Snap for 5590969 from 19df2fb19c93dab3c1ffc5cb7a1ab0007384a62d to sdk-release
Change-Id: I938648611c28941c300e849f891efeac2e06127f
diff --git a/tensorflow/lite/kernels/register_ref.cc b/tensorflow/lite/kernels/register_ref.cc
index faa864b..a806b45 100644
--- a/tensorflow/lite/kernels/register_ref.cc
+++ b/tensorflow/lite/kernels/register_ref.cc
@@ -281,9 +281,9 @@
// TODO(andrewharp, ahentz): Move these somewhere more appropriate so that
// custom ops aren't always included by default.
- AddCustom("Mfcc", tflite::ops::custom::Register_MFCC());
- AddCustom("AudioSpectrogram",
- tflite::ops::custom::Register_AUDIO_SPECTROGRAM());
+ // AddCustom("Mfcc", tflite::ops::custom::Register_MFCC());
+ // AddCustom("AudioSpectrogram",
+ // tflite::ops::custom::Register_AUDIO_SPECTROGRAM());
AddCustom("TFLite_Detection_PostProcess",
tflite::ops::custom::Register_DETECTION_POSTPROCESS());
}
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/Android.bp b/tensorflow/lite/testing/nnapi_tflite_zip_tests/Android.bp
new file mode 100644
index 0000000..9af542c
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/Android.bp
@@ -0,0 +1,42 @@
+cc_test {
+ name: "TfliteGeneratedNnapiTest",
+ sdk_version: "current",
+ srcs: [
+ "generated_examples_zip_test.cc",
+ "parse_testdata.cc",
+ "tflite_driver.cc",
+ "split.cc",
+ "message.cc",
+ "tokenize.cc",
+ ],
+ data: [
+ "models.tar",
+ "test_manifest.txt",
+ ],
+ include_dirs: [
+ "external/flatbuffers/include",
+ "external/tensorflow",
+ ],
+ cflags: [
+ "-DPLATFORM_POSIX_ANDROID",
+ "-Wall",
+ "-Werror",
+ "-Wextra",
+ "-Wno-extern-c-compat",
+ "-Wno-sign-compare",
+ "-Wno-unused-parameter",
+ "-Wno-unused-private-field",
+ ],
+ stl: "libc++_static",
+ static_libs: [
+ "libtflite_static",
+ "libgmock_ndk",
+ ],
+ shared_libs: [
+ "liblog",
+ ],
+ test_suites: [
+ "general-tests",
+ ],
+}
+
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/AndroidTest.xml b/tensorflow/lite/testing/nnapi_tflite_zip_tests/AndroidTest.xml
new file mode 100644
index 0000000..2f31146
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/AndroidTest.xml
@@ -0,0 +1,33 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Copyright (C) 2019 The Android Open Source Project
+
+ 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.
+-->
+<configuration description="Configuration for TFLite NNAPI zip Tests">
+ <option name="test-suite-tag" value="general-tests" />
+ <option name="config-descriptor:metadata" key="component" value="neuralnetworks" />
+ <target_preparer class="com.android.compatibility.common.tradefed.targetprep.FilePusher">
+ <option name="cleanup" value="true" />
+ <option name="push" value="TfliteGeneratedNnapiTest->/data/local/tmp/TfliteGeneratedNnapiTest" />
+ <option name="push" value="models.tar->/data/local/tmp/models.tar" />
+ <option name="push" value="test_manifest.txt->/data/local/tmp/test_manifest.txt" />
+ <option name="post-push" value="tar xfo /data/local/tmp/models.tar -C /data/local/tmp/" />
+ </target_preparer>
+ <test class="com.android.tradefed.testtype.GTest" >
+ <option name="native-test-device-path" value="/data/local/tmp" />
+ <option name="module-name" value="TfliteGeneratedNnapiTest" />
+ <option name="runtime-hint" value="10m" />
+ <!-- test-timeout unit is ms, value = 10 min -->
+ <option name="native-test-timeout" value="600000" />
+ </test>
+</configuration>
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/generated_examples_zip_test.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/generated_examples_zip_test.cc
new file mode 100644
index 0000000..82279f9
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/generated_examples_zip_test.cc
@@ -0,0 +1,105 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#include <cstdarg>
+#include <cstdio>
+#include <cstdlib>
+#include <fstream>
+#include <map>
+#include <sstream>
+#include <gtest/gtest.h>
+#include "parse_testdata.h"
+#include "tflite_driver.h"
+#include "util.h"
+
+namespace tflite {
+namespace testing {
+
+namespace {
+bool FLAGS_use_nnapi = true;
+} // namespace
+
+// Get a list of tests from the manifest file.
+std::vector<string> FindAllTests() {
+ const string test_dir = "/data/local/tmp";
+
+ std::vector<string> test_paths;
+ // Read the newline delimited list of entries in the manifest.
+ std::ifstream manifest_fp(test_dir + "/test_manifest.txt");
+ string manifest((std::istreambuf_iterator<char>(manifest_fp)),
+ std::istreambuf_iterator<char>());
+ size_t pos = 0;
+ int added = 0;
+ while (true) {
+ size_t end_pos = manifest.find("\n", pos);
+ if (end_pos == string::npos) break;
+ // ignore disabled tests.
+ if (manifest.substr(pos, 8) != "DISABLED") {
+ string filename = manifest.substr(pos, end_pos - pos);
+ test_paths.push_back(test_dir + "/models/" + filename);
+ }
+ pos = end_pos + 1;
+ added += 1;
+ }
+ return test_paths;
+}
+
+class OpsTest : public ::testing::TestWithParam<string> {};
+
+TEST_P(OpsTest, RunZipTests) {
+ string test_path = GetParam();
+ string tflite_test_case = test_path + "_tests.txt";
+ string tflite_dir = test_path.substr(0, test_path.find_last_of("/"));
+ string test_name = test_path.substr(test_path.find_last_of('/'));
+
+ std::ifstream tflite_stream(tflite_test_case);
+ ASSERT_TRUE(tflite_stream.is_open()) << tflite_test_case;
+ tflite::testing::TfLiteDriver test_driver(FLAGS_use_nnapi);
+ test_driver.SetModelBaseDir(tflite_dir);
+
+ bool result = tflite::testing::ParseAndRunTests(&tflite_stream, &test_driver);
+ string message = test_driver.GetErrorMessage();
+ EXPECT_TRUE(result) << message;
+}
+
+struct ZipPathParamName {
+ template <class ParamType>
+ string operator()(const ::testing::TestParamInfo<ParamType>& info) const {
+ string param_name = info.param;
+ size_t last_slash = param_name.find_last_of("\\/");
+ if (last_slash != string::npos) {
+ param_name = param_name.substr(last_slash);
+ }
+ for (size_t index = 0; index < param_name.size(); ++index) {
+ if (!isalnum(param_name[index]) && param_name[index] != '_')
+ param_name[index] = '_';
+ }
+ return param_name;
+ }
+};
+
+INSTANTIATE_TEST_CASE_P(tests, OpsTest, ::testing::ValuesIn(FindAllTests()),
+ ZipPathParamName());
+
+} // namespace testing
+} // namespace tflite
+
+int main(int argc, char** argv) {
+ ::tflite::LogToStderr();
+ ::testing::InitGoogleTest(&argc, argv);
+ return RUN_ALL_TESTS();
+}
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/join.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/join.h
new file mode 100644
index 0000000..b845f7e
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/join.h
@@ -0,0 +1,77 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_JOIN_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_JOIN_H_
+
+#include <cstdlib>
+#include <iomanip>
+#include <sstream>
+
+#include "tensorflow/lite/string_tflite.h"
+
+namespace tflite {
+namespace testing {
+
+// Join a list of data with default precision separated by delimiter.
+template <typename T>
+string JoinDefault(T* data, size_t len, const string& delimiter) {
+ if (len == 0 || data == nullptr) {
+ return "";
+ }
+ std::stringstream result;
+ result << data[0];
+ for (int i = 1; i < len; i++) {
+ result << delimiter << data[i];
+ }
+ return result.str();
+}
+
+// Join a list of data with fixed precision separated by delimiter.
+template <typename T>
+string Join(T* data, size_t len, const string& delimiter) {
+ if (len == 0 || data == nullptr) {
+ return "";
+ }
+ std::stringstream result;
+ result << std::setprecision(9) << data[0];
+ for (int i = 1; i < len; i++) {
+ result << std::setprecision(9) << delimiter << data[i];
+ }
+ return result.str();
+}
+
+// Join a list of uint8 data separated by a delimiter. Cast data to int before
+// placing it in the string to prevent values from being treated like chars.
