diff --git a/tensorflow/lite/experimental/writer/option_writer_generator.cc b/tensorflow/lite/experimental/writer/option_writer_generator.cc
index a565422457c..898f4a95ef6 100644
--- a/tensorflow/lite/experimental/writer/option_writer_generator.cc
+++ b/tensorflow/lite/experimental/writer/option_writer_generator.cc
@@ -265,6 +265,29 @@ void GenerateImportForResizeBilinearOp(FILE* fp) {
           "  }\n  break;\n");
 }
 
+// Reshape Op infers output shape either from Parameter or from shape tensor
+// that's is an additional input. When we have this additional shape tensor as
+// input we don't have the parameter present in this layer. In case of more than
+// one input we import an empty vector for the parameters.
+void GenerateImportForReshapeOp(FILE* fp) {
+  fprintf(fp,
+          "  case BuiltinOperator_RESHAPE:  {\n"
+          "    const auto* params = reinterpret_cast<const "
+          "TfLiteReshapeParams*>(builtin_op_data);\n"
+          "    flatbuffers::Offset<void> union_type;\n"
+          "    if (node.inputs->size > 1) {\n"
+          "      union_type = CreateReshapeOptions(*fbb).Union();\n"
+          "    } else {\n"
+          "      auto val0 = fbb->CreateVector(std::vector<int>(params->shape, "
+          "params->shape + params->num_dimensions));\n"
+          "      union_type = CreateReshapeOptions(*fbb, "
+          "val0).Union();\n"
+          "    }\n"
+          "    return std::make_pair(BuiltinOptions_ReshapeOptions, "
+          "union_type);\n"
+          "  }\n  break;\n");
+}
+
 void GenerateImportForOp(FILE* fp, const std::string& op_name,
                          const std::string& option_name,
                          const std::string& option_type,
@@ -276,6 +299,13 @@ void GenerateImportForOp(FILE* fp, const std::string& op_name,
     return;
   }
 
+  // Special case Reshape that may have 'new_shape' field missing from the
+  // parameters.
+  if (struct_name == "TfLiteReshapeParams") {
+    GenerateImportForReshapeOp(fp);
+    return;
+  }
+
   fprintf(fp, "  case BuiltinOperator_%s:  {\n", op_name.c_str());
   if (options->num_elems != 0) {
     fprintf(fp,
diff --git a/tensorflow/lite/experimental/writer/writer_lib.cc b/tensorflow/lite/experimental/writer/writer_lib.cc
index ed26c7f9038..2f509daa9cb 100644
--- a/tensorflow/lite/experimental/writer/writer_lib.cc
+++ b/tensorflow/lite/experimental/writer/writer_lib.cc
@@ -31,7 +31,7 @@ namespace tflite {
 
 std::pair<BuiltinOptions, flatbuffers::Offset<void>> CreateBuiltinUnion(
     flatbuffers::FlatBufferBuilder* fbb, enum BuiltinOperator op,
-    void* builtin_op_data) {
+    void* builtin_op_data, const TfLiteNode& node) {
   switch (op) {
 #include "tensorflow/lite/experimental/writer/option_writer_generated.h"
   }
@@ -82,7 +82,7 @@ SubgraphWriter::ExportOperators(flatbuffers::FlatBufferBuilder* fbb) {
       // builtin
       auto builtin_options_and_type = CreateBuiltinUnion(
           fbb, static_cast<enum BuiltinOperator>(registration.builtin_code),
-          node.builtin_data);
+          node.builtin_data, node);
       builtin_options = builtin_options_and_type.second;
       builtin_options_type = builtin_options_and_type.first;
     } else {
diff --git a/tensorflow/lite/experimental/writer/writer_lib_test.cc b/tensorflow/lite/experimental/writer/writer_lib_test.cc
index 41cca88ead7..fb59482f705 100644
--- a/tensorflow/lite/experimental/writer/writer_lib_test.cc
+++ b/tensorflow/lite/experimental/writer/writer_lib_test.cc
@@ -15,6 +15,9 @@ limitations under the License.
 
