let description = [{
    This pass looks for the usage of the result of TPUCopyWithDynamicShapeOp
    and sets the shape of these inputs to be dynamic shaped. This will ensure
    that the generated HLO program is correctly reflecting the dynamic shape.
  }];

  // Required for mhlo bounded shape extension.
  let dependentDialects = ["mhlo::MhloDialect"];

### 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