diff --git a/mediapipe/calculators/pytorch/BUILD b/mediapipe/calculators/pytorch/BUILD
index 2bb86766c..9711e39fc 100644
--- a/mediapipe/calculators/pytorch/BUILD
+++ b/mediapipe/calculators/pytorch/BUILD
@@ -134,3 +134,17 @@ cc_test(
         "//mediapipe/framework/port:parse_text_proto",
     ],
 )
+
+cc_test(
+    name = "pytorch_inference_calculator_test",
+    srcs = ["pytorch_inference_calculator_test.cc"],
+    deps = [
+        ":pytorch_inference_calculator",
+        ":pytorch_inference_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:image_frame",
+        "//mediapipe/framework/formats:image_frame_opencv",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+    ],
+)
diff --git a/mediapipe/calculators/pytorch/pytorch_inference_calculator_test.cc b/mediapipe/calculators/pytorch/pytorch_inference_calculator_test.cc
new file mode 100644
index 000000000..94f3e1484
--- /dev/null
+++ b/mediapipe/calculators/pytorch/pytorch_inference_calculator_test.cc
@@ -0,0 +1,165 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+// #include <memory>
+// #include <string>
+// #include <vector>
+
+// #include "absl/strings/str_replace.h"
+// #include "absl/strings/string_view.h"
+#include "mediapipe/calculators/pytorch/pytorch_inference_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+// #include "mediapipe/framework/calculator_runner.h"
+// #include "mediapipe/framework/deps/file_path.h"
+// #include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+// #include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status_matchers.h"  // NOLINT
+// #include "mediapipe/framework/tool/validate_type.h"
+
+namespace mediapipe {
+
+using ::tflite::Interpreter;
+
+void DoSmokeTest(const std::string& graph_proto) {
+  const int width = 8;
+  const int height = 8;
+  const int channels = 3;
+
+  // Prepare input tensor.
+  std::unique_ptr<Interpreter> interpreter(new Interpreter);
+  ASSERT_NE(interpreter, nullptr);
+
+  interpreter->AddTensors(1);
+  interpreter->SetInputs({0});
+  interpreter->SetOutputs({0});
+  interpreter->SetTensorParametersReadWrite(0, kTfLiteFloat32, "", {3},
+                                            TfLiteQuantization());
+  int t = interpreter->inputs()[0];
+  TfLiteTensor* tensor = interpreter->tensor(t);
+  interpreter->ResizeInputTensor(t, {width, height, channels});
+  interpreter->AllocateTensors();
+
+  float* tensor_buffer = tensor->data.f;
+  ASSERT_NE(tensor_buffer, nullptr);
+  for (int i = 0; i < width * height * channels - 1; i++) {
+    tensor_buffer[i] = 1;
+  }
+
+  auto input_vec = absl::make_unique<std::vector<TfLiteTensor>>();
+  input_vec->emplace_back(*tensor);
+
+  // Prepare single calculator graph to and wait for packets.
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(graph_proto);
+  std::vector<Packet> output_packets;
+  tool::AddVectorSink("tensor_out", &graph_config, &output_packets);
+  CalculatorGraph graph(graph_config);
+  MP_ASSERT_OK(graph.StartRun({}));
+
+  // Push the tensor into the graph.
+  MP_ASSERT_OK(graph.AddPacketToInputStream(
+      "tensor_in", Adopt(input_vec.release()).At(Timestamp(0))));
+  // Wait until the calculator done processing.
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+  ASSERT_EQ(1, output_packets.size());
+
+  // Get and process results.
+  const std::vector<TfLiteTensor>& result_vec =
+      output_packets[0].Get<std::vector<TfLiteTensor>>();
+  ASSERT_EQ(1, result_vec.size());
+
+  const TfLiteTensor* result = &result_vec[0];
+  float* result_buffer = result->data.f;
+  ASSERT_NE(result_buffer, nullptr);
+  for (int i = 0; i < width * height * channels - 1; i++) {
+    ASSERT_EQ(3, result_buffer[i]);
+  }
+
+  // Fully close graph at end, otherwise calculator+tensors are destroyed
+  // after calling WaitUntilDone().
+  MP_ASSERT_OK(graph.CloseInputStream("tensor_in"));
+  MP_ASSERT_OK(graph.WaitUntilDone());
+}
+
+// Tests a simple add model that adds an input tensor to itself.
+TEST(TfLiteInferenceCalculatorTest, SmokeTest) {
+  std::string graph_proto = R"(
+    input_stream: "tensor_in"
+    node {
+      calculator: "TfLiteInferenceCalculator"
+      input_stream: "TENSORS:tensor_in"
+      output_stream: "TENSORS:tensor_out"
+      options {
+        [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
+          model_path: "mediapipe/calculators/tflite/testdata/add.bin"
+          $delegate
+        }
+      }
+    }
+  )";
+  DoSmokeTest(
+      /*graph_proto=*/absl::StrReplaceAll(graph_proto, {{"$delegate", ""}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto, {{"$delegate", "delegate { tflite {} }"}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto, {{"$delegate", "delegate { xnnpack {} }"}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto,
+      {{"$delegate", "delegate { xnnpack { num_threads: 10 } }"}}));
+}
+
+TEST(TfLiteInferenceCalculatorTest, SmokeTest_ModelAsInputSidePacket) {
+  std::string graph_proto = R"(
+    input_stream: "tensor_in"
+
+    node {
+      calculator: "ConstantSidePacketCalculator"
+      output_side_packet: "PACKET:model_path"
+      options: {
+        [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+          packet { string_value: "mediapipe/calculators/tflite/testdata/add.bin" }
+        }
+      }
+    }
+
+    node {
+      calculator: "LocalFileContentsCalculator"
+      input_side_packet: "FILE_PATH:model_path"
+      output_side_packet: "CONTENTS:model_blob"
+    }
+
+    node {
+      calculator: "TfLiteModelCalculator"
+      input_side_packet: "MODEL_BLOB:model_blob"
+      output_side_packet: "MODEL:model"
+    }
+
+    node {
+      calculator: "TfLiteInferenceCalculator"
+      input_stream: "TENSORS:tensor_in"
+      output_stream: "TENSORS:tensor_out"
+      input_side_packet: "MODEL:model"
+      options {
+        [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
+          use_gpu: false
+        }
+      }
+    }
+  )";
+  DoSmokeTest(graph_proto);
+}
+
+}  // namespace mediapipe