// CHECK: "tf.BatchMatMulV2"(%arg0, %arg1) <{adj_x = false, adj_y = false, grad_x = false, grad_y = false}> {device = "/job:localhost/replica:0/task:0/device:GPU:0"}
  %0 = "tf.BatchMatMul"(%arg0, %arg1) <{adj_x = false, adj_y = false}> {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<2x3x5xf32>, tensor<2x5x7xf32>) -> tensor<2x3x7xf32>
  func.return %0: tensor<2x3x7xf32>
}

func.func @testBiasAdd(%arg0: tensor<2x3x5x7xf32>, %arg1: tensor<5x7xf32>) -> tensor<2x3x5x7xf32> {
  // expected-error @+1 {{requires bias operand to have rank exactly one}}
  %0 = "tf.BiasAdd"(%arg0, %arg1) {data_format = "NHWC"} : (tensor<2x3x5x7xf32>, tensor<5x7xf32>) -> tensor<2x3x5x7xf32>
  func.return %0 : tensor<2x3x5x7xf32>
}

// -----

func.func @testBiasAdd(%arg0: tensor<2x3x5x7xf32>, %arg1: tensor<5xf32>) -> tensor<2x3x5x7xf32> {

  // CHECK-LABEL: func @shape_partial_eval
  func.func @shape_partial_eval(%arg0: tensor<1x?x7xf32>, %arg1: tensor<3x7xf32>) -> tensor<*xf32> {
    %0 = "tf.Shape"(%arg0) : (tensor<1x?x7xf32>) -> tensor<3xi32>

    // CHECK: tf.Reshape
    // CHECK-SAME: tensor<1x3x7xf32>
    %1 = "tf.Reshape"(%arg1, %0) : (tensor<3x7xf32>, tensor<3xi32>) -> tensor<*xf32>
    return %1 : tensor<*xf32>
  }

}

func.func @gatherNdVectorIndices(%arg0 : tensor<3x2x2xf32>, %arg1 : tensor<2xi32>) -> tensor<2xf32> {
  %0 = "tf.GatherNd"(%arg0, %arg1) : (tensor<3x2x2xf32>, tensor<2xi32>) -> tensor<2xf32>
  func.return %0 : tensor<2xf32>

// CHECK-LABEL:gatherNdVectorIndices
// CHECK:  "tfl.gather_nd"(%arg0, %arg1) : (tensor<3x2x2xf32>, tensor<2xi32>) -> tensor<2xf32>
}