message: Fixed dimensions of activation and cell state tensors.
  State tensors are {batch, size} (2D) and not {batch * size} (1D).
diff: @@ -103,9 +103,9 @@ class LSTMOpModel : public SingleOpModel {
  // Adding the 2 input state tensors.
  input_activation_state_ =
  - AddInput(TensorData{TensorType_FLOAT32, {n_output_ * n_batch_}}, true);
  + AddInput(TensorData{TensorType_FLOAT32, {n_batch_, n_output_}}, true);
  input_cell_state_ =
  - AddInput(TensorData{TensorType_FLOAT32, {n_cell_ * n_batch_}}, true);
  + AddInput(TensorData{TensorType_FLOAT32, {n_batch_, n_cell_}}, true);
  // Layer norm weights.
  if (is_layer_norm) {
  @@ -1589,7 +1589,7 @@ TEST_F(NoCifgPeepholeProjectionNoClippingLstmTest, LstmBlackBoxTest) {
  VerifyGoldens(lstm_input_, lstm_golden_output_, &lstm);
  }
  -TEST_F(NoCifgPeepholeProjectionNoClippingLstmTest, HybridLstmBlackBoxTesInt8) {
  +TEST_F(NoCifgPeepholeProjectionNoClippingLstmTest, HybridLstmBlackBoxTestInt8) {
  const int n_batch = 2;
  const int n_input = 5;
  const int n_cell = 20;
  @@ -1626,7 +1626,7 @@ TEST_F(NoCifgPeepholeProjectionNoClippingLstmTest, HybridLstmBlackBoxTesInt8) {
  {n_output, n_cell}, // projection_weight tensor
  {0}, // projection_bias tensor
  },
  - TensorType_UINT8);
  + TensorType_INT8);
  lstm.SetInputToInputWeights(input_to_input_weights_);
  lstm.SetInputToCellWeights(input_to_cell_weights_);
  @@ -1690,7 +1690,7 @@ TEST_F(NoCifgPeepholeProjectionNoClippingLstmTest,
  {n_output, n_cell}, // projection_weight tensor
  {0}, // projection_bias tensor
  },
  - TensorType_INT8);
  + TensorType_UINT8);
  lstm.SetInputToInputWeights(input_to_input_weights_);
  lstm.SetInputToCellWeights(input_to_cell_weights_);
  