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Go: Update generated wrapper functions for TensorFlow ops.

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PiperOrigin-RevId: 307690267
Change-Id: Ic78e8ce07983dd496ba9563bcf60352473a0428c
This commit is contained in:
A. Unique TensorFlower 2020-04-21 15:15:02 -07:00 committed by TensorFlower Gardener
parent 75940041fc
commit 567f7e24ef
1 changed files with 106 additions and 92 deletions
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154
tensorflow/go/op/wrappers.go
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@ -9878,12 +9878,26 @@ func RegisterDataset(scope *Scope, dataset tf.Output, address tf.Output, protoco
return op.Output(0)
}
// DataServiceDatasetAttr is an optional argument to DataServiceDataset.
type DataServiceDatasetAttr func(optionalAttr)
// DataServiceDatasetTaskRefreshIntervalHintMs sets the optional task_refresh_interval_hint_ms attribute to value.
// If not specified, defaults to -1
func DataServiceDatasetTaskRefreshIntervalHintMs(value int64) DataServiceDatasetAttr {
return func(m optionalAttr) {
m["task_refresh_interval_hint_ms"] = value
}
}
// Creates a dataset that reads data from the tf.data service.
func DataServiceDataset(scope *Scope, address tf.Output, protocol tf.Output, max_outstanding_requests tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
func DataServiceDataset(scope *Scope, address tf.Output, protocol tf.Output, max_outstanding_requests tf.Output, output_types []tf.DataType, output_shapes []tf.Shape, optional ...DataServiceDatasetAttr) (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: "DataServiceDataset",
Input: []tf.Input{
@ -11879,75 +11893,6 @@ func ExtractGlimpse(scope *Scope, input tf.Output, size tf.Output, offsets tf.Ou
return op.Output(0)
}
// Converts one or more images from RGB to HSV.
//
// Outputs a tensor of the same shape as the `images` tensor, containing the HSV
// value of the pixels. The output is only well defined if the value in `images`
// are in `[0,1]`.
//
// `output[..., 0]` contains hue, `output[..., 1]` contains saturation, and
// `output[..., 2]` contains value. All HSV values are in `[0,1]`. A hue of 0
// corresponds to pure red, hue 1/3 is pure green, and 2/3 is pure blue.
//
// Usage Example:
//
// >>> blue_image = tf.stack([
// ... tf.zeros([5,5]),
// ... tf.zeros([5,5]),
// ... tf.ones([5,5])],
// ... axis=-1)
// >>> blue_hsv_image = tf.image.rgb_to_hsv(blue_image)
// >>> blue_hsv_image[0,0].numpy()
// array([0.6666667, 1. , 1. ], dtype=float32)
//
//
// Arguments:
// images: 1-D or higher rank. RGB data to convert. Last dimension must be size 3.
//
// Returns `images` converted to HSV.
func RGBToHSV(scope *Scope, images tf.Output) (output tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "RGBToHSV",
Input: []tf.Input{
images,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Decode the frame(s) of a GIF-encoded image to a uint8 tensor.
//
// GIF images with frame or transparency compression are not supported.
// On Linux and MacOS systems, convert animated GIFs from compressed to
// uncompressed by running:
//
// convert $src.gif -coalesce $dst.gif
//
// This op also supports decoding JPEGs and PNGs, though it is cleaner to use
// `tf.io.decode_image`.
//
// Arguments:
// contents: 0-D. The GIF-encoded image.
//
// Returns 4-D with shape `[num_frames, height, width, 3]`. RGB channel order.
func DecodeGif(scope *Scope, contents tf.Output) (image tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "DecodeGif",
Input: []tf.Input{
contents,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// SampleDistortedBoundingBoxAttr is an optional argument to SampleDistortedBoundingBox.
type SampleDistortedBoundingBoxAttr func(optionalAttr)
@ -12104,6 +12049,75 @@ func SampleDistortedBoundingBox(scope *Scope, image_size tf.Output, bounding_box
return op.Output(0), op.Output(1), op.Output(2)
}
// Converts one or more images from RGB to HSV.
//
// Outputs a tensor of the same shape as the `images` tensor, containing the HSV
// value of the pixels. The output is only well defined if the value in `images`
// are in `[0,1]`.
//
// `output[..., 0]` contains hue, `output[..., 1]` contains saturation, and
// `output[..., 2]` contains value. All HSV values are in `[0,1]`. A hue of 0
// corresponds to pure red, hue 1/3 is pure green, and 2/3 is pure blue.
//
// Usage Example:
//
// >>> blue_image = tf.stack([
// ... tf.zeros([5,5]),
// ... tf.zeros([5,5]),
// ... tf.ones([5,5])],
// ... axis=-1)
// >>> blue_hsv_image = tf.image.rgb_to_hsv(blue_image)
// >>> blue_hsv_image[0,0].numpy()
// array([0.6666667, 1. , 1. ], dtype=float32)
//
//
// Arguments:
// images: 1-D or higher rank. RGB data to convert. Last dimension must be size 3.
//
// Returns `images` converted to HSV.
func RGBToHSV(scope *Scope, images tf.Output) (output tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "RGBToHSV",
Input: []tf.Input{
images,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Decode the frame(s) of a GIF-encoded image to a uint8 tensor.
//
// GIF images with frame or transparency compression are not supported.
// On Linux and MacOS systems, convert animated GIFs from compressed to
// uncompressed by running:
//
// convert $src.gif -coalesce $dst.gif
//
// This op also supports decoding JPEGs and PNGs, though it is cleaner to use
// `tf.io.decode_image`.
//
// Arguments:
// contents: 0-D. The GIF-encoded image.
//
// Returns 4-D with shape `[num_frames, height, width, 3]`. RGB channel order.
func DecodeGif(scope *Scope, contents tf.Output) (image tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "DecodeGif",
Input: []tf.Input{
contents,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// DecodeBmpAttr is an optional argument to DecodeBmp.
type DecodeBmpAttr func(optionalAttr)