diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go index 8c8867e6193..0db0284555c 100644 --- a/tensorflow/go/op/wrappers.go +++ b/tensorflow/go/op/wrappers.go @@ -6915,9 +6915,7 @@ func GetSessionHandle(scope *Scope, value tf.Output) (handle tf.Output) { return op.Output(0) } -// Copy a tensor setting everything outside a central band in each innermost matrix -// -// to zero. +// Copy a tensor setting everything outside a central band in each innermost matrix to zero. // // The `band` part is computed as follows: // Assume `input` has `k` dimensions `[I, J, K, ..., M, N]`, then the output is a @@ -11935,7 +11933,7 @@ 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 @@ -11946,7 +11944,7 @@ 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 @@ -18622,7 +18620,7 @@ 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 @@ -18633,7 +18631,7 @@ 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 @@ -19037,7 +19035,7 @@ 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 @@ -20108,7 +20106,7 @@ 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 @@ -21280,7 +21278,7 @@ 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 @@ -21988,7 +21986,7 @@ 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 @@ -22184,7 +22182,7 @@ 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 @@ -22253,7 +22251,7 @@ 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 @@ -22368,7 +22366,7 @@ 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 @@ -22427,7 +22425,7 @@ 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 @@ -22601,7 +22599,7 @@ 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 @@ -22978,7 +22976,7 @@ 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 @@ -25298,7 +25296,7 @@ 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 @@ -25361,7 +25359,7 @@ 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 @@ -25612,7 +25610,7 @@ 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 @@ -26096,7 +26094,7 @@ 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 @@ -40144,9 +40142,9 @@ func ResourceApplyMomentumUseNesterov(value bool) ResourceApplyMomentumAttr { } } -// Update '*var' according to the momentum scheme. Set use_nesterov = True if you +// Update '*var' according to the momentum scheme. // -// want to use Nesterov momentum. +// Set use_nesterov = True if you want to use Nesterov momentum. // // accum = accum * momentum + grad // var -= lr * accum @@ -40349,7 +40347,7 @@ 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 @@ -45846,7 +45844,7 @@ 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 @@ -46838,7 +46836,7 @@ 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 @@ -46909,7 +46907,7 @@ 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 @@ -47099,7 +47097,7 @@ func ResourceApplyAdagradV2UpdateSlots(value bool) ResourceApplyAdagradV2Attr { // Update '*var' according to the adagrad scheme. // // accum += grad * grad -// var -= lr * grad * (1 / sqrt(accum)) +// var -= lr * grad * (1 / (sqrt(accum) + epsilon)) // // Arguments: // var_: Should be from a Variable().