[Runtime] MISRA-C compliant TVM runtime (apache#3934)

* implement of MISRA-C compliant TVM runtime;

* working on bundle_deploy_c demo

* move header files into include dir

* fix compatibility issues

* fix compatibility issues

* resolve most of the warnings and errros

* implement c_backend_api

* introduce bridge

* working well

* move to header files and bundle.c into src/runtime/crt

* clean up

* satisfy linter

* clean up

* test with the cat image

* remove synset

* refactoring

* refactoring

* refactoring

* initial crt_runtime_api.c

* improved compatibility with g++

* using exposed API in c_runtime_api.h

* call from c_runtime_api.h

* clean up

* lint

* merge into apps/bundle_deploy directory

Change-Id: I51904db81b8589e65d107d8ca77b47452e3812b5

* make the demo runs in ci

Change-Id: I2c24f8b592508833d3555311c2b24d1931f19385

* address review comments

Change-Id: I027ddff15c31fb4da0bd0e461427dce619de1f93

* release

Change-Id: I5ad5bb8426468aac9fc8d074e56ddea358a7fd91

* fix ci testing

Change-Id: Ic2e82fb3051b6c254ef32a964f976b61e3e5fe4d

* add test case for misra c runtime

Change-Id: Ie0dfd0ade6be4665b4384db7d260a6c69b35010f

* fread files in testing to avoid calling xxd

Change-Id: Ie7fbc16b4b0b9509918d986a841f443900813bef

apps/bundle_deploy/Makefile

@@ -17,40 +17,80 @@
 
 # Makefile Example to bundle TVM modules.
 
+# Setup build environment
 TVM_ROOT=$(shell cd ../..; pwd)
 DMLC_CORE=${TVM_ROOT}/3rdparty/dmlc-core
-PKG_CFLAGS = -std=c++14 -O2 -fPIC\
-	-I${TVM_ROOT}/include\
-	-I${DMLC_CORE}/include\
+PKG_CXXFLAGS = -std=c++14 -O2 -fPIC \
+	-I${TVM_ROOT}/include \
+	-I${DMLC_CORE}/include \
+	-I${TVM_ROOT}/3rdparty/dlpack/include
+PKG_CFLAGS = -std=c99 -O2 -fPIC \
+	-I${TVM_ROOT}/include \
+	-I${DMLC_CORE}/include \
 	-I${TVM_ROOT}/3rdparty/dlpack/include
 
 PKG_LDFLAGS = -pthread
 
 build_dir := build
 
-test: $(build_dir)/demo $(build_dir)/bundle.so
-	$(build_dir)/demo $(build_dir)/bundle.so
+demo: $(build_dir)/demo $(build_dir)/bundle.so $(build_dir)/bundle_c.so $(build_dir)/cat.bin
+	TVM_NUM_THREADS=1 $(build_dir)/demo $(build_dir)/bundle.so $(build_dir)/cat.bin
+	TVM_NUM_THREADS=1 $(build_dir)/demo $(build_dir)/bundle_c.so $(build_dir)/cat.bin
+
+test: $(build_dir)/test $(build_dir)/test_bundle.so $(build_dir)/test_bundle_c.so $(build_dir)/test_data.bin $(build_dir)/test_output.bin
+	TVM_NUM_THREADS=1 $(build_dir)/test $(build_dir)/test_bundle.so $(build_dir)/test_data.bin $(build_dir)/test_output.bin $(build_dir)/test_graph.json $(build_dir)/test_params.bin
+	TVM_NUM_THREADS=1 $(build_dir)/test $(build_dir)/test_bundle_c.so $(build_dir)/test_data.bin $(build_dir)/test_output.bin $(build_dir)/test_graph.json $(build_dir)/test_params.bin
+
+$(build_dir)/demo: demo.cc ${build_dir}/graph.json.c ${build_dir}/params.bin.c
+	@mkdir -p $(@D)
+	g++ $(PKG_CXXFLAGS) -o $@  demo.cc -ldl
 
-$(build_dir)/demo: demo.cc
+$(build_dir)/test: test.cc ${build_dir}/test_graph.json ${build_dir}/test_params.bin
 	@mkdir -p $(@D)
-	$(CXX) $(PKG_CFLAGS) -o $@  $^ -ldl
+	g++ $(PKG_CXXFLAGS) -o $@  test.cc -ldl
 
