// CHECK:  return %[[CST]]
}

// CHECK-LABEL: @cast_i64_to_i32
func.func @cast_i64_to_i32() -> tensor<5xi32> {
  %cst = arith.constant dense<[-1, 0, 1, 2147483647, 2147483648]> : tensor<5xi64>
  %0 = "tfl.cast"(%cst) : (tensor<5xi64>) -> tensor<5xi32>
  func.return %0 : tensor<5xi32>

// CHECK: %[[CST:.*]] = arith.constant dense<[-1, 0, 1, 2147483647, -2147483648]> : tensor<5xi32>
// CHECK:  return %[[CST]]
}

}

func.func @conv3d_transpose(%arg0: tensor<2x5x6x8x2xf32>, %arg1: tensor<1x2x2x3x2xf32>, %arg2: tensor<5xi64>) -> tensor<?x?x?x?x?xf32> {
  %0 = "tf.Conv3DBackpropInputV2"(%arg2, %arg1, %arg0) {data_format = "NDHWC", dilations = [1, 1, 1, 1, 1], padding = "VALID", strides = [1, 2, 2, 2, 1]} : (tensor<5xi64>, tensor<1x2x2x3x2xf32>, tensor<2x5x6x8x2xf32>) -> tensor<?x?x?x?x?xf32>
  func.return %0 : tensor<?x?x?x?x?xf32>

  // CHECK: %[[CONCAT_RESHAPE:.*]] = "tf.Reshape"(%[[READ]],
  // CHECK-SAME: -> tensor<15xf32>
  // CHECK: %[[LENS:.*]] = "tf.Const"() <{value = dense<3> : tensor<5xi64>}> : () -> tensor<5xi64>
  %concat:2 = "tf.TensorArrayConcatV3"(%ta#0, %ta#1) {element_shape_except0 = #tf_type.shape<*>} : (tensor<!tf_type.resource>, tensor<f32>) -> (tensor<*xf32>, tensor<*xi64>)

}

// -----

func.func @testEqualOpIncompatibleShapeTrue(%x: tensor<5xf32>, %y: tensor<4xf32>) -> tensor<5xi1> {
  // expected-error @+1 {{operands don't have broadcast-compatible shapes}}
  %0 = "tf.Equal"(%x, %y) {incompatible_shape_error = true} : (tensor<5xf32>, tensor<4xf32>) -> tensor<5xi1>
  func.return %0 : tensor<5xi1>
}

// -----

// CHECK-LABEL: testEqualOpIncompatibleShapeFalse

  // CHECK: %[[INIT:.*]] = mhlo.constant dense<0xFF800000> : tensor<f32>
  // CHECK: "mhlo.reduce_window"(%[[ARG]], %[[INIT]])
  // CHECK: <{window_dimensions = dense<[1, 1, 2, 2, 1]> : tensor<5xi64>, window_strides = dense<[1, 1, 4, 4, 1]> : tensor<5xi64>}>
  // CHECK: mhlo.maximum
  // CHECK: mhlo.return

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uid    DiffPlug LLC <******@****.***>

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