+template <>
+inline string Join<uint8_t>(uint8_t* data, size_t len,
+ const string& delimiter) {
+ if (len == 0 || data == nullptr) {
+ return "";
+ }
+ std::stringstream result;
+ result << static_cast<int>(data[0]);
+ for (int i = 1; i < len; i++) {
+ result << delimiter << static_cast<int>(data[i]);
+ }
+ return result.str();
+}
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_JOIN_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/known_failures.txt b/tensorflow/lite/testing/nnapi_tflite_zip_tests/known_failures.txt
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/known_failures.txt
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.cc
new file mode 100644
index 0000000..c43cab7
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.cc
@@ -0,0 +1,99 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#include "message.h"
+
+#include <stack>
+
+#include "tokenize.h"
+
+namespace tflite {
+namespace testing {
+
+// A token processor that builds messages and forward calls to the current
+// message object. Place a new message at the top of the stack when it start
+// and remove it when it is finished.
+class MessageStack : public TokenProcessor {
+ public:
+ // Start a new MessageStack with the given first_node, which will be used to
+ // process freestanding fields and submessages.
+ explicit MessageStack(Message* first_node) {
+ nodes_.push(first_node);
+ valid_ = true;
+ }
+
+ void ConsumeToken(std::string* token) override {
+ if (!valid_) return;
+ Message* current_node = nodes_.top();
+ if (*token == "{") {
+ // This is the beginning of a new message, names after the previous token.
+ if (previous_token_.empty()) {
+ valid_ = false;
+ return;
+ }
+ nodes_.push(current_node ? current_node->AddChild(previous_token_)
+ : nullptr);
+ previous_token_.clear();
+ } else if (*token == "}") {
+ // A message is being completed. There should be no previous token. Note
+ // that the top-level message never closes, so we should always have at
+ // least one entry in the stack.
+ if (nodes_.size() == 1 || !previous_token_.empty()) {
+ valid_ = false;
+ return;
+ }
+ if (current_node) {
+ current_node->Finish();
+ }
+ nodes_.pop();
+ } else if (*token == ":") {
+ // We reached the end of the 'key' portion of a field. Store the token
+ // until we have the 'value' portion.
+ if (previous_token_.empty()) {
+ valid_ = false;
+ return;
+ }
+ } else {
+ if (previous_token_.empty()) {
+ previous_token_.swap(*token);
+ } else {
+ // This is the 'value' portion of a field. The previous token is the
+ // 'key'.
+ if (current_node) {
+ current_node->SetField(previous_token_, *token);
+ }
+ previous_token_.clear();
+ }
+ }
+ }
+
+ bool valid() const { return valid_; }
+
+ private:
+ std::stack<Message*> nodes_;
+ std::string previous_token_;
+ bool valid_;
+};
+
+bool Message::Read(std::istream* input, Message* message) {
+ MessageStack stack(message);
+ Tokenize(input, &stack);
+ return stack.valid();
+}
+
+} // namespace testing
+} // namespace tflite
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.h
new file mode 100644
index 0000000..5d3a489
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/message.h
@@ -0,0 +1,85 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_MESSAGE_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_MESSAGE_H_
+
+#include <memory>
+#include <string>
+#include <vector>
+
+namespace tflite {
+namespace testing {
+
+// A Message is a textual protobuf-like structure that looks like:
+// tag {
+// f : "values"
+// child {
+// a : 1
+// }
+// }
+// This class provides the framework for processing message but does not
+// associate any particular behavior to fields and submessage. In order
+// to properly parse a stream this class must be derived.
+class Message {
+ public:
+ // Reads a stream, tokenizes it and create a new message under the given
+ // top-level message. Returns true if the parsing succeeded.
+ static bool Read(std::istream* input, Message* message);
+
+ Message() {}
+ virtual ~Message() {}
+
+ // Called when a new field is found. For example, when:
+ // f : "values"
+ // is found, it triggers:
+ // SetField("f", "values");
+ virtual void SetField(const std::string& name, const std::string& value) {}
+
+ // Called when a submessage is started. For example, when:
+ // child {
+ // is found, it triggers
+ // AddChild("child");
+ // If nullptr is returned, the contents of the submessage will be ignored.
+ // Otherwise, the returned Message will be used to handle new fields and new
+ // submessages. The caller should not take ownership of the returned pointer.
+ virtual Message* AddChild(const std::string& name) { return nullptr; }
+
+ // Called when a submessage is completed, that is, whenever a '}' is found.
+ virtual void Finish() {}
+
+ protected:
+ // Takes ownership of the given pointer. Subclasses can use this method if
+ // they don't want to implement their own ownership semantics.
+ Message* Store(Message* n) {
+ children_.emplace_back(n);
+ return n;
+ }
+
+ // Returns a list of all owned submessages.
+ const std::vector<std::unique_ptr<Message>>& Children() const {
+ return children_;
+ }
+
+ private:
+ std::vector<std::unique_ptr<Message>> children_;
+};
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_MESSAGE_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/models.tar b/tensorflow/lite/testing/nnapi_tflite_zip_tests/models.tar
new file mode 100644
index 0000000..a172f1f
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/models.tar
Binary files differ
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/not_supported.txt b/tensorflow/lite/testing/nnapi_tflite_zip_tests/not_supported.txt
new file mode 100644
index 0000000..96cca6a
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/not_supported.txt
@@ -0,0 +1,536 @@
+abs/abs_input_shape=[]
+abs/abs_input_shape=[1]
+abs/abs_input_shape=[2,3]
+abs/abs_input_shape=[1,1,1,1]
+abs/abs_input_shape=[1,3,4,3]
+abs/abs_input_shape=[3,15,14,3]
+abs/abs_input_shape=[3,1,2,4,6]
+abs/abs_input_shape=[2,2,3,4,5,6]
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[5,5],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[5,5],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[5,5],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[5,5],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[10],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[10],is_arg_max=True,output_type=tf.int64
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[10],is_arg_max=True,output_type=tf.int32
+arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[10],is_arg_max=True,output_type=tf.int64
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=True,constant_crops=True,crops=[[0,0],[0,0]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=True,constant_crops=False,crops=[[0,0],[0,0]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=False,constant_crops=True,crops=[[0,0],[0,0]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=False,constant_crops=False,crops=[[0,0],[0,0]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=True,constant_crops=True,crops=[[1,1],[1,1]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=True,constant_crops=False,crops=[[1,1],[1,1]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=False,constant_crops=True,crops=[[1,1],[1,1]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=False,constant_crops=False,crops=[[1,1],[1,1]],dtype=tf.float32,input_shape=[12,3,3,1]
+batch_to_space_nd/batch_to_space_nd_block_shape=[1,4],constant_block_shape=True,constant_crops=True,crops=[[0,0],[0,0]],dtype=tf.int64,input_shape=[12,3,3,1]
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+mean/mean_axis=[],const_axis=False,input_dtype=tf.float32,input_shape=[],keepdims=False
+mean/mean_axis=[],const_axis=False,input_dtype=tf.float32,input_shape=[1,8,8,3],keepdims=True
+mean/mean_axis=[],const_axis=False,input_dtype=tf.float32,input_shape=[1,8,8,3],keepdims=False
+mean/mean_axis=[],const_axis=False,input_dtype=tf.float32,input_shape=[3,2,4],keepdims=True
+mean/mean_axis=[],const_axis=False,input_dtype=tf.float32,input_shape=[3,2,4],keepdims=False
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[],keepdims=True
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[],keepdims=False
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[1,8,8,3],keepdims=True
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[1,8,8,3],keepdims=False
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[3,2,4],keepdims=True
+mean/mean_axis=None,const_axis=True,input_dtype=tf.float32,input_shape=[3,2,4],keepdims=False
\ No newline at end of file
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.cc
new file mode 100644
index 0000000..a525e11
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.cc
@@ -0,0 +1,366 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+// Parses tflite example input data.
+// Format is ASCII
+// TODO(aselle): Switch to protobuf, but the android team requested a simple
+// ASCII file.
+#include "parse_testdata.h"
+
+#include <cinttypes>
+#include <cmath>
+#include <cstdint>
+#include <cstdio>
+#include <fstream>
+#include <iostream>
+#include <streambuf>
+
+#include "tensorflow/lite/error_reporter.h"
+#include "message.h"
+#include "split.h"
+
+namespace tflite {
+namespace testing {
+namespace {
+
+// Fatal error if parse error occurs
+#define PARSE_CHECK_EQ(filename, current_line, x, y) \
+ if ((x) != (y)) { \
+ fprintf(stderr, "Parse Error @ %s:%d\n File %s\n Line %d, %s != %s\n", \
+ __FILE__, __LINE__, filename, current_line + 1, #x, #y); \
+ return kTfLiteError; \
+ }
+
+// Breakup a "," delimited line into a std::vector<std::string>.