 # Serialize our graph.json file.
-$(build_dir)/graph.json.cc: $(build_dir)/graph.json
+$(build_dir)/graph.json.c: $(build_dir)/graph.json
 	xxd -i $^  > $@
 
 # Serialize our params.bin file.
-$(build_dir)/params.bin.cc: $(build_dir)/params.bin
+$(build_dir)/params.bin.c: $(build_dir)/params.bin
 	xxd -i $^  > $@
 
-$(build_dir)/model.o $(build_dir)/graph.json $(build_dir)/params.bin: build_model.py
+# # Serialize our test_graph.json file.
+# $(build_dir)/test_graph.json.c: $(build_dir)/test_graph.json
+# 	xxd -i $^  > $@
+# 
+# # Serialize our test_params.bin file.
+# $(build_dir)/test_params.bin.c: $(build_dir)/test_params.bin
+# 	xxd -i $^  > $@
+
+$(build_dir)/model.o $(build_dir)/graph.json $(build_dir)/params.bin $(build_dir)/cat.bin: build_model.py
 	python3 $< -o $(build_dir)
 
-# Build our bundle against the serialized bundle.cc API, the runtime.cc API, and
+$(build_dir)/test_model.o $(build_dir)/test_graph.json $(build_dir)/test_params.bin $(build_dir)/test_data.bin $(build_dir)/test_output.bin: build_model.py
+	python3 $< -o $(build_dir) --test
+
+# Build our bundle against the serialized bundle.c API, the runtime.cc API, and
 # the serialized graph.json and params.bin
-$(build_dir)/bundle.so: bundle.cc runtime.cc $(build_dir)/model.o $(build_dir)/graph.json.cc $(build_dir)/params.bin.cc
+$(build_dir)/bundle.so: bundle.cc runtime.cc $(build_dir)/model.o
 	@mkdir -p $(@D)
-	$(CXX) -shared $(PKG_CFLAGS) -fvisibility=hidden -o $@  $^ $(PKG_LDFLAGS)
+	g++ -shared $(PKG_CXXFLAGS) -fvisibility=hidden -o $@  $^ $(PKG_LDFLAGS)
+
+$(build_dir)/bundle_c.so: bundle.c runtime.c $(build_dir)/model.o
+	@mkdir -p $(@D)
+	gcc -shared $(PKG_CFLAGS) -fvisibility=hidden -o $@  $^ $(PKG_LDFLAGS)
+
+$(build_dir)/test_bundle.so: bundle.cc runtime.cc $(build_dir)/test_model.o
+	@mkdir -p $(@D)
+	g++ -shared $(PKG_CXXFLAGS) -fvisibility=hidden -o $@  $^ $(PKG_LDFLAGS)
+
+$(build_dir)/test_bundle_c.so: bundle.c runtime.c $(build_dir)/test_model.o
+	@mkdir -p $(@D)
+	gcc -shared $(PKG_CFLAGS) -fvisibility=hidden -o $@  $^ $(PKG_LDFLAGS)
 
 clean:
-	rm -r $(build_dir)
+	rm -rf $(build_dir)/bundle.so $(build_dir)/bundle_c.so $(build_dir)/test_bundle.so $(build_dir)/test_bundle_c.so
+
+cleanall:
+	rm -rf $(build_dir)

apps/bundle_deploy/README.md

@@ -45,9 +45,10 @@ make demo
 This will:
 
 - Download the mobilenet0.25 model from the MXNet Gluon Model Zoo
-- Compile the model with NNVM
+- Compile the model with Relay
 - Build a `bundle.so` shared object containing the model specification and
   parameters
-- Build a `demo` executable that `dlopen`'s `bundle.so`, instantiates the
-  contained graph runtime, and invokes the `GraphRuntime::Run` function on a
-  random input, then prints the output tensor to `stderr`.
+- Build a `demo` executable that `dlopen`'s `bundle.so` (or `bundle_c.so` in 
+  terms of the MISRA-C runtime), instantiates the contained graph runtime,
+  and invokes the `GraphRuntime::Run` function on a cat image, then prints
+  the output results.

