// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure lstm roundtrip exactly

// CHECK: {
// CHECK-NEXT:   version: 3,
// CHECK-NEXT:   operator_codes: [ {
// CHECK-NEXT:     deprecated_builtin_code: 16,
// CHECK-NEXT:     version: 1,
// CHECK-NEXT:     builtin_code: LSTM
// CHECK-NEXT:   } ],
// CHECK-NEXT:   subgraphs: [ {
// CHECK-NEXT:     tensors: [ {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       buffer: 1,
// CHECK-NEXT:       name: "arg0",

Christian Sigg <******@****.***> 1714543668 -0700

      lstm_func.emitWarning(
          "we cannot fuse this lstm func because all the inputs have not "
          "ranked tensor type.");
      return failure();
    }
    switch (i) {
      case 1:  // output_init_state
      case 2:  // hidden_init_state
        if (!input_type.hasStaticShape()) {
          lstm_func.emitWarning(
              "we cannot fuse this lstm func because the batch size is not "

  // The func will ultimately return the output of the fused
  // LSTM op.
  UpdateFuncSignature();

  // Transform the weights, projection, bias and layer norm coefficients
  // to generate operands for the TFL fused LSTM op.
  GenerateFusedOpOperands();

  // Create the fused LSTM op.
  SmallVector<int64_t, 2> output_shape = {1, n_output_};
  auto result_type = mlir::RankedTensorType::get(

    "LayerNormalizedLstmCellSimple";
constexpr char kCoupleInputForgetGates[] = "CoupleInputForgetGates";

// A utility class that enables the conversion of the LSTMCellSimple composite
// op into a fused TFL LSTM op. The fused op is contained within a FuncOp
// that also contains other supporting ops needed to construct the operands for
// the fused op. The caller provides the containing FuncOp as input with

// CHECK-DAG: %[[input_23:.*]] = "tfl.dequantize"({{.*}}) : (tensor<2x!quant.uniform<i16<-32767:32767>:f32, 2.736719606284107E-5>>) -> tensor<2xf32>

// CHECK: %[[lstm:.*]] = "tfl.lstm"(%[[input_0]], %[[none]], %[[input_2]], %[[input_3]], %[[input_4]], %[[none]], %[[input_6]], %[[input_7]], %[[input_8]],

// CHECK: {
// CHECK-NEXT:   version: 3,
// CHECK-NEXT:   operator_codes: [ {
// CHECK-NEXT:     deprecated_builtin_code: 16,
// CHECK-NEXT:     version: 1,
// CHECK-NEXT:     builtin_code: LSTM
// CHECK-NEXT:   } ],
// CHECK-NEXT:   subgraphs: [ {
// CHECK-NEXT:     tensors: [ {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       buffer: 1,
// CHECK-NEXT:       name: "arg0",

  alpha:float;
  beta:float;
}

enum LSTMKernelType : byte {
  // Full LSTM kernel which supports peephole and projection.
  FULL = 0,
  // Basic LSTM kernels. Equivalent to TensorFlow BasicLSTMCell.
  BASIC = 1,
}

// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
table LSTMOptions {
  // Parameters for LSTM version 1 or above.
  fused_activation_function:ActivationFunctionType;

  alpha:float;
  beta:float;
}

enum LSTMKernelType : byte {
  // Full LSTM kernel which supports peephole and projection.
  FULL = 0,
  // Basic LSTM kernels. Equivalent to TensorFlow BasicLSTMCell.
  BASIC = 1,
}

// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
table LSTMOptions {
  // Parameters for LSTM version 1 or above.
  fused_activation_function:ActivationFunctionType;