// 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(

  // Keras lstm tf.api_implements usually has attribute like "lstm_abcde91...".
  // TODO(b/147436982): we need to make sure that only the
  // outputs(full sequence) is used, not the last_output, not the new_states.
  // We will discard everything except the outputs.
  // And the outputs is in the shape of [batch, time, units].
  if (attr.getValue().starts_with("lstm_")) {

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

  // CHECK-DAG:  %[[CST_3:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf32>}> : () -> tensor<4x4xf32>

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

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// Transform pass for LSTMs.

#ifndef TENSORFLOW_COMPILER_MLIR_LITE_TRANSFORMS_PREPARE_QUANTIZE_HELPER_H_
#define TENSORFLOW_COMPILER_MLIR_LITE_TRANSFORMS_PREPARE_QUANTIZE_HELPER_H_

#include <algorithm>
#include <cmath>
#include <memory>

	for s := b; s != nil; s = s.parent {
		if t := s.lstmt; t != nil && t.Label.Value == name {
			return t
		}
	}
	return nil
}

// blockBranches processes a block's statement list and returns the set of outgoing forward jumps.
// all is the scope of all declared labels, parent the set of labels declared in the immediately
// enclosing block, and lstmt is the labeled statement this block is associated with (or nil).

	b := &block{parent: parent, lstmt: lstmt}

	var (
		varDeclPos         token.Pos
		fwdJumps, badJumps []*ast.BranchStmt
	)

	// All forward jumps jumping over a variable declaration are possibly
	// invalid (they may still jump out of the block and be ok).
	// recordVarDecl records them for the given position.

// 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]],

  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;