Add SequenceLSTMOptions to schema to decouple the sequential Op from the LSTM.

PiperOrigin-RevId: 216066634

2 files changed, 17 insertions, 8 deletions

diff --git a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc
index ec9cf38b83..89d57e4599 100644
--- a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc
+++ b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc
@@ -431,7 +431,9 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
 }
 
 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
-  auto* params = reinterpret_cast<TfLiteLSTMParams*>(node->builtin_data);
+  const auto* params =
+      reinterpret_cast<TfLiteUnidirectionalSequenceLSTMParams*>(
+          node->builtin_data);
   const TfLiteTensor* input = GetInput(context, node, kInputTensor);
 
   const TfLiteTensor* input_to_input_weights =
@@ -482,6 +484,12 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 
   TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
 
+  // Copy out the LSTM specific params so they can be passed in the function.
+  TfLiteLSTMParams lstm_params;
+  lstm_params.activation = params->activation;
+  lstm_params.cell_clip = params->cell_clip;
+  lstm_params.proj_clip = params->proj_clip;
+
   switch (input_to_output_weights->type) {
     case kTfLiteFloat32: {
       return lstm_eval::EvalFloat(
@@ -496,7 +504,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
           /*aux_input_to_cell_weights=*/nullptr,
           /*aux_input_to_output_weights=*/nullptr, input_gate_bias,
           forget_gate_bias, cell_bias, output_gate_bias, projection_weights,
-          projection_bias, params, /*forward_sequence=*/true,
+          projection_bias, &lstm_params, /*forward_sequence=*/true,
           /*output_offset=*/0, scratch_buffer, activation_state, cell_state,
           output);
     }
@@ -523,7 +531,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
           /*aux_input_to_cell_weights=*/nullptr,
           /*aux_input_to_output_weights=*/nullptr, input_gate_bias,
           forget_gate_bias, cell_bias, output_gate_bias, projection_weights,
-          projection_bias, params, /*forward_sequence=*/true,
+          projection_bias, &lstm_params, /*forward_sequence=*/true,
           /*output_offset=*/0, scratch_buffer, scaling_factors,
           prod_scaling_factors, recovered_cell_weights, input_quantized,
           /*aux_input_quantized=*/nullptr, activation_state_quantized,
diff --git a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm_test.cc b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm_test.cc
index cd3aac0532..c97b0fdd61 100644
--- a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm_test.cc
+++ b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm_test.cc
@@ -110,11 +110,12 @@ class UnidirectionalLSTMOpModel : public SingleOpModel {
 
     output_ = AddOutput(TensorType_FLOAT32);
 
-    SetBuiltinOp(BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM,
-                 BuiltinOptions_LSTMOptions,
-                 CreateLSTMOptions(builder_, ActivationFunctionType_TANH,
-                                   cell_clip, proj_clip)
-                     .Union());
+    SetBuiltinOp(
+        BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM,
+        BuiltinOptions_UnidirectionalSequenceLSTMOptions,
+        CreateUnidirectionalSequenceLSTMOptions(
+            builder_, ActivationFunctionType_TANH, cell_clip, proj_clip)
+            .Union());
     BuildInterpreter(input_shapes);
   }