experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Go: Update generated wrapper functions for TensorFlow ops.

Browse Source 
PiperOrigin-RevId: 286371061
Change-Id: I2817748cc82f745cae8cc71f6d1f44dd7d7ba6cc
This commit is contained in:
A. Unique TensorFlower 2019-12-19 04:46:21 -08:00 committed by TensorFlower Gardener
parent dd34097b12
commit c19bfd4219
1 changed files with 190 additions and 145 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

335
tensorflow/go/op/wrappers.go
View File

@ -6223,77 +6223,6 @@ func OrderedMapUnstageNoKey(scope *Scope, indices tf.Output, dtypes []tf.DataTyp
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 @@ 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
@ -11977,7 +11906,7 @@ 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
@ -11988,7 +11917,7 @@ 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
@ -12194,7 +12123,7 @@ 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
@ -12205,7 +12134,7 @@ 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
@ -13545,58 +13474,6 @@ func FixedLengthRecordReaderV2(scope *Scope, record_bytes int64, optional ...Fix
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 @@ func Roll(scope *Scope, input tf.Output, shift tf.Output, axis tf.Output) (outpu
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 @@ 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
@ -19890,7 +19935,7 @@ 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
@ -21187,7 +21232,7 @@ 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
@ -21895,7 +21940,7 @@ 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
@ -22091,7 +22136,7 @@ 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
@ -22160,7 +22205,7 @@ 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
@ -22275,7 +22320,7 @@ 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
@ -22334,7 +22379,7 @@ 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
@ -22508,7 +22553,7 @@ 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
@ -22699,7 +22744,7 @@ 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
@ -25273,7 +25318,7 @@ 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
@ -25330,7 +25375,7 @@ func DepthwiseConv2dNative(scope *Scope, input tf.Output, filter tf.Output, stri
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 @@ 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
@ -26285,7 +26330,7 @@ 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
@ -27306,7 +27351,7 @@ 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
@ -33684,7 +33729,7 @@ func SparseReduceMax(scope *Scope, input_indices tf.Output, input_values tf.Outp
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 @@ 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