%cst_0 = arith.constant dense<[1, 1, 64]> : tensor<3xi32>
  %0 = "tfl.reshape"(%arg0, %cst_0) : (tensor<1x64xf32>, tensor<3xi32>) -> tensor<1x1x64xf32>
  %1 = "tfl.batch_matmul"(%0, %arg1) {adj_x = false, adj_y = false} : (tensor<1x1x64xf32>, tensor<1x64x1024xf32>) -> tensor<1x1x1024xf32>
  %2 = "tfl.reshape"(%1, %cst) : (tensor<1x1x1024xf32>, tensor<2xi32>) -> tensor<1x1024xf32>
  return %2 : tensor<1x1024xf32>

  // CHECK: [[RESHAPE:%.*]] = mhlo.reshape [[SLICE]] : (tensor<2x16x2xf32>) -> tensor<2x16x2xf32>
  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) {Index = i32, T = f32} : (tensor<10x16x2xf32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<2x16x2xf32>
  // CHECK: return [[RESHAPE]] : tensor<2x16x2xf32>
  func.return %0 : tensor<2x16x2xf32>
}

// -----

// CHECK:           %[[VAL_9:.*]] = "tf.Reshape"(%[[VAL_5]], %[[VAL_8]]) : (tensor<3x2x6x4xf32>, tensor<3xi64>) -> tensor<3x12x4xf32>
// CHECK:           %[[VAL_10:.*]] = "tf.BatchMatMulV3"(%[[VAL_7]], %[[VAL_9]]) <{adj_x = false, adj_y = false, grad_x = false, grad_y = false}> : (tensor<3x5x12xf32>, tensor<3x12x4xf32>) -> tensor<3x5x4xf32>
// CHECK:           %[[VAL_11:.*]] = arith.constant dense<[3, 5, 1, 4]> : tensor<4xi64>