%cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

          dim {
            size: 4
          }
        }
        float_val: 1.0
        float_val: 2.0
        float_val: 3.0
        float_val: 4.0
      }
    }
  }
}
node {
  name: "cst1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {

    attributes {tf.entry_function = {outputs = "result"}} {
  %cst = arith.constant dense<1> : tensor<i32> loc("dec")
  %cst0 = arith.constant dense<5> : tensor<i32> loc("N")
  %cst1 = arith.constant dense<3.0> : tensor<1xf32> loc("val")
  %0:2 = "tfl.while"(%cst0, %cst1) ({
    ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
      // CHECK: call @WhileOp_cond
      // CHECK-SAME: (tensor<*xi32>, tensor<*xf32>)

          [(ValueEquals<"0.0"> $cst),
           (ValueEquals<"0.0"> $cst1),
           (ValueEquals<"0.0"> $cst2),
           (SameValue $rem, $rem1),
           (SameValue $rem, $rem2),
           (SameValue $rem, $rem3),
           (SameTypeOrDefaultCompare $compare_type, $cst),
           (SameTypeOrDefaultCompare $compare_type1, $cst1)]>;

// Converts a dag of HLOs representing floor_mod with a constant to

      "tfl.yield"(%3) : (tensor<i1>) -> ()
  },  {
    ^bb0(%arg3: tensor<*xi32>, %arg4: tensor<*x!tf_type.resource<tensor<*xi32>>>):
      %cst1 = arith.constant dense<2> : tensor<4xi32>
      "tf.AssignAddVariableOp"(%arg4, %cst1) {} : (tensor<*x!tf_type.resource<tensor<*xi32>>>, tensor<4xi32>) -> ()
      %4 = "tf.ReadVariableOp"(%arg4) {dtype = i32} : (tensor<*x!tf_type.resource<tensor<*xi32>>>) -> tensor<*xi32>

func.func @mixed_no_constant_folding() -> (tensor<f32>) {
  // CHECK:      %[[CST0:.+]] = arith.constant dense<0.000000e+00>
  // CHECK-NEXT: %[[CST1:.+]] = arith.constant dense<0.000000e+00>
  // CHECK-NEXT: "vhlo.add_v1"(%[[CST0]], %[[CST1]]) : (tensor<f32>, tensor<f32>) -> tensor<f32>
  %cst_0 = arith.constant dense<0.000000e+00> : tensor<f32>
  %cst_1 = arith.constant dense<0.000000e+00> : tensor<f32>

  // CHECK-DAG: %[[CST1:.*]] = arith.constant dense<1> : tensor<4xi32>
  // CHECK-DAG: %[[cst_1:.*]] = arith.constant dense<[1, 2, 3, 1]> : tensor<4xi32>
  // CHECK: %0 = "tf.Reshape"(%arg0, %[[cst_1]]) : (tensor<2x3xf32>, tensor<4xi32>) -> tensor<1x2x3x1xf32>

  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<1x4xf32>} : () -> tensor<1x4xf32> loc("Const")

// CHECK: %[[cst1:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 1.000000e-01>>, value = dense<1> : tensor<32x3x3x3xi8>}>
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[cst1]], %[[cst0]])
// CHECK: return %[[conv]] : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}