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Go: Update generated wrapper functions for TensorFlow ops.

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Change: 149040924
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A. Unique TensorFlower 2017-03-02 13:34:54 -08:00 committed by TensorFlower Gardener
parent c35d9489b0
commit c28b1ec2ef
1 changed files with 12 additions and 6 deletions
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18
tensorflow/go/op/wrappers.go
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@ -10134,9 +10134,9 @@ func Conv2DUseCudnnOnGpu(value bool) Conv2DAttr {
//
// value: Specify the data format of the input and output data. With the
// default format "NHWC", the data is stored in the order of:
// [batch, in_height, in_width, in_channels].
// [batch, height, width, channels].
// Alternatively, the format could be "NCHW", the data storage order of:
// [batch, in_channels, in_height, in_width].
// [batch, channels, height, width].
// If not specified, defaults to s:"NHWC"
func Conv2DDataFormat(value string) Conv2DAttr {
return func(m optionalAttr) {
@ -10169,11 +10169,17 @@ func Conv2DDataFormat(value string) Conv2DAttr {
// horizontal and vertices strides, `strides = [1, stride, stride, 1]`.
//
// Arguments:
//
//
// strides: 1-D of length 4. The stride of the sliding window for each dimension
// of `input`. Must be in the same order as the dimension specified with format.
// input: A 4-D tensor. The dimension order is interpreted according to the value
// of `data_format`, see below for details.
// filter: A 4-D tensor of shape
// `[filter_height, filter_width, in_channels, out_channels]`
// strides: 1-D tensor of length 4. The stride of the sliding window for each
// dimension of `input`. The dimension order is determined by the value of
// `data_format`, see below for details.
// padding: The type of padding algorithm to use.
//
// Returns A 4-D tensor. The dimension order is determined by the value of
// `data_format`, see below for details.
func Conv2D(scope *Scope, input tf.Output, filter tf.Output, strides []int64, padding string, optional ...Conv2DAttr) (output tf.Output) {
if scope.Err() != nil {
return