attributes  {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} {
    %0:2 = tf_executor.graph {
      %1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) {T = ["tfdtype$DT_FLOAT", "tfdtype$DT_INT32"], device = "", name = "identity"} : (tensor<*xf32>, tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32>)
      tf_executor.fetch %1#0, %1#1 : tensor<*xf32>, tensor<2x4x6x8xi32>
    }

  attributes  {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} {
    %0:2 = tf_executor.graph {
      %1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) {T = ["tfdtype$DT_FLOAT", "tfdtype$DT_INT32"], device = "", name = "identity"} : (tensor<*xf32>, tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32>)
      tf_executor.fetch %1#0, %1#1 : tensor<*xf32>, tensor<2x4x6x8xi32>
    }

Aditya Manthramurthy <******@****.***> 1714599073 -0700

Laura Kassovic <******@****.***> 1701107622 -0800

  %val1 = "tf.Identity"(%val0) {_class = ["loc:@v"]} : (tensor<96x!tf_type.f32ref>) -> tensor<96xf32>
  func.return
}

// -----

// Test case: Two ReadVariable ops.

func.func @f() {
  // CHECK: "tf.VarHandleOp"

  // During lowering to resource variables, this pass will preserve the
  // locations of the ReadVariableOps as Identity ops to keep the original graph
  // composition and order.

     */
    String getName(T element);

    /**
     * Returns the original identity name of the given element which
     * may be used to uniquely identify the element if the name returned
     * by getName() is not unique in the hierarchy.
     *
     * @param element the element, cannot be null
     * @return the identity name of the element, never null
     */
    String getIdentityName(T element);

    /**

//
// input   min cst       max cst          input   min cst       max cst
//  \       |             |                \       |             |
//   \  (tf.Identity) (tf.Identity)   =>    \  (tf.Identity) (tf.Identity)
//    \     |             |                  \     |             |
//       tf.FakeQuantWithMinMaxVars       tf.FakeQuantWithMinMaxVars
//                   |                                 |

  //tensorflow/c/experimental/ops/gen:generate_cpp -- \
  --output_dir="${current_dir}" \
  --api_dirs="${api_dir}" \
  --source_dir=third_party/tensorflow"

${generate} \
  --category=array \
  Identity \
  IdentityN \
  ZerosLike \
  Shape \
  ExpandDims \
  OnesLike

${generate} \
  --category=math \
  Mul \
  Conj \
  AddV2 \
  MatMul \
  Neg \
  Sum \
  Sub \
  Div \
  DivNoNan \

Laura Kassovic <******@****.***> 1701107622 -0800

Laura Kassovic <******@****.***> 1701107622 -0800