Skip to content

T
tensorflow

xxadev / tensorflow
与 Fork 源项目一致

从无法访问的项目Fork

通知 3
Star 1
Fork 0
T
tensorflow

体验新版 GitCode，发现更多精彩内容 >>

提交 26c5a01e 编写于 作者: A A. Unique TensorFlower 提交者： TensorFlower Gardener
浏览文件
操作

Go: Update generated wrapper functions for TensorFlow ops. 

Change: 149972913
上级 f51d8c75
隐藏空白更改
内联 并排
Showing with 46 addition and 301 deletion
tensorflow/go/op/wrappers.go
浏览文件 @ 26c5a01e
......@@ -225,6 +225,29 @@ func FakeQuantWithMinMaxVarsPerChannelGradient(scope *Scope, gradients tf.Output
return op.Output(0), op.Output(1), op.Output(2)
}
// Fake-quantize the 'inputs' tensor of type float via global float scalars `min`
//
// and `max` to 'outputs' tensor of same shape as `inputs`.
//
// [min; max] is the clamping range for the 'inputs' data. Op divides this range
// into 255 steps (total of 256 values), then replaces each 'inputs' value with the
// closest of the quantized step values.
//
// This operation has a gradient and thus allows for training `min` and `max` values.
func FakeQuantWithMinMaxVars(scope *Scope, inputs tf.Output, min tf.Output, max tf.Output) (outputs tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "FakeQuantWithMinMaxVars",
Input: []tf.Input{
inputs, min, max,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// QuantizedInstanceNormAttr is an optional argument to QuantizedInstanceNorm.
type QuantizedInstanceNormAttr func(optionalAttr)
......@@ -334,243 +357,6 @@ func QuantizedConcat(scope *Scope, concat_dim tf.Output, values []tf.Output, inp
return op.Output(0), op.Output(1), op.Output(2)
}
// DebugNumericSummaryAttr is an optional argument to DebugNumericSummary.
type DebugNumericSummaryAttr func(optionalAttr)
// DebugNumericSummaryTensorName sets the optional tensor_name attribute to value.
//
// value: Name of the input tensor.
// If not specified, defaults to ""
func DebugNumericSummaryTensorName(value string) DebugNumericSummaryAttr {
return func(m optionalAttr) {
m["tensor_name"] = value
}
}
// DebugNumericSummaryDebugUrls sets the optional debug_urls attribute to value.
//
// value: List of URLs to debug targets, e.g.,
// file:///foo/tfdbg_dump, grpc:://localhost:11011
// If not specified, defaults to <>
func DebugNumericSummaryDebugUrls(value []string) DebugNumericSummaryAttr {
return func(m optionalAttr) {
m["debug_urls"] = value
}
}
// Debug Numeric Summary Op.
//
// Provide a basic summary of numeric value types, range and distribution.
//
// Arguments:
// input: Input tensor, non-Reference type, float or double.
//
// Returns A double tensor of shape [12], the elements of which are:
// [0]: is initialized (1.0) or not (0.0).
// [1]: total number of elements
// [2]: -inf count
// [3]: negative element count (excluding -inf)
// [4]: zero element count
// [5]: positive element count (excluding +inf)
// [6]: +inf element count
// [7]: NaN element count
// Output elements [1:8] are all zero, if the tensor is uninitialized.
// [8]: minimum of all non-inf and non-NaN elements.
// If uninitialized or no such element exists: +inf.
// [9]: maximum of all non-inf and non-NaN elements.
// If uninitialized or no such element exists: -inf.
// [10]: mean of all non-inf and non-NaN elements.
// If uninitialized or no such element exists: NaN.
// [11]: variance of all non-inf and non-NaN elements.
// If uninitialized or no such element exists: NaN.
func DebugNumericSummary(scope *Scope, input tf.Output, optional ...DebugNumericSummaryAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "DebugNumericSummary",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Fake-quantize the 'inputs' tensor of type float via global float scalars `min`
//
// and `max` to 'outputs' tensor of same shape as `inputs`.
//
// [min; max] is the clamping range for the 'inputs' data. Op divides this range
// into 255 steps (total of 256 values), then replaces each 'inputs' value with the
// closest of the quantized step values.
//
// This operation has a gradient and thus allows for training `min` and `max` values.
func FakeQuantWithMinMaxVars(scope *Scope, inputs tf.Output, min tf.Output, max tf.Output) (outputs tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "FakeQuantWithMinMaxVars",
Input: []tf.Input{
inputs, min, max,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// DebugNanCountAttr is an optional argument to DebugNanCount.
type DebugNanCountAttr func(optionalAttr)
// DebugNanCountTensorName sets the optional tensor_name attribute to value.
//
// value: Name of the input tensor.
// If not specified, defaults to ""
func DebugNanCountTensorName(value string) DebugNanCountAttr {
return func(m optionalAttr) {
m["tensor_name"] = value
}
}
// DebugNanCountDebugUrls sets the optional debug_urls attribute to value.
//
// value: List of URLs to debug targets, e.g.,
// file:///foo/tfdbg_dump, grpc:://localhost:11011
// If not specified, defaults to <>
func DebugNanCountDebugUrls(value []string) DebugNanCountAttr {
return func(m optionalAttr) {
m["debug_urls"] = value
}
}
// Debug NaN Value Counter Op
//
// Counts number of NaNs in the input tensor, for debugging.
//
// Arguments:
// input: Input tensor, non-Reference type.
//
// Returns An integer output tensor that is the number of NaNs in the input.
func DebugNanCount(scope *Scope, input tf.Output, optional ...DebugNanCountAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "DebugNanCount",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// DebugIdentityAttr is an optional argument to DebugIdentity.