+// This is extremely inefficient, and just used for testing code.
+// TODO(aselle): replace with absl when we use it.
+std::vector<std::string> ParseLine(const std::string& line) {
+ size_t pos = 0;
+ std::vector<std::string> elements;
+ while (true) {
+ size_t end = line.find(',', pos);
+ if (end == std::string::npos) {
+ elements.push_back(line.substr(pos));
+ break;
+ } else {
+ elements.push_back(line.substr(pos, end - pos));
+ }
+ pos = end + 1;
+ }
+ return elements;
+}
+
+} // namespace
+
+// Given a `filename`, produce a vector of Examples corresopnding
+// to test cases that can be applied to a tflite model.
+TfLiteStatus ParseExamples(const char* filename,
+ std::vector<Example>* examples) {
+ std::ifstream fp(filename);
+ if (!fp.good()) {
+ fprintf(stderr, "Could not read '%s'\n", filename);
+ return kTfLiteError;
+ }
+ std::string str((std::istreambuf_iterator<char>(fp)),
+ std::istreambuf_iterator<char>());
+ size_t pos = 0;
+
+ // \n and , delimit parse a file.
+ std::vector<std::vector<std::string>> csv;
+ while (true) {
+ size_t end = str.find('\n', pos);
+
+ if (end == std::string::npos) {
+ csv.emplace_back(ParseLine(str.substr(pos)));
+ break;
+ }
+ csv.emplace_back(ParseLine(str.substr(pos, end - pos)));
+ pos = end + 1;
+ }
+
+ int current_line = 0;
+ PARSE_CHECK_EQ(filename, current_line, csv[0][0], "test_cases");
+ int example_count = std::stoi(csv[0][1]);
+ current_line++;
+
+ auto parse_tensor = [&filename, ¤t_line,
+ &csv](FloatTensor* tensor_ptr) {
+ PARSE_CHECK_EQ(filename, current_line, csv[current_line][0], "dtype");
+ current_line++;
+ // parse shape
+ PARSE_CHECK_EQ(filename, current_line, csv[current_line][0], "shape");
+ size_t elements = 1;
+ FloatTensor& tensor = *tensor_ptr;
+
+ for (size_t i = 1; i < csv[current_line].size(); i++) {
+ const auto& shape_part_to_parse = csv[current_line][i];
+ if (shape_part_to_parse.empty()) {
+ // Case of a 0-dimensional shape
+ break;
+ }
+ int shape_part = std::stoi(shape_part_to_parse);
+ elements *= shape_part;
+ tensor.shape.push_back(shape_part);
+ }
+ current_line++;
+ // parse data
+ PARSE_CHECK_EQ(filename, current_line, csv[current_line].size() - 1,
+ elements);
+ for (size_t i = 1; i < csv[current_line].size(); i++) {
+ tensor.flat_data.push_back(std::stof(csv[current_line][i]));
+ }
+ current_line++;
+
+ return kTfLiteOk;
+ };
+
+ for (int example_idx = 0; example_idx < example_count; example_idx++) {
+ Example example;
+ PARSE_CHECK_EQ(filename, current_line, csv[current_line][0], "inputs");
+ int inputs = std::stoi(csv[current_line][1]);
+ current_line++;
+ // parse dtype
+ for (int input_index = 0; input_index < inputs; input_index++) {
+ example.inputs.push_back(FloatTensor());
+ TF_LITE_ENSURE_STATUS(parse_tensor(&example.inputs.back()));
+ }
+
+ PARSE_CHECK_EQ(filename, current_line, csv[current_line][0], "outputs");
+ int outputs = std::stoi(csv[current_line][1]);
+ current_line++;
+ for (int input_index = 0; input_index < outputs; input_index++) {
+ example.outputs.push_back(FloatTensor());
+ TF_LITE_ENSURE_STATUS(parse_tensor(&example.outputs.back()));
+ }
+ examples->emplace_back(example);
+ }
+ return kTfLiteOk;
+}
+
+TfLiteStatus FeedExample(tflite::Interpreter* interpreter,
+ const Example& example) {
+ // Resize inputs to match example & allocate.
+ for (size_t i = 0; i < interpreter->inputs().size(); i++) {
+ int input_index = interpreter->inputs()[i];
+
+ TF_LITE_ENSURE_STATUS(
+ interpreter->ResizeInputTensor(input_index, example.inputs[i].shape));
+ }
+ TF_LITE_ENSURE_STATUS(interpreter->AllocateTensors());
+ // Copy data into tensors.
+ for (size_t i = 0; i < interpreter->inputs().size(); i++) {
+ int input_index = interpreter->inputs()[i];
+ if (float* data = interpreter->typed_tensor<float>(input_index)) {
+ for (size_t idx = 0; idx < example.inputs[i].flat_data.size(); idx++) {
+ data[idx] = example.inputs[i].flat_data[idx];
+ }
+ } else if (int32_t* data =
+ interpreter->typed_tensor<int32_t>(input_index)) {
+ for (size_t idx = 0; idx < example.inputs[i].flat_data.size(); idx++) {
+ data[idx] = example.inputs[i].flat_data[idx];
+ }
+ } else if (int64_t* data =
+ interpreter->typed_tensor<int64_t>(input_index)) {
+ for (size_t idx = 0; idx < example.inputs[i].flat_data.size(); idx++) {
+ data[idx] = example.inputs[i].flat_data[idx];
+ }
+ } else {
+ fprintf(stderr, "input[%zu] was not float or int data\n", i);
+ return kTfLiteError;
+ }
+ }
+ return kTfLiteOk;
+}
+
+TfLiteStatus CheckOutputs(tflite::Interpreter* interpreter,
+ const Example& example) {
+ constexpr double kRelativeThreshold = 1e-2f;
+ constexpr double kAbsoluteThreshold = 1e-4f;
+
+ ErrorReporter* context = DefaultErrorReporter();
+ int model_outputs = interpreter->outputs().size();
+ TF_LITE_ENSURE_EQ(context, model_outputs, example.outputs.size());
+ for (size_t i = 0; i < interpreter->outputs().size(); i++) {
+ bool tensors_differ = false;
+ int output_index = interpreter->outputs()[i];
+ if (const float* data = interpreter->typed_tensor<float>(output_index)) {
+ for (size_t idx = 0; idx < example.outputs[i].flat_data.size(); idx++) {
+ float computed = data[idx];
+ float reference = example.outputs[0].flat_data[idx];
+ float diff = std::abs(computed - reference);
+ // For very small numbers, try absolute error, otherwise go with
+ // relative.
