[Golang][Doc] improve the samples and doc (apache#4385)

* [Golang][Doc] improve the samples and doc

* [Golang][Doc] add asf header

* [Golang][Doc] Improve the end to end example

* [Golang][Doc] Improve the end to end example

Author: cchung100m

golang/README.md

@@ -68,6 +68,8 @@ To Demonstrates sample TVM module compilation using python and deploy via golang
 
 To deploy a realtime module with lib, graph and param.
 ```bash
+python3 gen_mobilenet_lib.py
+
 ./complex
 ```
 
@@ -80,13 +82,13 @@ To demonstrate go function closure conversion to packed function handle.
 To demonstrate a packed function handle given as an argument.
 
 ```bash
-pack_func_handle_arg
+./pack_func_handle_arg
 ```
 
 To register go function with runtime as a global function.
 
 ```bash
-pack_func_register
+./pack_func_register
 ```
 
 To demonstrate function closure passed as argument to a function call.
@@ -120,5 +122,5 @@ Please refer ```docker/install/ubuntu_install_golang.sh``` for the packages depe
 go compiler 1.10 on ubuntu doesn't install on standard path, hence an explicit export may be needed as shown below.
 
 ```bash
-export PATH="/usr/lib/go-1.10/bin:$PATH"```
+export PATH="/usr/lib/go-1.10/bin:$PATH"
 ```

golang/sample/Makefile

@@ -31,4 +31,4 @@ all: $(EXECUTABLE)
 	@go tool compile -pack -o $@ $<
 
 clean:
-	@rm -f $(EXECUTABLE) *.so *.o *.a
+	@rm -f $(EXECUTABLE) *.so *.o *.a *.json *.params

golang/sample/complex.go

@@ -89,7 +89,7 @@ func main() {
 
     // Array allocation attributes
     tshapeIn  := []int64{1, 224, 224, 3}
-    tshapeOut := []int64{1, 1001}
+    tshapeOut := []int64{1, 1000}
 
     // Allocate input Array
     inX, err := gotvm.Empty(tshapeIn, "float32", gotvm.CPU(0))

golang/sample/gen_mobilenet_lib.py

@@ -0,0 +1,91 @@
+# 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.
+
+import os
+from tvm import relay
+from tvm.contrib.download import download_testdata
+import tflite.Model
+
+
+################################################
+# Utils for downloading and extracting zip files
+# ----------------------------------------------
+def extract(path):
+    import tarfile
+    if path.endswith("tgz") or path.endswith("gz"):
+        dir_path = os.path.dirname(path)
+        tar = tarfile.open(path)
+        tar.extractall(path=dir_path)
+        tar.close()
+    else:
+        raise RuntimeError('Could not decompress the file: ' + path)
+
+
+###################################
+# Download TFLite pre-trained model
+# ---------------------------------
+
+model_url = "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz"
+model_path = download_testdata(model_url, "mobilenet_v2_1.4_224.tgz", module=['tf', 'official'])
+model_dir = os.path.dirname(model_path)
+extract(model_path)
+
+# now we have mobilenet_v2_1.4_224.tflite on disk
+model_file = os.path.join(model_dir, "mobilenet_v2_1.4_224.tflite")
+
+# get TFLite model from buffer
+tflite_model_buf = open(model_file, "rb").read()
+tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+
+##############################
+# Load Neural Network in Relay
+# ----------------------------
+
+# TFLite input tensor name, shape and type
+input_tensor = "input"
+input_shape = (1, 224, 224, 3)
+input_dtype = "float32"
+
+# parse TFLite model and convert into Relay computation graph
+mod, params = relay.frontend.from_tflite(tflite_model,
+                                         shape_dict={input_tensor: input_shape},
+                                         dtype_dict={input_tensor: input_dtype})
+
+#############
+# Compilation
+# -----------
+
+target = 'llvm'
+
+# Build with Relay
+with relay.build_config(opt_level=3):
+    graph, lib, params = relay.build_module.build(
+        mod, target, params=params)
+
+###############################################
+# Save the graph, lib and parameters into files
+# ---------------------------------------------
+
+lib.export_library("./mobilenet.so")
+print('lib export succeefully')
+
+with open("./mobilenet.json", "w") as fo:
+   fo.write(graph)
+
+with open("./mobilenet.params", "wb") as fo:
+   fo.write(relay.save_param_dict(params))