// This file contains operator definitions for TF uniform quantized ops.

include "tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td"
include "mlir/Interfaces/CallInterfaces.td"
include "mlir/Interfaces/InferTypeOpInterface.td"
include "mlir/IR/OpAsmInterface.td"

// TODO(b/230804708): Add hybrid dot general.
def TF_UniformQuantizedDotGeneralOp : TF_Op<"UniformQuantizedDotGeneral", [Pure]> {

==============================================================================*/
#ifdef TF_MLRT_DIALECT
#else
#define TF_MLRT_DIALECT

include "mlir/Interfaces/SideEffectInterfaces.td"
include "tensorflow/compiler/mlir/tfrt/ir/mlrt/mlrt_dialect.td"

// TODO(chky,rohitju): Unify this dialect with tfrt_fallback_sync dialect after
// vrooml is using the new interpreter.
def TensorflowMlrt_Dialect : Dialect {
  let name = "tf_mlrt";

#else
#define TFRT_FALLBACK_ASYNC_OPS

include "tfrt/tfrt_op_base.td"
include "tfrt/compiler/opdefs/tfrt_op_interfaces.td"
include "tfrt/compiler/opdefs/tfrt_traits.td"
include "tfrt/core_runtime/opdefs/corert_base.td"
include "tfrt/core_runtime/opdefs/corert_traits.td"
include "tfrt_fallback.td"
include "mlir/Interfaces/SideEffectInterfaces.td"

def FallbackAsync_Dialect : Dialect {
  let name = "tfrt_fallback_async";

limitations under the License.
==============================================================================*/
include "stablehlo/dialect/StablehloOps.td"
include "mlir/IR/OpBase.td"
include "mlir/IR/BuiltinAttributes.td"
include "mlir/IR/CommonAttrConstraints.td"
include "mlir/IR/CommonTypeConstraints.td"

def CloneF32ElementsAttrWithOnes
  : NativeCodeCall<"DenseElementsAttr::get($0.getType().cast<ShapedType>(), (float)1.0)">;

// This is the legalization pattern definition file for TF to XLA.

include "mlir/IR/OpBase.td"
include "mlir/Dialect/Shape/IR/ShapeOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/Dialect/Tensor/IR/TensorOps.td"
include "stablehlo/dialect/ChloOps.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"
include "mhlo/IR/hlo_ops.td"

def SignedIntTensor : TensorOf<[I1, I8, I16, I32, I64]>;

include "mlir/IR/OpBase.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mhlo/IR/hlo_ops.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"
include "tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_utils.td"
include "tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_avg_pool_patterns.td"

def LegalizeHardSwishComposite: Pat<

==============================================================================*/

#ifdef TFRT_GPU_OPS
#else
#define TFRT_GPU_OPS

include "tfrt/tfrt_op_base.td"
include "tfrt/compiler/opdefs/tfrt_op_interfaces.td"
include "tfrt/compiler/opdefs/tfrt_traits.td"
include "tfrt_fallback.td"

def TFRT_GPU_Dialect : Dialect {
  let name = "gpurt";

  let description = [{
    The TFRT GPU Dialect.
  }];

include "mlir/IR/OpBase.td"
include "mlir/IR/PatternBase.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/IR/CommonTypeConstraints.td"
include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"

// Quantize attribute $0 by using quantization parameter from %1.

#else
#define MLRT_TF_OPS

include "tensorflow/compiler/mlir/tfrt/ir/mlrt/tf_mlrt_dialect.td"
include "tensorflow/compiler/mlir/tfrt/ir/mlrt/mlrt_dialect.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td"
include "tfrt/compiler/opdefs/tfrt_op_interfaces.td"  // from @tf_runtime
include "tfrt/compiler/opdefs/tfrt_traits.td"  // from @tf_runtime

// tf_mlrt.tf_await returns a tensorflow Tensor. It is a fake op that is only

limitations under the License.
==============================================================================*/

// Utility predicates that are shared by multiple passes.

include "mlir/IR/OpBase.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/IR/PatternBase.td"

def CreateNoneValue : NativeCodeCall<
  "$_builder.create<TFL::NoValueOp>($0.getLoc(), $_builder.getUnitAttr())">;

// Returns shape of a ranked tensor.