+ bool local_tensors_differ =
+ std::abs(reference) < kRelativeThreshold
+ ? diff > kAbsoluteThreshold
+ : diff > kRelativeThreshold * std::abs(reference);
+ if (local_tensors_differ) {
+ fprintf(stdout, "output[%zu][%zu] did not match %f vs reference %f\n",
+ i, idx, data[idx], reference);
+ tensors_differ = local_tensors_differ;
+ }
+ }
+ } else if (const int32_t* data =
+ interpreter->typed_tensor<int32_t>(output_index)) {
+ for (size_t idx = 0; idx < example.outputs[i].flat_data.size(); idx++) {
+ int32_t computed = data[idx];
+ int32_t reference = example.outputs[0].flat_data[idx];
+ if (std::abs(computed - reference) > 0) {
+ fprintf(stderr, "output[%zu][%zu] did not match %d vs reference %d\n",
+ i, idx, computed, reference);
+ tensors_differ = true;
+ }
+ }
+ } else if (const int64_t* data =
+ interpreter->typed_tensor<int64_t>(output_index)) {
+ for (size_t idx = 0; idx < example.outputs[i].flat_data.size(); idx++) {
+ int64_t computed = data[idx];
+ int64_t reference = example.outputs[0].flat_data[idx];
+ if (std::abs(computed - reference) > 0) {
+ fprintf(stderr,
+ "output[%zu][%zu] did not match %" PRId64
+ " vs reference %" PRId64 "\n",
+ i, idx, computed, reference);
+ tensors_differ = true;
+ }
+ }
+ } else {
+ fprintf(stderr, "output[%zu] was not float or int data\n", i);
+ return kTfLiteError;
+ }
+ fprintf(stderr, "\n");
+ if (tensors_differ) return kTfLiteError;
+ }
+ return kTfLiteOk;
+}
+
+// Process an 'invoke' message, triggering execution of the test runner, as
+// well as verification of outputs. An 'invoke' message looks like:
+// invoke {
+// id: xyz
+// input: 1,2,1,1,1,2,3,4
+// output: 4,5,6
+// }
+class Invoke : public Message {
+ public:
+ explicit Invoke(TestRunner* test_runner) : test_runner_(test_runner) {
+ expected_inputs_ = test_runner->GetInputs();
+ expected_outputs_ = test_runner->GetOutputs();
+ }
+
+ void SetField(const std::string& name, const std::string& value) override {
+ if (name == "id") {
+ test_runner_->SetInvocationId(value);
+ } else if (name == "input") {
+ if (expected_inputs_.empty()) {
+ return test_runner_->Invalidate("Too many inputs");
+ }
+ test_runner_->SetInput(*expected_inputs_.begin(), value);
+ expected_inputs_.erase(expected_inputs_.begin());
+ } else if (name == "output") {
+ if (expected_outputs_.empty()) {
+ return test_runner_->Invalidate("Too many outputs");
+ }
+ test_runner_->SetExpectation(*expected_outputs_.begin(), value);
+ expected_outputs_.erase(expected_outputs_.begin());
+ }
+ }
+ void Finish() override {
+ test_runner_->Invoke();
+ test_runner_->CheckResults();
+ }
+
+ private:
+ std::vector<int> expected_inputs_;
+ std::vector<int> expected_outputs_;
+
+ TestRunner* test_runner_;
+};
+
+// Process an 'reshape' message, triggering resizing of the input tensors via
+// the test runner. A 'reshape' message looks like:
+// reshape {
+// input: 1,2,1,1,1,2,3,4
+// }
+class Reshape : public Message {
+ public:
+ explicit Reshape(TestRunner* test_runner) : test_runner_(test_runner) {
+ expected_inputs_ = test_runner->GetInputs();
+ }
+
+ void SetField(const std::string& name, const std::string& value) override {
+ if (name == "input") {
+ if (expected_inputs_.empty()) {
+ return test_runner_->Invalidate("Too many inputs to reshape");
+ }
+ test_runner_->ReshapeTensor(*expected_inputs_.begin(), value);
+ expected_inputs_.erase(expected_inputs_.begin());
+ }
+ }
+
+ private:
+ std::vector<int> expected_inputs_;
+ TestRunner* test_runner_;
+};
+
+// This is the top-level message in a test file.
+class TestData : public Message {
+ public:
+ explicit TestData(TestRunner* test_runner)
+ : test_runner_(test_runner), num_invocations_(0), max_invocations_(-1) {}
+ void SetMaxInvocations(int max) { max_invocations_ = max; }
+ void SetField(const std::string& name, const std::string& value) override {
+ if (name == "load_model") {
+ test_runner_->LoadModel(value);
+ } else if (name == "init_state") {
+ test_runner_->AllocateTensors();
+ for (int id : Split<int>(value, ",")) {
+ test_runner_->ResetTensor(id);
+ }
+ }
+ }
+ Message* AddChild(const std::string& s) override {
+ if (s == "invoke") {
+ test_runner_->AllocateTensors();
+ if (max_invocations_ == -1 || num_invocations_ < max_invocations_) {
+ ++num_invocations_;
+ return Store(new Invoke(test_runner_));
+ } else {
+ return nullptr;
+ }
+ } else if (s == "reshape") {
+ return Store(new Reshape(test_runner_));
+ }
+ return nullptr;
+ }
+
+ private:
+ TestRunner* test_runner_;
+ int num_invocations_;
+ int max_invocations_;
+};
+
+bool ParseAndRunTests(std::istream* input, TestRunner* test_runner,
+ int max_invocations) {
+ TestData test_data(test_runner);
+ test_data.SetMaxInvocations(max_invocations);
+ Message::Read(input, &test_data);
+ return test_runner->IsValid() && test_runner->GetOverallSuccess();
+}
+
+} // namespace testing
+} // namespace tflite
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.h
new file mode 100644
index 0000000..0220a09
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/parse_testdata.h
@@ -0,0 +1,78 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_PARSE_TESTDATA_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_PARSE_TESTDATA_H_
+
+#include <vector>
+#include "tensorflow/lite/interpreter.h"
+#include "test_runner.h"
+
+namespace tflite {
+namespace testing {
+
+// Shape and data for a float tensor
+struct FloatTensor {
+ std::vector<int> shape;
+ std::vector<float> flat_data;
+};
+
+// A prescribed input, output example
+struct Example {
+ std::vector<FloatTensor> inputs;
+ std::vector<FloatTensor> outputs;
+};
+
+// Parses an example input and output file (used for unit tests)
+TfLiteStatus ParseExamples(const char* filename,
+ std::vector<Example>* examples);
+
+// Inputs Tensors into a TensorFlow lite interpreter. Note, this will run
+// interpreter.AllocateTensors();
+TfLiteStatus FeedExample(tflite::Interpreter* interpreter, const Example&);
+
+// Check outputs against (already) evaluated result.
+TfLiteStatus CheckOutputs(tflite::Interpreter* interpreter, const Example&);
+
+// Parses a test description and feeds the given test runner with data.
+// The input format is similar to an ASCII proto:
+// // Loads model 'add.bin' from the TestRunner's model directory.
+// load_model: "add.bin"
+// // Changes the shape of inputs, provided in the same order they appear
+// // in the model.
+// reshape {
+// input: "1,224,224,3"
+// input: "1,3,4,1"
+// }
+// // Fills the given persistent tensors with zeros.
+// init_state: 0,1,2,3
+// // Invokes the interpreter with the given input and checks that it
+// // produces the expected output. Inputs and outputs should be specified in
+// // the order they appear in the model.
+// invoke {
+// input: "1,2,3,4,56"
+// input: "0.1,0.2,0.3,4.3,56.4"
+// output: "12,3,4,545,3"
+// output: "0.01,0.02"
+// }
+bool ParseAndRunTests(std::istream* input, TestRunner* test_runner,
+ int max_invocations = -1);
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_PARSE_TESTDATA_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.cc
new file mode 100644
index 0000000..eb1b15d
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.cc
@@ -0,0 +1,45 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#include "split.h"
+
+namespace tflite {
+namespace testing {
+
+std::vector<std::pair<size_t, size_t>> SplitToPos(const string& s,
+ const string& delimiter) {
+ std::vector<std::pair<size_t, size_t>> fields;
+ if (delimiter.length() == 0) {
+ fields.emplace_back(0, s.length());
+ return fields;
+ }
+ size_t pos = 0;
+ size_t start = 0;
+ while ((pos = s.find(delimiter, start)) != string::npos) {
+ if (pos != start) {
+ fields.emplace_back(start, pos);
+ }
+ start = pos + delimiter.length();
+ }
+ if (start != s.length()) {
+ fields.emplace_back(start, s.length());
+ }
+ return fields;
+}
+
+} // namespace testing
+} // namespace tflite
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.h
new file mode 100644
index 0000000..cdb5381
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/split.h
@@ -0,0 +1,99 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_SPLIT_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_SPLIT_H_
+
+#include <cstdlib>
+#include <string>
+#include <utility>
+#include <vector>
+#include "tensorflow/lite/string_tflite.h"
+
+namespace tflite {
+namespace testing {
+
+// Splits a string based on the given delimiter string. Each pair in the
+// returned vector has the start and past-the-end positions for each of the
+// parts of the original string. Empty fields are not represented in the
+// output.
+std::vector<std::pair<size_t, size_t>> SplitToPos(const string& s,
+ const string& delimiter);
+
+// Splits the given string and converts each part to the given T.
