llvm::SmallVector<Value>& outputs);

  // Tries to legalize the specified TensorFlow op, if supported.
  //
  // Emits an error and returns failure if an error is encountered during
  // conversion. Note that success return value doesn't mean successful
  // legalization.
  mlir::LogicalResult LegalizeOp();

  // Converts the given operand to expression of kind kConstant or kXlaOp.

// RUN: tf-opt %s -tfl-legalize-tf --cse -split-input-file| FileCheck %s --dump-input=fail

func.func @add(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
  %0 = "tf.Add"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  func.return %0: tensor<1xf32>

// CHECK-LABEL: add
// CHECK:  tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<1xf32>
// CHECK:  return
}

  ];
}

def LegalizeHloToTfPass : Pass<"tf-legalize-hlo", "ModuleOp"> {
  let summary = "Legalize from MHLO to the TF dialect";
  let dependentDialects = ["TF::TensorFlowDialect"];
  let constructor = "mlir::odml::CreateLegalizeHloToTfPass()";
}

def LegalizeHloToTfLitePass : Pass<"tfl-legalize-hlo", "mlir::ModuleOp"> {
  let summary = "Legalize from MHLO to the TFLite dialect";

    name = "all_tests",
    data = [":test_utilities"],
    driver = "@llvm-project//mlir:run_lit.sh",
    size_override = {
        "legalize-tf-binary-elementwise.mlir": "medium",
        "legalize-tf-include-tf2xla-fallback.mlir": "medium",
        "legalize-tf-prefer-tf2xla.mlir": "medium",
        "legalize-tf.mlir": "medium",
    },
    test_file_exts = [
        "mlir",
        "hlotxt",
    ],
)

// RUN: tf-opt -split-input-file -verify-diagnostics -xla-legalize-tf-communication %s | FileCheck %s

// Test legalization of `tf._XlaHostComputeMlir` expands into individual
// `mhlo.send` per operand and `mhlo.recv` per result. Channel Id's are uniquely
// assigned per mhlo communcation op, and frontend attributes (modified keys)
// and op shardings are added. Sink tokens are created
// if there are more than one operand or more than one result.
//

// -----

// ============================================================================
// The following functions tests example quantization patterns outputted from
// StableHLO Quantizer. These patterns should be legalized early directly
// to fused tflite ops.
// ============================================================================

// Tests that a simple per-channel quantized `stablehlo.dot_general` is properly

  // expected-error @+1 {{Could not legalize op: tf.Const}}
  %cst_0 = "tf.Const"() {value = dense<(1.000000e+00,1.000000e+00)> : tensor<8x64x128xcomplex<f32>>} : () -> tensor<8x64x128xcomplex<f32>>
  // expected-error @+1 {{Could not legalize op: tf.XlaEinsum}}

// RUN: tf-opt "-tfxla-verify-legalization=legalize-chlo=false" -verify-diagnostics -split-input-file %s | FileCheck %s --dump-input=fail
// Tests the VerifyTFXLALegalization Pass, that just ensures we don't have
// any illegal ops at the end of the pipeline. This runs with
// legalize-chlo=false since errors can't be mixed with the legalize-chlo=True
// version.

// CHECK-LABEL: allows_chlo

                            bool smuggle_disallowed_ops);

// This function is a common entry point for all graph optimizations that are
// not specific to any hardware. It legalizes SHLO->MHLO, does MHLO->MHLO
// optimizations by calling `AddMhloOptimizationPasses` internally, and
// legalizes MHLO->SHLO
void AddStablehloOptimizationPasses(OpPassManager& pm);

// Adds all the backend-agonstic stableHLO optimization passes

// Create a pass that legalizes MHLO to TF dialect.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeHloToTfPass();

// Creates a pass which replaces a splat constant tensor with a BroadcastInDim
// op.
std::unique_ptr<OperationPass<ModuleOp>> CreateUnfoldSplatConstantPass();

// Create a pass that legalizes MHLO to TFLite dialect.