float_spl && sgn_cst_spl) {
    return IsSign(float_spl.getValue(), sgn_cst_spl.getValue());
  }
  if (auto int_spl = llvm::dyn_cast_if_present<IntegerAttr>(splat),
      sgn_cst_spl = llvm::dyn_cast_if_present<IntegerAttr>(sgn_splat);
      int_spl && sgn_cst_spl) {
    return IsSign(int_spl.getValue(), sgn_cst_spl.getValue());
  }
  if (mlir::isa<DenseFPElementsAttr>(float_or_int)) {

  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "fused_node_outside_function"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }

  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
}
node {
  name: "_tf.foo"
  op: "foo"
  input: "Constant"
}
library {
  function {
    signature {
      name: "foo"
      input_arg {
        name: "arg"

    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
          dim {
            size: 1
          }
        }
        int_val: 1
      }
    }
  }
}
node {
  name: "func_call"
  op: "test_func_name"
  input: "x"
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
  attr {

          }
        }
        int_val: 0
      }
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "tf.Const1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }

          type: DT_INT32
        }
      }
      attr {
        key: "value"
        value {
          tensor {
            dtype: DT_INT32
            tensor_shape {
            }
            int_val: 0
          }
        }
      }
      experimental_debug_info {
        original_node_names: "Const"
      }
    }
    node_def {
      name: "tf.Greater"
      op: "Greater"

  attr {
    key: "dtype"
    value {
      type: DT_QUINT8
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_QUINT8
        tensor_shape {
        }
        int_val: 7
      }
    }
  }
}
library {
}
versions {
  producer: 70
}

# CHECK: tf.Const
# CHECK-SAME: value = #tf_type<tensor_proto : "{{0[xX][0-9a-fA-F]*}}"> : tensor<!tf_type.quint8>

			NumericRegexp: nil,
			Vars:          []interface{}{"jinzhu?", 1, 999.99, true, []byte("12345"), tt, &tt, nil, "w@g.\"com", myrole, pwd, intVal},

// CHECK-NEXT:         value {
// CHECK-NEXT:           tensor {
// CHECK-NEXT:             dtype: DT_INT32
// CHECK-NEXT:             tensor_shape {
// CHECK-NEXT:             }
// CHECK-NEXT:             int_val: 1
// CHECK-NEXT:           }
// CHECK-NEXT:         }
// CHECK-NEXT:       }
// CHECK:          }
// CHECK:          node_def {
// CHECK-NEXT:       name: "tf.Empty"
// CHECK-NEXT:       op: "Empty"

  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
}
node {
  name: "Case/input_0"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {