From fc6ff59c0c12bedbd1ca32000a24ae9e64c0b661 Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Tue, 19 Jun 2018 03:45:58 -0700 Subject: Go: Update generated wrapper functions for TensorFlow ops. PiperOrigin-RevId: 201150427 --- tensorflow/go/op/wrappers.go | 222 +++++++++++++++++++++---------------------- 1 file changed, 111 insertions(+), 111 deletions(-) (limited to 'tensorflow/go') diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go index a443879df2..bff2264c29 100644 --- a/tensorflow/go/op/wrappers.go +++ b/tensorflow/go/op/wrappers.go @@ -3015,40 +3015,6 @@ func Concat(scope *Scope, concat_dim tf.Output, values []tf.Output) (output tf.O return op.Output(0) } -// Creates a sequence of numbers. -// -// This operation creates a sequence of numbers that begins at `start` and -// extends by increments of `delta` up to but not including `limit`. -// -// For example: -// -// ``` -// # 'start' is 3 -// # 'limit' is 18 -// # 'delta' is 3 -// tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15] -// ``` -// -// Arguments: -// start: 0-D (scalar). First entry in the sequence. -// limit: 0-D (scalar). Upper limit of sequence, exclusive. -// delta: 0-D (scalar). Optional. Default is 1. Number that increments `start`. -// -// Returns 1-D. -func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (output tf.Output) { - if scope.Err() != nil { - return - } - opspec := tf.OpSpec{ - Type: "Range", - Input: []tf.Input{ - start, limit, delta, - }, - } - op := scope.AddOperation(opspec) - return op.Output(0) -} - // Computes gradients for SparseSegmentSqrtN. // // Returns tensor "output" with same shape as grad, except for dimension 0 whose @@ -8309,6 +8275,83 @@ func DataFormatVecPermute(scope *Scope, x tf.Output, optional ...DataFormatVecPe return op.Output(0) } +// Converts each string in the input Tensor to its hash mod by a number of buckets. +// +// The hash function is deterministic on the content of the string within the +// process. +// +// Note that the hash function may change from time to time. +// This functionality will be deprecated and it's recommended to use +// `tf.string_to_hash_bucket_fast()` or `tf.string_to_hash_bucket_strong()`. +// +// Arguments: +// +// num_buckets: The number of buckets. +// +// Returns A Tensor of the same shape as the input `string_tensor`. +func StringToHashBucket(scope *Scope, string_tensor tf.Output, num_buckets int64) (output tf.Output) { + if scope.Err() != nil { + return + } + attrs := map[string]interface{}{"num_buckets": num_buckets} + opspec := tf.OpSpec{ + Type: "StringToHashBucket", + Input: []tf.Input{ + string_tensor, + }, + Attrs: attrs, + } + op := scope.AddOperation(opspec) + return op.Output(0) +} + +// Computes gradients for the exponential linear (Elu) operation. +// +// Arguments: +// gradients: The backpropagated gradients to the corresponding Elu operation. +// outputs: The outputs of the corresponding Elu operation. +// +// Returns The gradients: `gradients * (outputs + 1)` if outputs < 0, +// `gradients` otherwise. +func EluGrad(scope *Scope, gradients tf.Output, outputs tf.Output) (backprops tf.Output) { + if scope.Err() != nil { + return + } + opspec := tf.OpSpec{ + Type: "EluGrad", + Input: []tf.Input{ + gradients, outputs, + }, + } + op := scope.AddOperation(opspec) + return op.Output(0) +} + +// Creates a dataset that contains `count` elements from the `input_dataset`. +// +// Arguments: +// +// count: A scalar representing the number of elements from the `input_dataset` +// that should be taken. A value of `-1` indicates that all of `input_dataset` +// is taken. +// +// +func TakeDataset(scope *Scope, input_dataset tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) { + if scope.Err() != nil { + return + } + attrs := map[string]interface{}{"output_types": output_types, "output_shapes": output_shapes} + opspec := tf.OpSpec{ + Type: "TakeDataset", + Input: []tf.Input{ + input_dataset, count, + }, + Attrs: attrs, + } + op := scope.AddOperation(opspec) + return op.Output(0) +} + // Reads the value of a variable. // // The tensor returned by this operation is immutable. @@ -9918,83 +9961,6 @@ func FixedLengthRecordReaderV2(scope *Scope, record_bytes int64, optional ...Fix return op.Output(0) } -// Converts each string in the input Tensor to its hash mod by a number of buckets. -// -// The hash function is deterministic on the content of the string within the -// process. -// -// Note that the hash function may change from time to time. -// This functionality will be deprecated and it's recommended to use -// `tf.string_to_hash_bucket_fast()` or `tf.string_to_hash_bucket_strong()`. -// -// Arguments: -// -// num_buckets: The number of buckets. -// -// Returns A Tensor of the same shape as the input `string_tensor`. -func StringToHashBucket(scope *Scope, string_tensor tf.Output, num_buckets int64) (output tf.Output) { - if scope.Err() != nil { - return - } - attrs := map[string]interface{}{"num_buckets": num_buckets} - opspec := tf.OpSpec{ - Type: "StringToHashBucket", - Input: []tf.Input{ - string_tensor, - }, - Attrs: attrs, - } - op := scope.AddOperation(opspec) - return op.Output(0) -} - -// Computes gradients for the exponential linear (Elu) operation. -// -// Arguments: -// gradients: The backpropagated gradients to the corresponding Elu operation. -// outputs: The outputs of the corresponding Elu operation. -// -// Returns The gradients: `gradients * (outputs + 1)` if outputs < 0, -// `gradients` otherwise. -func EluGrad(scope *Scope, gradients tf.Output, outputs tf.Output) (backprops tf.Output) { - if scope.Err() != nil { - return - } - opspec := tf.OpSpec{ - Type: "EluGrad", - Input: []tf.Input{ - gradients, outputs, - }, - } - op := scope.AddOperation(opspec) - return op.Output(0) -} - -// Creates a dataset that contains `count` elements from the `input_dataset`. -// -// Arguments: -// -// count: A scalar representing the number of elements from the `input_dataset` -// that should be taken. A value of `-1` indicates that all of `input_dataset` -// is taken. -// -// -func TakeDataset(scope *Scope, input_dataset tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) { - if scope.Err() != nil { - return - } - attrs := map[string]interface{}{"output_types": output_types, "output_shapes": output_shapes} - opspec := tf.OpSpec{ - Type: "TakeDataset", - Input: []tf.Input{ - input_dataset, count, - }, - Attrs: attrs, - } - 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 @@ -19440,6 +19406,40 @@ func OrderedMapIncompleteSize(scope *Scope, dtypes []tf.DataType, optional ...Or return op.Output(0) } +// Creates a sequence of numbers. +// +// This operation creates a sequence of numbers that begins at `start` and +// extends by increments of `delta` up to but not including `limit`. +// +// For example: +// +// ``` +// # 'start' is 3 +// # 'limit' is 18 +// # 'delta' is 3 +// tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15] +// ``` +// +// Arguments: +// start: 0-D (scalar). First entry in the sequence. +// limit: 0-D (scalar). Upper limit of sequence, exclusive. +// delta: 0-D (scalar). Optional. Default is 1. Number that increments `start`. +// +// Returns 1-D. +func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (output tf.Output) { + if scope.Err() != nil { + return + } + opspec := tf.OpSpec{ + Type: "Range", + Input: []tf.Input{ + start, limit, delta, + }, + } + op := scope.AddOperation(opspec) + return op.Output(0) +} + // DestroyResourceOpAttr is an optional argument to DestroyResourceOp. type DestroyResourceOpAttr func(optionalAttr) -- cgit v1.2.3