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authorGravatar A. Unique TensorFlower <gardener@tensorflow.org>2017-03-27 16:40:09 -0800
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2017-03-27 19:54:21 -0700
commitfdb3b6bfe95bfed9d8d7fac3ef27a23cf43eb9ea (patch)
tree87ad9d566b6631c33b62050e458676069652bc0a
parentce0a07f2479c864b0a6cc8f4a218d74e8b480746 (diff)
Go: Update generated wrapper functions for TensorFlow ops.
Change: 151396171
-rw-r--r--tensorflow/go/op/wrappers.go196
1 files changed, 144 insertions, 52 deletions
diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index d2578527ae..de014abafa 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -1710,58 +1710,6 @@ func ShapeN(scope *Scope, input []tf.Output, optional ...ShapeNAttr) (output []t
return output
}
-// UniqueAttr is an optional argument to Unique.
-type UniqueAttr func(optionalAttr)
-
-// UniqueOutIdx sets the optional out_idx attribute to value.
-// If not specified, defaults to DT_INT32
-func UniqueOutIdx(value tf.DataType) UniqueAttr {
- return func(m optionalAttr) {
- m["out_idx"] = value
- }
-}
-
-// Finds unique elements in a 1-D tensor.
-//
-// This operation returns a tensor `y` containing all of the unique elements of `x`
-// sorted in the same order that they occur in `x`. This operation also returns a
-// tensor `idx` the same size as `x` that contains the index of each value of `x`
-// in the unique output `y`. In other words:
-//
-// `y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`
-//
-// For example:
-//
-// ```prettyprint
-// # tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8]
-// y, idx = unique(x)
-// y ==> [1, 2, 4, 7, 8]
-// idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
-// ```
-//
-// Arguments:
-// x: 1-D.
-//
-// Returns 1-D.1-D.
-func Unique(scope *Scope, x tf.Output, optional ...UniqueAttr) (y tf.Output, idx tf.Output) {
- if scope.Err() != nil {
- return
- }
- attrs := map[string]interface{}{}
- for _, a := range optional {
- a(attrs)
- }
- opspec := tf.OpSpec{
- Type: "Unique",
- Input: []tf.Input{
- x,
- },
- Attrs: attrs,
- }
- op := scope.AddOperation(opspec)
- return op.Output(0), op.Output(1)
-}
-
// Reshapes a tensor.
//
// Given `tensor`, this operation returns a tensor that has the same values
@@ -2506,6 +2454,121 @@ func ParallelConcat(scope *Scope, values []tf.Output, shape tf.Shape) (output tf
return op.Output(0)
}
+// UniqueAttr is an optional argument to Unique.
+type UniqueAttr func(optionalAttr)
+
+// UniqueOutIdx sets the optional out_idx attribute to value.
+// If not specified, defaults to DT_INT32
+func UniqueOutIdx(value tf.DataType) UniqueAttr {
+ return func(m optionalAttr) {
+ m["out_idx"] = value
+ }
+}
+
+// Finds unique elements in a 1-D tensor.
+//
+// This operation returns a tensor `y` containing all of the unique elements of `x`
+// sorted in the same order that they occur in `x`. This operation also returns a
+// tensor `idx` the same size as `x` that contains the index of each value of `x`
+// in the unique output `y`. In other words:
+//
+// `y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`
+//
+// For example:
+//
+// ```prettyprint
+// # tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8]
+// y, idx = unique(x)
+// y ==> [1, 2, 4, 7, 8]
+// idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
+// ```
+//
+// Arguments:
+// x: 1-D.
+//
+// Returns 1-D.1-D.
+func Unique(scope *Scope, x tf.Output, optional ...UniqueAttr) (y tf.Output, idx tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ attrs := map[string]interface{}{}
+ for _, a := range optional {
+ a(attrs)
+ }
+ opspec := tf.OpSpec{
+ Type: "Unique",
+ Input: []tf.Input{
+ x,
+ },
+ Attrs: attrs,
+ }
+ op := scope.AddOperation(opspec)
+ return op.Output(0), op.Output(1)
+}
+
+// DecodeWavAttr is an optional argument to DecodeWav.