+template <typename T>
+std::vector<T> Split(const string& s, const string& delimiter);
+
+template <>
+inline std::vector<string> Split(const string& s, const string& delimiter) {
+ std::vector<string> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(s.substr(p.first, p.second - p.first));
+ }
+ return fields;
+}
+
+template <>
+inline std::vector<int> Split(const string& s, const string& delimiter) {
+ std::vector<int> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(strtol(s.data() + p.first, nullptr, 10));
+ }
+ return fields;
+}
+
+template <>
+inline std::vector<int64_t> Split(const string& s, const string& delimiter) {
+ std::vector<int64_t> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(strtoll(s.data() + p.first, nullptr, 10));
+ }
+ return fields;
+}
+
+template <>
+inline std::vector<float> Split(const string& s, const string& delimiter) {
+ std::vector<float> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(strtod(s.data() + p.first, nullptr));
+ }
+ return fields;
+}
+
+template <>
+inline std::vector<uint8_t> Split(const string& s, const string& delimiter) {
+ std::vector<uint8_t> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(strtol(s.data() + p.first, nullptr, 10));
+ }
+ return fields;
+}
+
+template <>
+inline std::vector<bool> Split(const string& s, const string& delimiter) {
+ std::vector<bool> fields;
+ for (const auto& p : SplitToPos(s, delimiter)) {
+ fields.push_back(
+ static_cast<bool>(strtol(s.data() + p.first, nullptr, 10)));
+ }
+ return fields;
+}
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_SPLIT_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_manifest.txt b/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_manifest.txt
new file mode 100644
index 0000000..ff0d85d
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_manifest.txt
@@ -0,0 +1,2105 @@
+add/add_activation=True,dtype=tf.float32,input_shape_1=[1,3,4,3],input_shape_2=[1,3,4,3]
+DISABLED_add/add_activation=True,dtype=tf.int32,input_shape_1=[1,3,4,3],input_shape_2=[1,3,4,3]
+add/add_activation=False,dtype=tf.float32,input_shape_1=[5],input_shape_2=[5]
+add/add_activation=True,dtype=tf.float32,input_shape_1=[5],input_shape_2=[5]
+add/add_activation=True,dtype=tf.float32,input_shape_1=[1,3,4,3],input_shape_2=[3]
+add/add_activation=False,dtype=tf.float32,input_shape_1=[1,3,4,3],input_shape_2=[3]
+DISABLED_add/add_activation=True,dtype=tf.int32,input_shape_1=[1,3,4,3],input_shape_2=[3]
+DISABLED_add/add_activation=False,dtype=tf.int32,input_shape_1=[1,3,4,3],input_shape_2=[3]
+DISABLED_add/add_activation=True,dtype=tf.int64,input_shape_1=[1,3,4,3],input_shape_2=[3]
+DISABLED_add/add_activation=False,dtype=tf.int64,input_shape_1=[1,3,4,3],input_shape_2=[3]
+add/add_activation=True,dtype=tf.float32,input_shape_1=[3],input_shape_2=[1,3,4,3]
+add/add_activation=False,dtype=tf.float32,input_shape_1=[3],input_shape_2=[1,3,4,3]
+DISABLED_add/add_activation=True,dtype=tf.int32,input_shape_1=[3],input_shape_2=[1,3,4,3]
+DISABLED_add/add_activation=False,dtype=tf.int32,input_shape_1=[3],input_shape_2=[1,3,4,3]
+DISABLED_add/add_activation=False,dtype=tf.float32,input_shape_1=[],input_shape_2=[]
+DISABLED_add/add_activation=False,dtype=tf.float32,input_shape_1=[0],input_shape_2=[1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[1,1,1,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[1,1,2,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[1,10,11,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides=[1,1,1,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides=[1,1,2,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides=[1,10,11,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides=[1,1,1,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides=[1,1,2,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides=[1,10,11,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='VALID',strides=[1,1,1,1]
+avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='VALID',strides=[1,1,2,1]
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+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=0.3,depth_radius=None,input_shape=[3,15,14,3]
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+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=0.3,depth_radius=1,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=0.3,depth_radius=3,input_shape=[3,15,14,3]
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+local_response_norm/local_response_norm_alpha=-3,beta=None,bias=-0.1,depth_radius=None,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=None,bias=-0.1,depth_radius=0,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=None,bias=-0.1,depth_radius=1,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=None,bias=-0.1,depth_radius=3,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=None,bias=-0.1,depth_radius=5,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=0.25,bias=-0.1,depth_radius=None,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=0.25,bias=-0.1,depth_radius=0,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=0.25,bias=-0.1,depth_radius=1,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=0.25,bias=-0.1,depth_radius=3,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=0.25,bias=-0.1,depth_radius=5,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=-0.1,depth_radius=None,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=-0.1,depth_radius=0,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=-0.1,depth_radius=1,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=-0.1,depth_radius=3,input_shape=[3,15,14,3]
+local_response_norm/local_response_norm_alpha=-3,beta=2,bias=-0.1,depth_radius=5,input_shape=[3,15,14,3]
+DISABLED_relu/relu_input_shape=[]
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+relu/relu_input_shape=[1,1,1,1]
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+relu/relu_input_shape=[3,15,14,3]
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+DISABLED_relu/relu_input_shape=[2,2,3,4,5,6]
+DISABLED_relu1/relu1_input_shape=[]
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+relu1/relu1_input_shape=[1,3,4,3]
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+DISABLED_relu1/relu1_input_shape=[2,2,3,4,5,6]
+DISABLED_relu6/relu6_input_shape=[]
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+DISABLED_relu6/relu6_input_shape=[2,2,3,4,5,6]
+sub/sub_activation=True,dtype=tf.float32,input_shape_1=[1,3,4,3],input_shape_2=[1,3,4,3]
+DISABLED_sub/sub_activation=True,dtype=tf.int32,input_shape_1=[1,3,4,3],input_shape_2=[1,3,4,3]
+sub/sub_activation=False,dtype=tf.float32,input_shape_1=[5],input_shape_2=[5]
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+DISABLED_sub/sub_activation=False,dtype=tf.int64,input_shape_1=[1,3,4,3],input_shape_2=[3]
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+DISABLED_sub/sub_activation=False,dtype=tf.int32,input_shape_1=[3],input_shape_2=[1,3,4,3]
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+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=1,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=None,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=None,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=None,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=2,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=3,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=None,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=1,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_strided_slice/strided_slice_begin=[0,-1],begin_mask=2,constant_indices=False,dtype=tf.float32,end=[2,-3],end_mask=2,index_type=tf.int32,input_shape=[2,3],shrink_axis_mask=-1,strides=[1,-1]
+DISABLED_transpose/transpose_constant_perm=True,dtype=tf.int32,input_shape=[2,2,3],perm=[0,1,2]
+DISABLED_transpose/transpose_constant_perm=True,dtype=tf.int32,input_shape=[2,2,3],perm=[0,2,1]
+DISABLED_transpose/transpose_constant_perm=True,dtype=tf.int64,input_shape=[2,2,3],perm=[0,1,2]
+DISABLED_transpose/transpose_constant_perm=True,dtype=tf.int64,input_shape=[2,2,3],perm=[0,2,1]
+transpose/transpose_constant_perm=True,dtype=tf.float32,input_shape=[2,2,3],perm=[0,1,2]
+transpose/transpose_constant_perm=True,dtype=tf.float32,input_shape=[2,2,3],perm=[0,2,1]
+transpose/transpose_constant_perm=True,dtype=tf.float32,input_shape=[1,2,3,4],perm=[0,1,2,3]
+transpose/transpose_constant_perm=True,dtype=tf.float32,input_shape=[1,2,3,4],perm=[3,0,1,2]
+DISABLED_transpose/transpose_constant_perm=True,dtype=tf.float32,input_shape=[1,2,3,4,5],perm=[4,3,2,1,0]
+lstm/lstm_dtype=tf.float32,input_vec_size=3,num_batchs=1,num_cells=4,split_tflite_lstm_inputs=False,time_step_size=1
\ No newline at end of file
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_runner.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_runner.h
new file mode 100644
index 0000000..1a8f765
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/test_runner.h
@@ -0,0 +1,133 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_TEST_RUNNER_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_TEST_RUNNER_H_
+
+#include <iostream>
+#include <memory>
+#include <string>
+#include <vector>
+#include "tensorflow/lite/string_tflite.h"
+
+namespace tflite {
+namespace testing {
+
+// This is the base class for processing test data. Each one of the virtual
+// methods must be implemented to forward the data to the appropriate executor
+// (e.g. TF Lite's interpreter, or the NNAPI).
+class TestRunner {
+ public:
+ TestRunner() {}
+ virtual ~TestRunner() {}
+
+ // Load the given model, as a path relative to SetModelBaseDir().
+ virtual void LoadModel(const string& bin_file_path) = 0;
+
+ // Return the list of input tensors in the loaded model.
+ virtual const std::vector<int>& GetInputs() = 0;
+
+ // Return the list of output tensors in the loaded model.
+ virtual const std::vector<int>& GetOutputs() = 0;
+
+ // Prepare for a run by resize the given tensor. The given 'id' is
+ // guaranteed to be one of the ids returned by GetInputs().
