@@ -90,7 +90,11 @@ private[api] trait Basic {
9090 * @return Created op output.
9191 */
9292 private [ops] def immutableConstant (
93- dataType : DataType , shape : Shape , memoryRegionName : String , name : String = " ImmutableConstant" ): Output = {
93+ dataType : DataType ,
94+ shape : Shape ,
95+ memoryRegionName : String ,
96+ name : String = " ImmutableConstant"
97+ ): Output = {
9498 Op .Builder (opType = " ImmutableConst" , name = name)
9599 .setAttribute(" dtype" , dataType)
96100 .setAttribute(" shape" , shape)
@@ -123,7 +127,11 @@ private[api] trait Basic {
123127 * @return Created op output.
124128 */
125129 def zerosLike (
126- input : Output , dataType : DataType = null , optimize : Boolean = true , name : String = " ZerosLike" ): Output = {
130+ input : Output ,
131+ dataType : DataType = null ,
132+ optimize : Boolean = true ,
133+ name : String = " ZerosLike"
134+ ): Output = {
127135 val outputDataType = if (dataType != null ) dataType else input.dataType
128136 if (optimize && input.shape.isFullyDefined) {
129137 // We can produce a zeros tensor independent of the value of 'tensor' since the shape is known statically.
@@ -247,8 +255,7 @@ private[api] trait Basic {
247255 * @param name Name for the created op.
248256 * @return Created op output.
249257 */
250- def sparsePlaceholder (
251- dataType : DataType , shape : Shape = null , name : String = " SparsePlaceholder" ): SparseOutput = {
258+ def sparsePlaceholder (dataType : DataType , shape : Shape = null , name : String = " SparsePlaceholder" ): SparseOutput = {
252259 SparseOutput (
253260 indices = placeholder(dataType, Shape (- 1 , - 1 ), name + " /Indices" ),
254261 values = placeholder(INT64 , Shape (- 1 ), name + " /Values" ),
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