}

// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
table BidirectionalSequenceRNNOptions {
  time_major:bool;
  fused_activation_function:ActivationFunctionType;
  merge_outputs: bool;
  asymmetric_quantize_inputs:bool;
}

enum FullyConnectedOptionsWeightsFormat: byte {
  DEFAULT = 0,
  SHUFFLED4x16INT8 = 1,
}

}

// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
table BidirectionalSequenceRNNOptions {
  time_major:bool;
  fused_activation_function:ActivationFunctionType;
  merge_outputs: bool;
  asymmetric_quantize_inputs:bool;
}

// LINT.IfChange
enum FullyConnectedOptionsWeightsFormat: byte {
  DEFAULT = 0,
  SHUFFLED4x16INT8 = 1,
}

  auto _fused_activation_function = _o->fused_activation_function;
  auto _merge_outputs = _o->merge_outputs;
  auto _asymmetric_quantize_inputs = _o->asymmetric_quantize_inputs;
  return tflite::CreateBidirectionalSequenceRNNOptions(
      _fbb,
      _time_major,
      _fused_activation_function,
      _merge_outputs,
      _asymmetric_quantize_inputs);
}

%arg26, %arg27, %arg28, %arg29, %arg30, %arg31, %arg32, %arg33, %arg34, %arg35, %arg36, %arg37, %arg38, %arg39, %arg40, %arg41, %arg42, %arg43, %arg44, %arg45, %arg46, %arg47) <{cell_clip = 1.000000e+00 : f32, fused_activation_function = "NONE", merge_outputs = true, time_major = false}> : (tensor<?x?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>, tensor<?xf32>,...

    ConfinedAttr<DefaultValuedOptionalAttr<F32Attr, "0.0f">, [TFL_FloatNonNegative]>:$cell_clip,
    ConfinedAttr<DefaultValuedOptionalAttr<F32Attr, "0.0f">, [TFL_FloatNonNegative]>:$proj_clip,
    BoolAttr:$merge_outputs,
    BoolAttr:$time_major,
    // Used in post-training dynamic range quantization. If the value is true,
    // input activations are asymmetrically quantized.
    OptionalAttr<BoolAttr>:$asymmetric_quantize_inputs