+ virtual void ReshapeTensor(int id, const string& csv_values) = 0;
+
+ // Reserve memory for all tensors.
+ virtual void AllocateTensors() = 0;
+
+ // Set the given tensor to some initial state, usually zero. This is
+ // used to reset persistent buffers in a model.
+ virtual void ResetTensor(int id) = 0;
+
+ // Define the contents of the given input tensor. The given 'id' is
+ // guaranteed to be one of the ids returned by GetInputs().
+ virtual void SetInput(int id, const string& values_as_string) = 0;
+
+ // Define what should be expected for an output tensor after Invoke() runs.
+ // The given 'id' is guaranteed to be one of the ids returned by
+ // GetOutputs().
+ virtual void SetExpectation(int id, const string& values_as_string) = 0;
+
+ // Run the model.
+ virtual void Invoke() = 0;
+
+ // Verify that the contents of all outputs conform to the existing
+ // expectations. Return true if there are no expectations or they are all
+ // satisfied.
+ virtual bool CheckResults() = 0;
+
+ // Read contents of tensor into csv format.
+ // The given 'id' is guaranteed to be one of the ids returned by GetOutputs().
+ virtual string ReadOutput(int id) = 0;
+
+ // Set the base path for loading models.
+ void SetModelBaseDir(const string& path) {
+ model_base_dir_ = path;
+ if (path[path.length() - 1] != '/') {
+ model_base_dir_ += "/";
+ }
+ }
+
+ // Return the full path of a model.
+ string GetFullPath(const string& path) { return model_base_dir_ + path; }
+
+ // Give an id to the next invocation to make error reporting more meaningful.
+ void SetInvocationId(const string& id) { invocation_id_ = id; }
+ const string& GetInvocationId() const { return invocation_id_; }
+
+ // Invalidate the test runner, preventing it from executing any further.
+ void Invalidate(const string& error_message) {
+ std::cerr << error_message << std::endl;
+ error_message_ = error_message;
+ }
+ bool IsValid() const { return error_message_.empty(); }
+ const string& GetErrorMessage() const { return error_message_; }
+
+ // Handle the overall success of this test runner. This will be true if all
+ // invocations were successful.
+ void SetOverallSuccess(bool value) { overall_success_ = value; }
+ bool GetOverallSuccess() const { return overall_success_; }
+
+ protected:
+ // A helper to check of the given number of values is consistent with the
+ // number of bytes in a tensor of type T. When incompatibles sizes are found,
+ // the test runner is invalidated and false is returned.
+ template <typename T>
+ bool CheckSizes(size_t tensor_bytes, size_t num_values) {
+ size_t num_tensor_elements = tensor_bytes / sizeof(T);
+ if (num_tensor_elements != num_values) {
+ Invalidate("Expected '" + std::to_string(num_tensor_elements) +
+ "' elements for a tensor, but only got '" +
+ std::to_string(num_values) + "'");
+ return false;
+ }
+ return true;
+ }
+
+ private:
+ string model_base_dir_;
+ string invocation_id_;
+ bool overall_success_ = true;
+
+ string error_message_;
+};
+
+} // namespace testing
+} // namespace tflite
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_TEST_RUNNER_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.cc
new file mode 100644
index 0000000..86f55cf
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.cc
@@ -0,0 +1,412 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#include "tflite_driver.h"
+
+#include <iostream>
+
+#include "tensorflow/lite/builtin_op_data.h"
+#include "tensorflow/lite/delegates/nnapi/nnapi_delegate.h"
+#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/kernels/register_ref.h"
+#include "tensorflow/lite/string_util.h"
+#include "join.h"
+#include "split.h"
+
+namespace tflite {
+namespace testing {
+
+namespace {
+
+// Returns the value in the given position in a tensor.
+template <typename T>
+T Value(const TfLitePtrUnion& data, int index);
+template <>
+float Value(const TfLitePtrUnion& data, int index) {
+ return data.f[index];
+}
+template <>
+int32_t Value(const TfLitePtrUnion& data, int index) {
+ return data.i32[index];
+}
+template <>
+int64_t Value(const TfLitePtrUnion& data, int index) {
+ return data.i64[index];
+}
+template <>
+uint8_t Value(const TfLitePtrUnion& data, int index) {
+ return data.uint8[index];
+}
+template <>
+bool Value(const TfLitePtrUnion& data, int index) {
+ return data.b[index];
+}
+
+template <typename T>
+void SetTensorData(const std::vector<T>& values, TfLitePtrUnion* data) {
+ T* input_ptr = reinterpret_cast<T*>(data->raw);
+ for (const T& v : values) {
+ *input_ptr = v;
+ ++input_ptr;
+ }
+}
+
+} // namespace
+
+class TfLiteDriver::Expectation {
+ public:
+ Expectation() {
+ data_.raw = nullptr;
+ num_elements_ = 0;
+ }
+ ~Expectation() { delete[] data_.raw; }
+ template <typename T>
+ void SetData(const string& csv_values) {
+ const auto& values = testing::Split<T>(csv_values, ",");
+ num_elements_ = values.size();
+ data_.raw = new char[num_elements_ * sizeof(T)];
+ SetTensorData(values, &data_);
+ }
+
+ bool Check(bool verbose, const TfLiteTensor& tensor);
+
+ private:
+ template <typename T>
+ bool TypedCheck(bool verbose, const TfLiteTensor& tensor) {
+ // TODO(ahentz): must find a way to configure the tolerance.
+ constexpr double kRelativeThreshold = 1e-2f;
+ constexpr double kAbsoluteThreshold = 1e-4f;
+
+ size_t tensor_size = tensor.bytes / sizeof(T);
+
+ if (tensor_size != num_elements_) {
+ std::cerr << "Expected a tensor with " << num_elements_
+ << " elements, got " << tensor_size << std::endl;
+ std::cerr << "while checking tensor " << tensor.name << std::endl;
+ return false;
+ }
+
+ bool good_output = true;
+ for (int i = 0; i < tensor_size; ++i) {
+ float computed = Value<T>(tensor.data, i);
+ float reference = Value<T>(data_, i);
+ float diff = std::abs(computed - reference);
+ bool error_is_large = false;
+ // For very small numbers, try absolute error, otherwise go with
+ // relative.
