndDequantizeV2GradAttr func(optionalAttr)
-
-// QuantizeAndDequantizeV2GradAxis sets the optional axis attribute to value.
-// If not specified, defaults to -1
-func QuantizeAndDequantizeV2GradAxis(value int64) QuantizeAndDequantizeV2GradAttr {
- return func(m optionalAttr) {
- m["axis"] = value
- }
-}
-
-// Returns the gradient of `QuantizeAndDequantizeV2`.
-//
-// Returns a gradient of 1 for inputs that are within the quantization range,
-// or 0 otherwise.
-func QuantizeAndDequantizeV2Grad(scope *Scope, gradients tf.Output, input tf.Output, input_min tf.Output, input_max tf.Output, optional ...QuantizeAndDequantizeV2GradAttr) (input_backprop tf.Output, input_min_backprop tf.Output, input_max_backprop tf.Output) {
- if scope.Err() != nil {
- return
- }
- attrs := map[string]interface{}{}
- for _, a := range optional {
- a(attrs)
- }
- opspec := tf.OpSpec{
- Type: "QuantizeAndDequantizeV2Grad",
- Input: []tf.Input{
- gradients, input, input_min, input_max,
- },
- Attrs: attrs,
- }
- op := scope.AddOperation(opspec)
- return op.Output(0), op.Output(1), op.Output(2)
-}
-
// Computes the sparse Cholesky decomposition of `input`.
//
// Computes the Sparse Cholesky decomposition of a sparse matrix, with the given
@@ -45570,7 +45536,7 @@
// 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
