// CHECK: return %[[v3:.*]] : tensor<5x7xf32>
}

func.func @einsum_transpose_matmul(%arg0: tensor<2x5x7xf32>, %arg1: tensor<5x3x2xf32>) -> tensor<5x3x7xf32> {
  %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "lbh,bkl->bkh"}: (tensor<2x5x7xf32>, tensor<5x3x2xf32>) -> tensor<5x3x7xf32>
  func.return %0 : tensor<5x3x7xf32>
  // CHECK-LABEL: einsum_transpose_matmul

    func.func @main() -> (tensor<5x11xf32>) {
      %arg0 = "tf.Const"() {value = dense<-3.0> : tensor<5x7xf32>} : () -> tensor<5x7xf32>
      %arg1 = "tf.Const"() {value = dense<-3.0> : tensor<11x7xf32>} : () -> tensor<11x7xf32>

      %1 = "tf.MatMul"(%arg0, %arg1) {transpose_a = false, transpose_b = true} : (tensor<5x7xf32>, tensor<11x7xf32>) -> tensor<5x11xf32>

      func.return %1 : tensor<5x11xf32>
    }
  })";

// Test scatter into existing tensor list.

// CHECK-LABEL: func @main
// CHECK-SAME: (%[[ARG0:.*]]: tensor<10x8x9xf32>, %[[ARG1:.*]]: tensor<5xi32>, %[[ARG2:.*]]: tensor<5x8x9xf32>) -> tensor<10x8x9xf32>
func.func @main(%arg0: tensor<10x8x9xf32>, %arg1: tensor<5xi32>, %arg2: tensor<5x8x9xf32>) -> tensor<10x8x9xf32> {
  %elem_shape = "tf.Const"() {value = dense<[8, 9]> : tensor<2xi32>} : () -> tensor<2xi32>

}

// -----

func.func @trivial_dynamic_update_slice_wrong_update_shape(%arg0: tensor<2x7x14xf32>, %arg1: tensor<2x7x7xf32>) -> tensor<2x7x14xf32> {
  %0 = arith.constant dense<0> : tensor<3xi32>
  %1 = "tfl.dynamic_update_slice"(%arg0, %arg1, %0) : (tensor<2x7x14xf32>, tensor<2x7x7xf32>, tensor<3xi32>) -> tensor<2x7x14xf32>
  // CHECK: "tfl.dynamic_update_slice"
  func.return %1 : tensor<2x7x14xf32>
}

// CHECK-LABEL: @ShapeOpI32
func.func @ShapeOpI32(%arg0 : tensor<576x72xf32>) -> tensor<2xi32> {
  %0 = "tfl.shape"(%arg0) : (tensor<576x72xf32>) -> tensor<2xi32>
  func.return %0 : tensor<2xi32>
  // CHECK: %[[CST:.*]] = arith.constant dense<[576, 72]> : tensor<2xi32>
  // CHECK:  return %[[CST]]
}

// CHECK-LABEL: @ShapeOpI64
func.func @ShapeOpI64(%arg0 : tensor<576x72xf32>) -> tensor<2xi64> {

// RUN: odml-to-stablehlo-opt %s -tfl-legalize-hlo -split-input-file | FileCheck %s --dump-input=fail

func.func @main(%arg0: tensor<5x7xf32>) -> tensor<5x7xf32> {
  func.return %arg0: tensor<5x7xf32>
// CHECK-LABEL: main
// CHECK: return %arg0 : tensor<5x7xf32>
}

// - transpose
//
func.func @transpose_2d(%arg0: tensor<2x3xf32>) -> tensor<3x2xf32> {