+ if (std::abs(reference) < kRelativeThreshold) {
+ error_is_large = (diff > kAbsoluteThreshold);
+ } else {
+ error_is_large = (diff > kRelativeThreshold * std::abs(reference));
+ }
+ if (error_is_large) {
+ good_output = false;
+ if (verbose) {
+ std::cerr << " index " << i << ": got " << computed
+ << ", but expected " << reference << std::endl;
+ }
+ }
+ }
+ return good_output;
+ }
+
+ TfLitePtrUnion data_;
+ size_t num_elements_;
+};
+
+template <>
+void TfLiteDriver::Expectation::SetData<string>(const string& csv_values) {
+ std::cerr << "String tensor not supported!" << std::endl;
+}
+
+template <>
+bool TfLiteDriver::Expectation::TypedCheck<string>(bool verbose,
+ const TfLiteTensor& tensor) {
+ if (tensor.data.raw == nullptr) {
+ if (verbose) {
+ std::cerr << " got empty string" << std::endl;
+ }
+ return false;
+ }
+ int expected_num_strings = GetStringCount(data_.raw);
+ int returned_num_strings = GetStringCount(tensor.data.raw);
+ if (expected_num_strings != returned_num_strings) {
+ if (verbose) {
+ std::cerr << " string count differ: got " << returned_num_strings
+ << ", but expected " << expected_num_strings << std::endl;
+ }
+ return false;
+ }
+ for (int i = 0; i < returned_num_strings; ++i) {
+ auto expected_ref = GetString(data_.raw, i);
+ auto returned_ref = GetString(tensor.data.raw, i);
+ if (expected_ref.len != returned_ref.len) {
+ if (verbose) {
+ std::cerr << " index " << i << ": got string of size "
+ << returned_ref.len << ", but expected size "
+ << expected_ref.len << std::endl;
+ }
+ return false;
+ }
+ if (strncmp(expected_ref.str, returned_ref.str, returned_ref.len) != 0) {
+ if (verbose) {
+ std::cerr << " index " << i << ": strings are different" << std::endl;
+ }
+ return false;
+ }
+ }
+
+ return true;
+}
+
+bool TfLiteDriver::Expectation::Check(bool verbose,
+ const TfLiteTensor& tensor) {
+ switch (tensor.type) {
+ case kTfLiteFloat32:
+ return TypedCheck<float>(verbose, tensor);
+ case kTfLiteInt32:
+ return TypedCheck<int32_t>(verbose, tensor);
+ case kTfLiteInt64:
+ return TypedCheck<int64_t>(verbose, tensor);
+ case kTfLiteUInt8:
+ return TypedCheck<uint8_t>(verbose, tensor);
+ case kTfLiteBool:
+ return TypedCheck<bool>(verbose, tensor);
+ case kTfLiteString:
+ return TypedCheck<string>(verbose, tensor);
+ default:
+ fprintf(stderr, "Unsupported type %d in Check\n", tensor.type);
+ return false;
+ }
+}
+
+TfLiteDriver::TfLiteDriver(bool use_nnapi, const string& delegate_name,
+ bool reference_kernel)
+ : use_nnapi_(use_nnapi) {
+ if (reference_kernel) {
+ resolver_.reset(new ops::builtin::BuiltinRefOpResolver);
+ } else {
+ resolver_.reset(new ops::builtin::BuiltinOpResolver);
+ }
+#if 0
+ if (delegate_name == "FLEX") {
+ delegate_ = FlexDelegate::Create();
+ }
+#endif
+}
+
+TfLiteDriver::~TfLiteDriver() {
+ for (auto t : tensors_to_deallocate_) {
+ DeallocateStringTensor(t.second);
+ }
+ interpreter_.reset();
+}
+
+void TfLiteDriver::AllocateTensors() {
+ if (must_allocate_tensors_) {
+ if (interpreter_->AllocateTensors() != kTfLiteOk) {
+ Invalidate("Failed to allocate tensors");
+ return;
+ }
+ ResetLSTMStateTensors();
+ must_allocate_tensors_ = false;
+ }
+}
+
+void TfLiteDriver::LoadModel(const string& bin_file_path) {
+ if (!IsValid()) return;
+
+ model_ = FlatBufferModel::BuildFromFile(GetFullPath(bin_file_path).c_str());
+ if (!model_) {
+ Invalidate("Failed to mmap model " + bin_file_path);
+ return;
+ }
+ InterpreterBuilder(*model_, *resolver_)(&interpreter_);
+ if (!interpreter_) {
+ Invalidate("Failed build interpreter");
+ return;
+ }
+#if 0
+ if (delegate_) {
+ if (interpreter_->ModifyGraphWithDelegate(delegate_.get()) != kTfLiteOk) {
+ Invalidate("Unable to the build graph using the delegate");
+ return;
+ }
+ }
+#endif
+
+ must_allocate_tensors_ = true;
+}
+
+void TfLiteDriver::ResetTensor(int id) {
+ if (!IsValid()) return;
+ auto* tensor = interpreter_->tensor(id);
+ memset(tensor->data.raw, 0, tensor->bytes);
+}
+
+void TfLiteDriver::ReshapeTensor(int id, const string& csv_values) {
+ if (!IsValid()) return;
+ if (interpreter_->ResizeInputTensor(
+ id, testing::Split<int>(csv_values, ",")) != kTfLiteOk) {
+ Invalidate("Failed to resize input tensor " + std::to_string(id));
+ return;
+ }
+ must_allocate_tensors_ = true;
+}
+
+void TfLiteDriver::SetInput(int id, const string& csv_values) {
+ if (!IsValid()) return;
+ auto* tensor = interpreter_->tensor(id);
+ switch (tensor->type) {
+ case kTfLiteFloat32: {
+ const auto& values = testing::Split<float>(csv_values, ",");
+ if (!CheckSizes<float>(tensor->bytes, values.size())) return;
+ SetTensorData(values, &tensor->data);
+ break;
+ }
+ case kTfLiteInt32: {
+ const auto& values = testing::Split<int32_t>(csv_values, ",");
+ if (!CheckSizes<int32_t>(tensor->bytes, values.size())) return;
+ SetTensorData(values, &tensor->data);
+ break;
+ }
+ case kTfLiteInt64: {
+ const auto& values = testing::Split<int64_t>(csv_values, ",");
+ if (!CheckSizes<int64_t>(tensor->bytes, values.size())) return;
+ SetTensorData(values, &tensor->data);
+ break;
+ }
+ case kTfLiteUInt8: {
+ const auto& values = testing::Split<uint8_t>(csv_values, ",");
+ if (!CheckSizes<uint8_t>(tensor->bytes, values.size())) return;
+ SetTensorData(values, &tensor->data);
+ break;
+ }
+ case kTfLiteBool: {
+ const auto& values = testing::Split<bool>(csv_values, ",");
+ if (!CheckSizes<bool>(tensor->bytes, values.size())) return;
+ SetTensorData(values, &tensor->data);
+ break;
+ }
+ case kTfLiteString: {
+ Invalidate("String tensor not supported!");
+ break;
+ }
+ default:
+ Invalidate("Unsupported tensor type!");
+ return;
+ }
+}
+
+void TfLiteDriver::SetExpectation(int id, const string& csv_values) {
+ if (!IsValid()) return;
+ auto* tensor = interpreter_->tensor(id);
+ if (expected_output_.count(id) != 0) {
+ Invalidate("Overridden expectation for tensor.");
+ }
+ expected_output_[id].reset(new Expectation);
+ switch (tensor->type) {
+ case kTfLiteFloat32:
+ expected_output_[id]->SetData<float>(csv_values);
+ break;
+ case kTfLiteInt32:
+ expected_output_[id]->SetData<int32_t>(csv_values);
+ break;
+ case kTfLiteInt64:
+ expected_output_[id]->SetData<int64_t>(csv_values);
+ break;
+ case kTfLiteUInt8:
+ expected_output_[id]->SetData<uint8_t>(csv_values);
+ break;
+ case kTfLiteBool:
+ expected_output_[id]->SetData<bool>(csv_values);
+ break;
+ case kTfLiteString:
+ expected_output_[id]->SetData<string>(csv_values);
+ break;
+ default:
+ Invalidate("Unsupported tensor type!");
+ return;
+ }
+}
+
+void TfLiteDriver::Invoke() {
+ if (!IsValid()) return;
+ if (use_nnapi_) {
+ if (interpreter_->ModifyGraphWithDelegate(NnApiDelegate()) != kTfLiteOk) {
+ Invalidate("Unable to the build graph using NNAPI delegate");
+ }
+ }
+ if (interpreter_->Invoke() != kTfLiteOk) {
+ Invalidate("Failed to invoke interpreter");
+ }
+}
+
+bool TfLiteDriver::CheckResults() {
+ if (!IsValid()) return false;
+ bool success = true;
+ for (const auto& p : expected_output_) {
+ int id = p.first;
+ auto* tensor = interpreter_->tensor(id);
+ if (!p.second->Check(/*verbose=*/false, *tensor)) {
+ // Do not invalidate anything here. Instead, simply output the
+ // differences and return false. Invalidating would prevent all
+ // subsequent invocations from running..
+ std::cerr << "There were errors in invocation '" << GetInvocationId()
+ << "', output tensor '" << id << "':" << std::endl;
+ p.second->Check(/*verbose=*/true, *tensor);
+ success = false;
+ SetOverallSuccess(false);
+ }
+ }
+ expected_output_.clear();
+ return success;
+}
+
+void TfLiteDriver::ResetLSTMStateTensors() {
+ interpreter_->ResetVariableTensors();
+}
+
+string TfLiteDriver::ReadOutput(int id) {
+ auto* tensor = interpreter_->tensor(id);
+ int num_elements = 1;
+
+ for (int i = 0; i < tensor->dims->size; ++i) {
+ num_elements *= tensor->dims->data[i];
+ }
+
+ switch (tensor->type) {
+ case kTfLiteFloat32:
+ return JoinDefault(tensor->data.f, num_elements, ",");
+ case kTfLiteInt32:
+ return JoinDefault(tensor->data.i32, num_elements, ",");
+ case kTfLiteInt64:
+ return JoinDefault(tensor->data.i64, num_elements, ",");
+ case kTfLiteUInt8:
+ return Join(tensor->data.uint8, num_elements, ",");
+ case kTfLiteInt8:
+ return JoinDefault(tensor->data.int8, num_elements, ",");
+ case kTfLiteBool:
+ return JoinDefault(tensor->data.b, num_elements, ",");
+ default:
+ Invalidate("Unsupported tensor type!");
+ return "";
+ }
+}
+
+} // namespace testing
+} // namespace tflite
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.h
new file mode 100644
index 0000000..b383421
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tflite_driver.h
@@ -0,0 +1,86 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_TFLITE_DRIVER_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_TFLITE_DRIVER_H_
+
+#include <map>
+#include <memory>
+
+#include "tensorflow/lite/interpreter.h"
+#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/kernels/register_ref.h"
+#include "tensorflow/lite/model.h"
+#include "test_runner.h"
+
+namespace tflite {
+namespace testing {
+
+// A test runner that feeds inputs into TF Lite and verifies its outputs.