+type DecodeWavAttr func(optionalAttr)
+
+// DecodeWavDesiredChannels sets the optional desired_channels attribute to value.
+//
+// value: Number of sample channels wanted.
+// If not specified, defaults to -1
+func DecodeWavDesiredChannels(value int64) DecodeWavAttr {
+ return func(m optionalAttr) {
+ m["desired_channels"] = value
+ }
+}
+
+// DecodeWavDesiredSamples sets the optional desired_samples attribute to value.
+//
+// value: Length of audio requested.
+// If not specified, defaults to -1
+func DecodeWavDesiredSamples(value int64) DecodeWavAttr {
+ return func(m optionalAttr) {
+ m["desired_samples"] = value
+ }
+}
+
+// Decode a 16-bit PCM WAV file to a float tensor.
+//
+// The -32768 to 32767 signed 16-bit values will be scaled to -1.0 to 1.0 in float.
+//
+// When desired_channels is set, if the input contains fewer channels than this
+// then the last channel will be duplicated to give the requested number, else if
+// the input has more channels than requested then the additional channels will be
+// ignored.
+//
+// If desired_samples is set, then the audio will be cropped or padded with zeroes
+// to the requested length.
+//
+// The first output contains a Tensor with the content of the audio samples. The
+// lowest dimension will be the number of channels, and the second will be the
+// number of samples. For example, a ten-sample-long stereo WAV file should give an
+// output shape of [10, 2].
+//
+// Arguments:
+// contents: The WAV-encoded audio, usually from a file.
+//
+// Returns 2-D with shape `[length, channels]`.Scalar holding the sample rate found in the WAV header.
+func DecodeWav(scope *Scope, contents tf.Output, optional ...DecodeWavAttr) (audio tf.Output, sample_rate tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ attrs := map[string]interface{}{}
+ for _, a := range optional {
+ a(attrs)
+ }
+ opspec := tf.OpSpec{
+ Type: "DecodeWav",
+ Input: []tf.Input{
+ contents,
+ },
+ Attrs: attrs,
+ }
+ op := scope.AddOperation(opspec)
+ return op.Output(0), op.Output(1)
+}
+
// AllCandidateSamplerAttr is an optional argument to AllCandidateSampler.
type AllCandidateSamplerAttr func(optionalAttr)
@@ -8606,6 +8669,35 @@ func MergeSummary(scope *Scope, inputs []tf.Output) (summary tf.Output) {
return op.Output(0)
}
+// Encode audio data using the WAV file format.
+//
+// This operation will generate a string suitable to be saved out to create a .wav
+// audio file. It will be encoded in the 16-bit PCM format. It takes in float
+// values in the range -1.0f to 1.0f, and any outside that value will be clamped to
+// that range.
+//
+// `audio` is a 2-D float Tensor of shape `[length, channels]`.
+// `sample_rate` is a scalar Tensor holding the rate to use (e.g. 44100).
+//
+// Arguments:
+// audio: 2-D with shape `[length, channels]`.
+// sample_rate: Scalar containing the sample frequency.
+//
+// Returns 0-D. WAV-encoded file contents.
+func EncodeWav(scope *Scope, audio tf.Output, sample_rate tf.Output) (contents tf.Output) {
+ if scope.Err() != nil {
+ return
+ }
+ opspec := tf.OpSpec{
+ Type: "EncodeWav",
+ Input: []tf.Input{
+ audio, sample_rate,
+ },
+ }
+ op := scope.AddOperation(opspec)
+ return op.Output(0)
+}
+
// The gradient operator for the SparseAdd op.
//
// The SparseAdd op calculates A + B, where A, B, and the sum are all represented