 #include "tensorflow/lite/experimental/writer/writer_lib.h"
 
+#include <numeric>
+#include <sstream>
+
 #include <gtest/gtest.h>
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/interpreter.h"
@@ -184,6 +187,83 @@ TEST(Writer, PerTensorQuantizedModelTest) {
   CHECK_EQ(new_interpreter->AllocateTensors(), kTfLiteOk);
 }
 
+struct ReshapeTestPattern {
+  int num_inputs;
+  bool is_param_valid;
+};
+
+class ReshapeLayerTest : public ::testing::TestWithParam<ReshapeTestPattern> {};
+
+TEST_P(ReshapeLayerTest, ReshapeLayerTest) {
+  const auto param = GetParam();
+  Interpreter interpreter;
+  const int total_tensors = param.num_inputs + 1;
+  interpreter.AddTensors(total_tensors);
+  int output_shape[] = {1, 2, 3};
+  interpreter.SetTensorParametersReadWrite(/*tensor_index=*/0, kTfLiteFloat32,
+                                           /*name=*/"a", /*dims=*/{6},
+                                           TfLiteQuantization());
+  ASSERT_LE(param.num_inputs, 2);
+  if (param.num_inputs == 2) {
+    interpreter.SetTensorParametersReadOnly(
+        /*tensor_index=*/1, kTfLiteInt32, /*name=*/"b", /*dims=*/{3},
+        TfLiteQuantization(), reinterpret_cast<char*>(output_shape),
+        sizeof(output_shape));
+  }
+  interpreter.SetTensorParametersReadWrite(/*tensor_index=*/total_tensors - 1,
+                                           kTfLiteFloat32, /*name=*/"c",
+                                           /*dims=*/{3}, TfLiteQuantization());
+
+  std::vector<int> input_tensors(param.num_inputs);
+  std::iota(input_tensors.begin(), input_tensors.end(), 0);
+
+  interpreter.SetInputs(input_tensors);
+  interpreter.SetOutputs({total_tensors - 1});
+  const char* initial_data = "";
+  tflite::ops::builtin::BuiltinOpResolver resolver;
+  TfLiteReshapeParams* builtin_data = reinterpret_cast<TfLiteReshapeParams*>(
+      malloc(sizeof(TfLiteReshapeParams)));
+  if (param.is_param_valid) {
+    builtin_data->num_dimensions = 3;
+    for (int dim = 0; dim < builtin_data->num_dimensions; ++dim) {
+      builtin_data->shape[dim] = output_shape[dim];
+    }
+  }
+  const TfLiteRegistration* reg = resolver.FindOp(BuiltinOperator_RESHAPE, 1);
+  interpreter.AddNodeWithParameters(input_tensors,
+                                    /*outputs=*/{total_tensors - 1},
+                                    initial_data, /*init_data_size=*/0,
+                                    reinterpret_cast<void*>(builtin_data), reg);
+
+  SubgraphWriter writer(&interpreter.primary_subgraph());
+  std::stringstream ss;
+  ss << "/tmp/test_reshape_" << param.num_inputs << param.is_param_valid
+     << ".tflite";
+  std::string filename = ss.str();
+  writer.Write(filename);
+  std::unique_ptr<FlatBufferModel> model =
+      FlatBufferModel::BuildFromFile(filename.c_str());
+  InterpreterBuilder builder(*model, resolver);
+  std::unique_ptr<Interpreter> new_interpreter;
+  builder(&new_interpreter);
+  ASSERT_EQ(new_interpreter->AllocateTensors(), kTfLiteOk);
+}
+
+INSTANTIATE_TEST_SUITE_P(
+    Writer, ReshapeLayerTest,
+    ::testing::Values(ReshapeTestPattern{/*num_inputs=*/2,
+                                         /*is_param_valid=*/true},
+                      ReshapeTestPattern{/*num_inputs=*/2,
+                                         /*is_param_valid=*/false},
+                      ReshapeTestPattern{/*num_inputs=*/1,
+                                         /*is_param_valid=*/true}),
+    [](const ::testing::TestParamInfo<ReshapeLayerTest::ParamType>& info) {
+      std::stringstream ss;
+      ss << "num_inputs_" << info.param.num_inputs << "_valid_param_"
+         << info.param.is_param_valid;
+      std::string name = ss.str();
+      return name;
+    });
 }  // namespace tflite
 
 int main(int argc, char** argv) {