+class TfLiteDriver : public TestRunner {
+ public:
+ explicit TfLiteDriver(bool use_nnapi, const string& delegate = "",
+ bool reference_kernel = false);
+ ~TfLiteDriver() override;
+
+ void LoadModel(const string& bin_file_path) override;
+ const std::vector<int>& GetInputs() override {
+ return interpreter_->inputs();
+ }
+ const std::vector<int>& GetOutputs() override {
+ return interpreter_->outputs();
+ }
+ void ReshapeTensor(int id, const string& csv_values) override;
+ void AllocateTensors() override;
+ void ResetTensor(int id) override;
+ void SetInput(int id, const string& csv_values) override;
+ void SetExpectation(int id, const string& csv_values) override;
+ void Invoke() override;
+ bool CheckResults() override;
+ string ReadOutput(int id) override;
+
+ private:
+ void DeallocateStringTensor(TfLiteTensor* t) {
+ if (t) {
+ free(t->data.raw);
+ t->data.raw = nullptr;
+ }
+ }
+ void AllocateStringTensor(int id, size_t num_bytes, TfLiteTensor* t) {
+ t->data.raw = reinterpret_cast<char*>(malloc(num_bytes));
+ t->bytes = num_bytes;
+ tensors_to_deallocate_[id] = t;
+ }
+
+ void ResetLSTMStateTensors();
+
+ class Expectation;
+
+ std::unique_ptr<OpResolver> resolver_;
+ std::unique_ptr<TfLiteDelegate> delegate_;
+ bool use_nnapi_ = false;
+ std::unique_ptr<FlatBufferModel> model_;
+ std::unique_ptr<Interpreter> interpreter_;
+ std::map<int, std::unique_ptr<Expectation>> expected_output_;
+ bool must_allocate_tensors_ = true;
+ std::map<int, TfLiteTensor*> tensors_to_deallocate_;
+};
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_TFLITE_DRIVER_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.cc b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.cc
new file mode 100644
index 0000000..95251dc
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.cc
@@ -0,0 +1,98 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#include "tokenize.h"
+#include <istream>
+#include <string>
+#include "tensorflow/lite/string_tflite.h"
+
+namespace tflite {
+namespace testing {
+
+void Tokenize(std::istream* input, TokenProcessor* processor) {
+ enum State { kBuildQuotedToken, kBuildToken, kIdle };
+
+ std::string current_token;
+ State state = kIdle;
+ auto start_token = [&](char c) {
+ state = kBuildToken;
+ current_token.clear();
+ current_token = c;
+ };
+ auto issue_token = [&]() {
+ state = kIdle;
+ processor->ConsumeToken(¤t_token);
+ current_token.clear();
+ };
+ auto start_quoted_token = [&]() {
+ state = kBuildQuotedToken;
+ current_token.clear();
+ };
+ auto issue_quoted_token = [&]() {
+ state = kIdle;
+ processor->ConsumeToken(¤t_token);
+ current_token.clear();
+ };
+ auto issue_delim = [&](char d) {
+ current_token = string(1, d);
+ processor->ConsumeToken(¤t_token);
+ current_token.clear();
+ };
+ auto is_delim = [](char c) { return c == '{' || c == '}' || c == ':'; };
+ auto is_quote = [](char c) { return c == '"'; };
+
+ for (auto it = std::istreambuf_iterator<char>(*input);
+ it != std::istreambuf_iterator<char>(); ++it) {
+ switch (state) {
+ case kIdle:
+ if (is_delim(*it)) {
+ issue_delim(*it);
+ } else if (is_quote(*it)) {
+ start_quoted_token();
+ } else if (!isspace(*it)) {
+ start_token(*it);
+ }
+ break;
+ case kBuildToken:
+ if (is_delim(*it)) {
+ issue_token();
+ issue_delim(*it);
+ } else if (is_quote(*it)) {
+ issue_token();
+ start_quoted_token();
+ } else if (isspace(*it)) {
+ issue_token();
+ } else {
+ current_token += *it;
+ }
+ break;
+ case kBuildQuotedToken:
+ if (is_quote(*it)) {
+ issue_quoted_token();
+ } else {
+ current_token += *it;
+ }
+ break;
+ }
+ }
+ if (state != kIdle) {
+ issue_token();
+ }
+}
+
+} // namespace testing
+} // namespace tflite
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.h
new file mode 100644
index 0000000..31b84c2
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/tokenize.h
@@ -0,0 +1,45 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_TOKENIZE_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_TOKENIZE_H_
+
+#include <istream>
+#include <string>
+
+namespace tflite {
+namespace testing {
+
+// Process tokens coming from Tokenize().
+class TokenProcessor {
+ public:
+ virtual ~TokenProcessor() {}
+ // Process a single token. The token won't be reused, so it is OK to call
+ // token.swap().
+ virtual void ConsumeToken(std::string* token) = 0;
+};
+
+// Tokenize a stream on whitespaces, colons and curly braces. Whitespaces are
+// removed from the tokens and double-quotes can be used to avoid that. Note
+// that there is no way to escape double-quotes, so there's no way to have a
+// double-quote inside a token.
+void Tokenize(std::istream* input, TokenProcessor* processor);
+
+} // namespace testing
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_TOKENIZE_H_
diff --git a/tensorflow/lite/testing/nnapi_tflite_zip_tests/util.h b/tensorflow/lite/testing/nnapi_tflite_zip_tests/util.h
new file mode 100644
index 0000000..883c5e0
--- /dev/null
+++ b/tensorflow/lite/testing/nnapi_tflite_zip_tests/util.h
@@ -0,0 +1,62 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+// NOTE: this is a Android version of the file with the same name in parent folder.
+// The main difference is the removal of absl, re2 and tensorflow core dependencies.
+
+#ifndef TENSORFLOW_LITE_TESTING_ANDROID_UTIL_H_
+#define TENSORFLOW_LITE_TESTING_ANDROID_UTIL_H_
+
+#include <cstdio>
+
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/string_tflite.h"
+
+namespace tflite {
+
+// An ErrorReporter that collects error message in a string, in addition
+// to printing to stderr.
+class TestErrorReporter : public ErrorReporter {
+ public:
+ int Report(const char* format, va_list args) override {
+ char buffer[1024];
+ int size = vsnprintf(buffer, sizeof(buffer), format, args);
+ fprintf(stderr, "%s", buffer);
+ error_messages_ += buffer;
+ num_calls_++;
+ return size;
+ }
+
+ void Reset() {
+ num_calls_ = 0;
+ error_messages_.clear();
+ }
+
+ int num_calls() const { return num_calls_; }
+ const string& error_messages() const { return error_messages_; }
+
+ private:
+ int num_calls_ = 0;
+ string error_messages_;
+};
+
+inline void LogToStderr() {
+#ifdef PLATFORM_GOOGLE
+ FLAGS_logtostderr = true;
+#endif
+}
+
+} // namespace tflite
+
+#endif // TENSORFLOW_LITE_TESTING_ANDROID_UTIL_H_
diff --git a/tensorflow/lite/tflite_static.bp b/tensorflow/lite/tflite_static.bp
index 3022093..d05bf0d 100644
--- a/tensorflow/lite/tflite_static.bp
+++ b/tensorflow/lite/tflite_static.bp
@@ -26,7 +26,7 @@
"core/api/op_resolver.cc",
"core/subgraph.cc",
"delegates/nnapi/nnapi_delegate.cc",
- "graph_info.cc",
+ "graph_info.cc",
"interpreter.cc",
"minimal_logging.cc",
"minimal_logging_android.cc",
@@ -39,9 +39,9 @@
"stderr_reporter.cc",
"string_util.cc",
"util.cc",
- "kernels/elementwise.cc",
- "kernels/split.cc",
- "kernels/topk_v2.cc",
+ "kernels/elementwise.cc",
+ "kernels/split.cc",
+ "kernels/topk_v2.cc",
"kernels/activations.cc",
"kernels/add.cc",
"kernels/add_n.cc",
@@ -95,6 +95,7 @@
"kernels/rank.cc",
"kernels/reduce.cc",
"kernels/register.cc",
+ "kernels/register_ref.cc",
"kernels/reshape.cc",
"kernels/resize_bilinear.cc",
"kernels/resize_nearest_neighbor.cc",
