func.return %0 : tensor<5x11xf32>
}

// Verify that MatMul with ranked inputs are lowered to HLO.
// CHECK-LABEL: matmul_ranked
func.func @matmul_ranked(%a: tensor<?x7xf32>, %b: tensor<7x?xf32>) -> tensor<?x?xf32> {
  // CHECK: "mhlo.dot"

### XLA Support:

*   xla.experimental.compile is deprecated, use
    `tf.function(experimental_compile=True)` instead.
*   Adds `tf.function.experimental_get_compiler_ir` which returns compiler IR
    (currently 'hlo' and 'optimized_hlo') for given input for given function.

### Security:

*   Fixes an undefined behavior causing a segfault in `tf.raw_ops.Switch`,

// NOTE: Assertions have been autogenerated by utils/generate-test-checks.py
// RUN: odml-to-stablehlo-opt -tf-legalize-hlo -verify-diagnostics %s | FileCheck %s

// CHECK-LABEL:   func @biasAdd_NHWC(
// CHECK-SAME:                       %[[VAL_0:.*]]: tensor<1x32x10x32xi32>,
// CHECK-SAME:                       %[[VAL_1:.*]]: tensor<32xi32>) -> tensor<1x32x10x32xi32> {

  TF_DerivedResultTypeAttr preferred_element_type = TF_DerivedResultTypeAttr<0>;

  let hasVerifier = 1;
}

def TF_XlaCustomCallV2Op : TF_Op<"XlaCustomCallV2", [Pure]> {
  let summary = "Emits an HLO `CustomCall` operation with multiple outputs.";

  let description = [{
As opposed to `XlaCustomCall`, this operation supports multiple outputs.

See `CustomCall` specification at