apps/bundle_deploy/build_model.py

@@ -22,15 +22,9 @@
 import tvm
 from tvm import te
 import logging
+import json
 
-
-def main():
-    logging.basicConfig(level=logging.INFO)
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument('-o', '--out-dir', default='.')
-    opts = parser.parse_args()
-
+def build_module(opts):
     dshape = (1, 3, 224, 224)
     from mxnet.gluon.model_zoo.vision import get_model
     block = get_model('mobilenet0.25', pretrained=True)
@@ -53,6 +47,69 @@ def main():
     with open(os.path.join(build_dir, 'params.bin'), 'wb') as f_params:
         f_params.write(relay.save_param_dict(params))
 
+def build_test_module(opts):
+    import numpy as np
+
+    x = relay.var('x', shape=(10, 5))
+    y = relay.var('y', shape=(1, 5))
+    z = relay.add(x, y)
+    func = relay.Function([x, y], z)
+    x_data = np.random.rand(10, 5).astype('float32')
+    y_data = np.random.rand(1, 5).astype('float32')
+    params = {"y": y_data}
+    graph, lib, params = relay.build(
+        tvm.IRModule.from_expr(func), "llvm --system-lib", params=params)
+
+    build_dir = os.path.abspath(opts.out_dir)
+    if not os.path.isdir(build_dir):
+        os.makedirs(build_dir)
+
+    lib.save(os.path.join(build_dir, 'test_model.o'))
+    with open(os.path.join(build_dir, 'test_graph.json'), 'w') as f_graph_json:
+        f_graph_json.write(graph)
+    with open(os.path.join(build_dir, 'test_params.bin'), 'wb') as f_params:
+        f_params.write(relay.save_param_dict(params))
+    with open(os.path.join(build_dir, "test_data.bin"), "wb") as fp:
+        fp.write(x_data.astype(np.float32).tobytes())
+    x_output = x_data + y_data
+    with open(os.path.join(build_dir, "test_output.bin"), "wb") as fp:
+        fp.write(x_output.astype(np.float32).tobytes())
+
+def build_inputs(opts):
+    from tvm.contrib import download
+    from PIL import Image
+    import numpy as np
+
+    build_dir = os.path.abspath(opts.out_dir)
+
+    # Download test image
+    image_url = 'https://homes.cs.washington.edu/~moreau/media/vta/cat.jpg'
+    image_fn = os.path.join(build_dir, "cat.png")
+    download.download(image_url, image_fn)
+    image = Image.open(image_fn).resize((224, 224))
+
+    def transform_image(image):
+        image = np.array(image) - np.array([123., 117., 104.])
+        image /= np.array([58.395, 57.12, 57.375])
+        image = image.transpose((2, 0, 1))
+        image = image[np.newaxis, :]
+        return image
+
+    x = transform_image(image)
+    print('x', x.shape)
+    with open(os.path.join(build_dir, "cat.bin"), "wb") as fp:
+        fp.write(x.astype(np.float32).tobytes())
 
 if __name__ == '__main__':
-    main()
+    logging.basicConfig(level=logging.INFO)
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-o', '--out-dir', default='.')
+    parser.add_argument('-t', '--test', action='store_true')
+    opts = parser.parse_args()
+
+    if opts.test:
+        build_test_module(opts)
+    else:
+        build_module(opts)
+        build_inputs(opts)

