diff options
| -rw-r--r-- | tensorflow/go/op/wrappers.go | 40 |
1 files changed, 40 insertions, 0 deletions
diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go index b70c398b2d..0025692146 100644 --- a/tensorflow/go/op/wrappers.go +++ b/tensorflow/go/op/wrappers.go @@ -1268,6 +1268,46 @@ func MirrorPad(scope *Scope, input tf.Output, paddings tf.Output, mode string) ( return op.Output(0) } +// Pads a tensor. +// +// This operation pads `input` according to the `paddings` and `constant_values` +// you specify. `paddings` is an integer tensor with shape `[Dn, 2]`, where n is +// the rank of `input`. For each dimension D of `input`, `paddings[D, 0]` indicates +// how many padding values to add before the contents of `input` in that dimension, +// and `paddings[D, 1]` indicates how many padding values to add after the contents +// of `input` in that dimension. `constant_values` is a scalar tensor of the same +// type as `input` that indicates the value to use for padding `input`. +// +// The padded size of each dimension D of the output is: +// +// `paddings(D, 0) + input.dim_size(D) + paddings(D, 1)` +// +// For example: +// +// ``` +// # 't' is [[1, 1], [2, 2]] +// # 'paddings' is [[1, 1], [2, 2]] +// # 'constant_values' is 0 +// # rank of 't' is 2 +// pad(t, paddings) ==> [[0, 0, 0, 0, 0, 0] +// [0, 0, 1, 1, 0, 0] +// [0, 0, 2, 2, 0, 0] +// [0, 0, 0, 0, 0, 0]] +// ``` +func PadV2(scope *Scope, input tf.Output, paddings tf.Output, constant_values tf.Output) (output tf.Output) { + if scope.Err() != nil { + return + } + opspec := tf.OpSpec{ + Type: "PadV2", + Input: []tf.Input{ + input, paddings, constant_values, + }, + } + op := scope.AddOperation(opspec) + return op.Output(0) +} + // Return the reduction indices for computing gradients of s0 op s1 with broadcast. // // This is typically used by gradient computations for a broadcasting operation. |