[MXNET-357] New Scala API Design (Symbol) (apache#10660)

* Simplfied current Macros impl to Quasiquote
* Change the Symbol Function Field, add SymbolArg
* Fix the Macros problem, disable the hidden function _
* Add Implementation for New API
* Add examples and comments
* Add _contrib_ support
* New namespace for Symbol API
* Change names and add comments
* add TODOs and name changes
* Add relative path to MXNET_BASEDIR
* Update Base.scala

scala-package/core/src/main/scala/org/apache/mxnet/Symbol.scala

@@ -830,6 +830,8 @@ object Symbol {
   private val functions: Map[String, SymbolFunction] = initSymbolModule()
   private val bindReqMap = Map("null" -> 0, "write" -> 1, "add" -> 3)
 
+  val api = SymbolAPI
+
   def pow(sym1: Symbol, sym2: Symbol): Symbol = {
     Symbol.createFromListedSymbols("_Power")(Array(sym1, sym2))
   }

scala-package/core/src/main/scala/org/apache/mxnet/SymbolAPI.scala

@@ -0,0 +1,26 @@
+/*
+ * 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.
+ */
+package org.apache.mxnet
+
+
+@AddSymbolAPIs(false)
+/**
+  * typesafe Symbol API: Symbol.api._
+  * Main code will be generated during compile time through Macros
+  */
+object SymbolAPI {
+}

scala-package/examples/src/main/scala/org/apache/mxnetexamples/imclassification/TrainMnist.scala

@@ -30,40 +30,40 @@ object TrainMnist {
   // multi-layer perceptron
   def getMlp: Symbol = {
     val data = Symbol.Variable("data")
-    val fc1 = Symbol.FullyConnected(name = "fc1")()(Map("data" -> data, "num_hidden" -> 128))
-    val act1 = Symbol.Activation(name = "relu1")()(Map("data" -> fc1, "act_type" -> "relu"))
-    val fc2 = Symbol.FullyConnected(name = "fc2")()(Map("data" -> act1, "num_hidden" -> 64))
-    val act2 = Symbol.Activation(name = "relu2")()(Map("data" -> fc2, "act_type" -> "relu"))
-    val fc3 = Symbol.FullyConnected(name = "fc3")()(Map("data" -> act2, "num_hidden" -> 10))
-    val mlp = Symbol.SoftmaxOutput(name = "softmax")()(Map("data" -> fc3))
+
+    val fc1 = Symbol.api.FullyConnected(data = Some(data), num_hidden = 128, name = "fc1")
+    val act1 = Symbol.api.Activation (data = Some(fc1), "relu", name = "relu")
+    val fc2 = Symbol.api.FullyConnected(Some(act1), None, None, 64, name = "fc2")
+    val act2 = Symbol.api.Activation(data = Some(fc2), "relu", name = "relu2")
+    val fc3 = Symbol.api.FullyConnected(Some(act2), None, None, 10, name = "fc3")
+    val mlp = Symbol.api.SoftmaxOutput(name = "softmax", data = Some(fc3))
     mlp
   }
 