apps/bundle_deploy/bundle.c

@@ -0,0 +1,89 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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 <tvm/runtime/c_runtime_api.h>
+#include <stdio.h>
+#include <stdlib.h>
+
+/*! \brief macro to do C API call */
+#define TVM_CCALL(func)                                                 \
+  do {                                                                  \
+    int ret = (func);                                                   \
+    if (ret != 0) {                                                     \
+      fprintf(stderr, "%s: %d: error: %s\n", __FILE__, __LINE__, TVMGetLastError()); \
+      exit(ret);                                                        \
+    }                                                                   \
+  } while (0)
+
+TVM_DLL void * tvm_runtime_create(const char * json_data,
+                                  const char * params_data,
+                                  const uint64_t params_size) {
+  int64_t device_type = kDLCPU;
+  int64_t device_id = 0;
+
+  TVMByteArray params;
+  params.data = params_data;
+  params.size = params_size;
+
+  TVMContext ctx;
+  ctx.device_type = (DLDeviceType)device_type;
+  ctx.device_id = device_id;
+
+  // declare pointers
+  TVMModuleHandle (*SystemLibraryCreate)();
+  TVMModuleHandle (*TVMGraphRuntimeCreate)(const char *, const TVMModuleHandle, const TVMContext *);
+  int (*TVMGraphRuntime_LoadParams)(TVMModuleHandle, const char *, const uint32_t);
+
+  // get pointers
+  TVM_CCALL(TVMFuncGetGlobal("runtime.SystemLib", (TVMFunctionHandle*)&SystemLibraryCreate));
+  TVM_CCALL(TVMFuncGetGlobal("tvm.graph_runtime.create", (TVMFunctionHandle*)&TVMGraphRuntimeCreate));
+
+  // run modules
+  TVMModuleHandle mod_syslib = SystemLibraryCreate();
+  TVMModuleHandle mod = TVMGraphRuntimeCreate(json_data, mod_syslib, &ctx);
+  TVM_CCALL(TVMModGetFunction(mod, "load_params", 0, (TVMFunctionHandle*)&TVMGraphRuntime_LoadParams));
+  TVMGraphRuntime_LoadParams(mod, params.data, params.size);
+
+  return mod;
+}
+
+TVM_DLL void tvm_runtime_destroy(void * runtime) {
+  void (*TVMGraphRuntimeRelease)(TVMModuleHandle *);
+  TVM_CCALL(TVMFuncGetGlobal("tvm.graph_runtime.release", (TVMFunctionHandle*)&TVMGraphRuntimeRelease));
+  TVMGraphRuntimeRelease(&runtime);
+}
+
+TVM_DLL void tvm_runtime_set_input(void * runtime, const char * name, DLTensor * tensor) {
+  void (*TVMGraphRuntime_SetInput)(TVMModuleHandle, const char *, DLTensor*);
+  TVM_CCALL(TVMFuncGetGlobal("tvm.graph_runtime.set_input", (TVMFunctionHandle*)&TVMGraphRuntime_SetInput));
+  TVMGraphRuntime_SetInput(runtime, name, tensor);
+}
+
+TVM_DLL void tvm_runtime_run(void * runtime) {
+  void (*TVMGraphRuntime_Run)(TVMModuleHandle runtime);
+  TVM_CCALL(TVMFuncGetGlobal("tvm.graph_runtime.run", (TVMFunctionHandle*)&TVMGraphRuntime_Run));
+  TVMGraphRuntime_Run(runtime);
+}
+
+TVM_DLL void tvm_runtime_get_output(void * runtime, int32_t index, DLTensor * tensor) {
+  int (*TVMGraphRuntime_GetOutput)(TVMModuleHandle, const int32_t, DLTensor *);
+  TVM_CCALL(TVMFuncGetGlobal("tvm.graph_runtime.get_output", (TVMFunctionHandle*)&TVMGraphRuntime_GetOutput));
+  TVMGraphRuntime_GetOutput(runtime, index, tensor);
+}
+

apps/bundle_deploy/bundle.cc

@@ -21,16 +21,14 @@
 #include <tvm/runtime/c_runtime_api.h>
 #include <tvm/runtime/registry.h>
 
-extern unsigned char build_graph_json[];
-extern unsigned int build_graph_json_len;
-extern unsigned char build_params_bin[];
-extern unsigned int build_params_bin_len;
-
 #define TVM_BUNDLE_FUNCTION __attribute__((visibility("default")))
 
 extern "C" {
 
-TVM_BUNDLE_FUNCTION void *tvm_runtime_create() {
+TVM_BUNDLE_FUNCTION void *tvm_runtime_create(const char * build_graph_json,
+                                             const char * build_params_bin,
+                                             const uint64_t build_params_bin_len) {
+  const int build_graph_json_len = strlen(build_graph_json);
   const std::string json_data(&build_graph_json[0],
                               &build_graph_json[0] + build_graph_json_len);
   tvm::runtime::Module mod_syslib =