 
 
 
-
-func accumulatorNumAccumulated(scope:Scope,handle: tf.Output)  ->(numAccumulated: tf.Output){
-    if scope.error() != nil {
-        return
-    }
-    let opspec = tf.OpSpec(
-        Type: "AccumulatorNumAccumulated",
-        Input: [ handle]
+func accumulatorNumAccumulated(scope:Scope,handle: tf.Output )  ->(numAccumulated: tf.Output){
+    if scope.error() != nil {
+        return
+    }
+
+    var attrs:Dictionary<String,Tensorflow_AttrValue> = [:]
+
+    let opspec = tf.OpSpec(
+        OpType: "AccumulatorNumAccumulated",
+        Input: [ handle],
         Attrs: attrs
     )
     let op = scope.AddOperation(opspec)





func quantizedReshape(scope:Scope,tensor: tf.Output, shape: tf.Output, inputMin: tf.Output, inputMax: tf.OutputT :type, Tshape :type)  ->(output: tf.Output, outputMin: tf.Output, outputMax: tf.Output){
    if scope.error() != nil {
        return
    }
    let opspec = tf.OpSpec(
        Type: "QuantizedReshape",
        Input: [ tensor, shape, inputMin, inputMax]
        Attrs: attrs
    )
    let op = scope.AddOperation(opspec)




func maxPoolGradGradWithArgmax(scope:Scope,input: tf.Output, grad: tf.Output, argmax: tf.Output, ksize :list(int)  , strides :list(int)  , padding :string  , targmax :type  , t :type  )  ->(output: tf.Output){
    if scope.error() != nil {
        return
    }

    var attrs:Dictionary<String,Tensorflow_AttrValue> = [:]
    attr.append("ksize":ksize)
    attr.append("strides":strides)
    attr.append("padding":padding)
    attr.append("Targmax":targmax)
    attr.append("T":t)

    let opspec = tf.OpSpec(
        OpType: "MaxPoolGradGradWithArgmax",
        Input: [ input, grad, argmax],
        Attrs: attrs
    )
    let op = scope.AddOperation(opspec)