type DebugIdentityAttr func(optionalAttr)
// DebugIdentityTensorName sets the optional tensor_name attribute to value.
//
// value: Name of the input tensor.
// If not specified, defaults to ""
func DebugIdentityTensorName(value string) DebugIdentityAttr {
return func(m optionalAttr) {
m["tensor_name"] = value
}
}
// DebugIdentityDebugUrls sets the optional debug_urls attribute to value.
//
// value: List of URLs to debug targets, e.g.,
// file:///foo/tfdbg_dump, grpc:://localhost:11011
// If not specified, defaults to <>
func DebugIdentityDebugUrls(value []string) DebugIdentityAttr {
return func(m optionalAttr) {
m["debug_urls"] = value
}
}
// Debug Identity Op.
//
// Provides an identity mapping of the non-Ref type input tensor for debugging.
//
// Arguments:
// input: Input tensor, non-Reference type.
//
// Returns Output tensor that equals the input tensor.
func DebugIdentity(scope *Scope, input tf.Output, optional ...DebugIdentityAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "DebugIdentity",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// CopyAttr is an optional argument to Copy.
type CopyAttr func(optionalAttr)
// CopyTensorName sets the optional tensor_name attribute to value.
//
// value: The name of the input tensor.
// If not specified, defaults to ""
func CopyTensorName(value string) CopyAttr {
return func(m optionalAttr) {
m["tensor_name"] = value
}
}
// Copy Op.
//
// Performs CPU-to-CPU or GPU-to-GPU deep-copying of tensor, depending on the
// device on which the tensor is allocated.
//
// Unlike the CopyHost Op, this op does not have HostMemory constraint on its
// input or output.
//
// Arguments:
// input: Input tensor.
//
// Returns Output tensor, deep-copied from input.
func Copy(scope *Scope, input tf.Output, optional ...CopyAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "Copy",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// QuantizeAndDequantizeAttr is an optional argument to QuantizeAndDequantize.
type QuantizeAndDequantizeAttr func(optionalAttr)
......@@ -5754,11 +5540,11 @@ func RsqrtGrad(scope *Scope, x tf.Output, y tf.Output) (z tf.Output) {
// The graph specifications are serialized by protobuf as graph_transfer_info.
// The implementation / limitations may differ for each platform
// and each available peripheral.
func RemoteFusedGraphExecute(scope *Scope, values []tf.Output, N int64, serialized_graph_transfer_info string) (output []tf.Output) {
func RemoteFusedGraphExecute(scope *Scope, values []tf.Output, N int64, U tf.DataType, serialized_graph_transfer_info string) (output []tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{"N": N, "serialized_graph_transfer_info": serialized_graph_transfer_info}
attrs := map[string]interface{}{"N": N, "U": U, "serialized_graph_transfer_info": serialized_graph_transfer_info}
opspec := tf.OpSpec{
Type: "RemoteFusedGraphExecute",
Input: []tf.Input{
......@@ -11561,26 +11347,6 @@ func ResourceSparseApplyProximalAdagrad(scope *Scope, var_ tf.Output, accum tf.O
return scope.AddOperation(opspec)
}
// Store the input tensor in the state of the current session.
//
// Arguments:
// value: The tensor to be stored.
//
// Returns The handle for the tensor stored in the session state.
func GetSessionHandle(scope *Scope, value tf.Output) (handle tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "GetSessionHandle",
Input: []tf.Input{
value,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Decode web-safe base64-encoded strings.
//
// Input may or may not have padding at the end. See EncodeBase64 for padding.
......@@ -13188,48 +12954,6 @@ func Substr(scope *Scope, input tf.Output, pos tf.Output, len tf.Output) (output
return op.Output(0)
}
// CopyHostAttr is an optional argument to CopyHost.
type CopyHostAttr func(optionalAttr)
// CopyHostTensorName sets the optional tensor_name attribute to value.
//
// value: The name of the input tensor.
// If not specified, defaults to ""
func CopyHostTensorName(value string) CopyHostAttr {
return func(m optionalAttr) {
m["tensor_name"] = value
}
}
// Copy Host Op.
//
// Performs CPU-to-CPU deep-copying of tensor.
//
// Unlike the Copy Op, this op has HostMemory constraint on its input or output.
//
// Arguments:
// input: Input tensor.
//
// Returns Output tensor, deep-copied from input.
func CopyHost(scope *Scope, input tf.Output, optional ...CopyHostAttr) (output tf.Output) {
if scope.Err() != nil {
return
}
attrs := map[string]interface{}{}
for _, a := range optional {
a(attrs)
}
opspec := tf.OpSpec{
Type: "CopyHost",
Input: []tf.Input{
input,
},
Attrs: attrs,
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Computes the sum along sparse segments of a tensor divided by the sqrt of N.
//
// N is the size of the segment being reduced.
......@@ -20029,6 +19753,27 @@ func AdjustContrast(scope *Scope, images tf.Output, contrast_factor tf.Output, m
return op.Output(0)
}
// Store the input tensor in the state of the current session.
//
// Arguments:
// value: The tensor to be stored.
//
// Returns The handle for the tensor stored in the session state, represented
// as a ResourceHandle object.
func GetSessionHandleV2(scope *Scope, value tf.Output) (handle tf.Output) {
if scope.Err() != nil {
return
}
opspec := tf.OpSpec{
Type: "GetSessionHandleV2",
Input: []tf.Input{
value,
},
}
op := scope.AddOperation(opspec)
return op.Output(0)
}
// Restore a Reader to its initial clean state.
//
// Arguments:
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或