// CHECK: return %[[RESULT0]]
}

// CHECK-LABEL: testMatmulAsymAttributeTrue
func.func @testMatmulAsymAttributeTrue(%arg0: tensor<4x10x15xf32>, %arg1: tensor<4x15x17xf32>) -> tensor<4x10x17xf32> {
  %0 = "tfl.batch_matmul"(%arg0, %arg1) {adj_x = false, adj_y = false, asymmetric_quantize_inputs = true} : (tensor<4x10x15xf32>, tensor<4x15x17xf32>) -> tensor<4x10x17xf32>

}

func.func @matmul_batchv3_unknown_dim(%arg0: tensor<?x10x15xf32>, %arg1: tensor<15x17xf32>) -> tensor<?x10x17xf32> {
  %0 = "tf.BatchMatMulV3"(%arg0, %arg1) {Ta = "tfdtype$DT_FLOAT", Tb = "tfdtype$DT_FLOAT", device = "/device:CPU:0", name = "MatMul", adj_x = false, adj_y = false} :
(tensor<?x10x15xf32>, tensor<15x17xf32>) -> tensor<?x10x17xf32>

  %3 = "tf.Transpose"(%arg4, %2) : (tensor<10x4xf32>, tensor<2xi32>) -> tensor<4x10xf32>
  %4 = "tf.MatrixDiag"(%3) : (tensor<4x10xf32>) -> tensor<4x10x10xf32>
  %5 = "tf.Const"() { value = dense<0> : tensor<i64> } : () -> tensor<i64>
  %6 = "tf.ConcatV2"(%4, %5) : (tensor<4x10x10xf32>, tensor<i64>) -> tensor<40x10xf32>
  %7 = "tf.BatchMatMulV2"(%1, %6) {adj_x = false, adj_y = false} : (tensor<8x8x40xf32>, tensor<40x10xf32>) -> tensor<8x8x10xf32>

  %0 = "tf.SpaceToBatchND"(%input, %block_shape, %paddings) : (tensor<3x5x7x9x10x11xf32>, tensor<3xi64>, tensor<3x2xi64>) -> tensor<?x?x?x?x10x11xf32>
  func.return %0 : tensor<?x?x?x?x10x11xf32>
}

// CHECK-LABEL: func @batchToSpace
func.func @batchToSpace(%arg0: tensor<3x5x2xf32>) -> (tensor<1x8x2xf32>) {

}

// CHECK-LABEL: @FuseExcessBroadcastingOnReshapesDynamicShapes
func.func @FuseExcessBroadcastingOnReshapesDynamicShapes(%arg0: tensor<?x10x1xf32>, %arg1: tensor<6xi32>, %arg2: tensor<6xi32>, %arg3: tensor<2xi32>) -> tensor<?x50xf32> {
    %1196 = "tfl.reshape"(%arg0, %arg1) : (tensor<?x10x1xf32>, tensor<6xi32>) -> tensor<1x?x1x10x1x1xf32>

}

// -----

func.func @testBatchMatMulV2InvalidOutputBatchDimension(%lhs: tensor<10x2x5x10xf32>, %rhs: tensor<2x10x10xf32>) {
  // expected-error @+1 {{has mismatching input batch dimension 2 and output batch dimension 3}}
  %0 = "tf.BatchMatMulV2"(%lhs, %rhs) : (tensor<10x2x5x10xf32>, tensor<2x10x10xf32>) -> tensor<10x3x10x10xf32>
}

// -----