   // LeCun, Yann, Leon Bottou, Yoshua Bengio, and Patrick
   // Haffner. "Gradient-based learning applied to document recognition."
   // Proceedings of the IEEE (1998)
+
   def getLenet: Symbol = {
     val data = Symbol.Variable("data")
     // first conv
-    val conv1 = Symbol.Convolution()()(
-      Map("data" -> data, "kernel" -> "(5, 5)", "num_filter" -> 20))
-    val tanh1 = Symbol.Activation()()(Map("data" -> conv1, "act_type" -> "tanh"))
-    val pool1 = Symbol.Pooling()()(Map("data" -> tanh1, "pool_type" -> "max",
-                                       "kernel" -> "(2, 2)", "stride" -> "(2, 2)"))
+    val conv1 = Symbol.api.Convolution(data = Some(data), kernel = Shape(5, 5), num_filter = 20)
+    val tanh1 = Symbol.api.tanh(data = Some(conv1))
+    val pool1 = Symbol.api.Pooling(data = Some(tanh1), pool_type = Some("max"),
+      kernel = Some(Shape(2, 2)), stride = Some(Shape(2, 2)))
     // second conv
-    val conv2 = Symbol.Convolution()()(
-      Map("data" -> pool1, "kernel" -> "(5, 5)", "num_filter" -> 50))
-    val tanh2 = Symbol.Activation()()(Map("data" -> conv2, "act_type" -> "tanh"))
-    val pool2 = Symbol.Pooling()()(Map("data" -> tanh2, "pool_type" -> "max",
-                                       "kernel" -> "(2, 2)", "stride" -> "(2, 2)"))
+    val conv2 = Symbol.api.Convolution(data = Some(pool1), kernel = Shape(5, 5), num_filter = 50)
+    val tanh2 = Symbol.api.tanh(data = Some(conv2))
+    val pool2 = Symbol.api.Pooling(data = Some(tanh2), pool_type = Some("max"),
+      kernel = Some(Shape(2, 2)), stride = Some(Shape(2, 2)))
     // first fullc
-    val flatten = Symbol.Flatten()()(Map("data" -> pool2))
-    val fc1 = Symbol.FullyConnected()()(Map("data" -> flatten, "num_hidden" -> 500))
-    val tanh3 = Symbol.Activation()()(Map("data" -> fc1, "act_type" -> "tanh"))
+    val flatten = Symbol.api.Flatten(data = Some(pool2))
+    val fc1 = Symbol.api.FullyConnected(data = Some(flatten), num_hidden = 500)
+    val tanh3 = Symbol.api.tanh(data = Some(fc1))
     // second fullc
-    val fc2 = Symbol.FullyConnected()()(Map("data" -> tanh3, "num_hidden" -> 10))
+    val fc2 = Symbol.api.FullyConnected(data = Some(tanh3), num_hidden = 10)
     // loss
-    val lenet = Symbol.SoftmaxOutput(name = "softmax")()(Map("data" -> fc2))
+    val lenet = Symbol.api.SoftmaxOutput(name = "softmax", data = Some(fc2))
     lenet
   }
 

scala-package/init/src/main/scala/org/apache/mxnet/init/Base.scala

@@ -37,7 +37,12 @@ object Base {
 
   @throws(classOf[UnsatisfiedLinkError])
   private def tryLoadInitLibrary(): Unit = {
-    val baseDir = System.getProperty("user.dir") + "/init-native"
+    var baseDir = System.getProperty("user.dir") + "/init-native"
+    // TODO(lanKing520) Update this to use relative path to the MXNet director.
+    // TODO(lanking520) baseDir = sys.env("MXNET_BASEDIR") + "/scala-package/init-native"
+    if (System.getenv().containsKey("MXNET_BASEDIR")) {
+      baseDir = sys.env("MXNET_BASEDIR")
+    }
     val os = System.getProperty("os.name")
     // ref: http://lopica.sourceforge.net/os.html
     if (os.startsWith("Linux")) {

scala-package/macros/pom.xml

@@ -52,4 +52,42 @@
       <type>${libtype}</type>
     </dependency>
   </dependencies>
+
+  <build>
+    <plugins>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-jar-plugin</artifactId>
+        <configuration>
+          <excludes>
+            <exclude>META-INF/*.SF</exclude>
+            <exclude>META-INF/*.DSA</exclude>
+            <exclude>META-INF/*.RSA</exclude>
+          </excludes>
+        </configuration>
+      </plugin>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-compiler-plugin</artifactId>
+      </plugin>
+      <plugin>
+        <groupId>org.scalatest</groupId>
+        <artifactId>scalatest-maven-plugin</artifactId>
+        <configuration>
+          <environmentVariables>
+            <MXNET_BASEDIR>${project.parent.basedir}/init-native</MXNET_BASEDIR>
+          </environmentVariables>
+          <argLine>
+            -Djava.library.path=${project.parent.basedir}/native/${platform}/target \
+            -Dlog4j.configuration=file://${project.basedir}/src/test/resources/log4j.properties
+          </argLine>
+        </configuration>
+      </plugin>
+      <plugin>
+        <groupId>org.scalastyle</groupId>
+        <artifactId>scalastyle-maven-plugin</artifactId>
+      </plugin>
+    </plugins>
+  </build>
+
 </project>