Upgrading to TensorFlow v1.2.1

**NOTE** DeviceList is still not available in binary, the function body
is a placeholder right now and will be activate in the future version.

README.md

@@ -50,7 +50,7 @@ Ensure you have installed and activated the latest Swift 3.1 tool chain; The sou
 
 ## Project Status
 
-The framework is Beta testing now. 
+The framework is Beta testing now.
 
 ## Development Notes
 
@@ -80,7 +80,7 @@ API programming topics can be found in [Perfect TensorFlow Guide](GUIDE.md)
 ### TensorFlow C API Library Installation
 
 Perfect-TensorFlow is based on TensorFlow C API, i.e., `libtensorflow.so` on runtime.
-This project contains an express CPU v1.2.0 installation script for this module on both macOS / Ubuntu Linux, and will install the dynamic library into path `/usr/local/lib/libtensorflow.so`. You can download & run [`install.sh`](https://github.com/PerfectlySoft/Perfect-TensorFlow/blob/master/install.sh). Before running this script, please make sure that `wget` has been installed onto your computer, otherwise please run either `brew install wget` for macOS or `sudo apt-get install wget` for Ubuntu first.
+This project contains an express CPU v1.2.1 installation script for this module on both macOS / Ubuntu Linux, and will install the dynamic library into path `/usr/local/lib/libtensorflow.so`. You can download & run [`install.sh`](https://github.com/PerfectlySoft/Perfect-TensorFlow/blob/master/install.sh). Before running this script, please make sure that `wget` has been installed onto your computer, otherwise please run either `brew install wget` for macOS or `sudo apt-get install wget` for Ubuntu first.
 
 For more installation options, such as GPU/CPU and multiple versions on the same machine, please check TensorFlow website: [Installing TensorFlow for C](https://www.tensorflow.org/install/install_c)
 
@@ -101,7 +101,7 @@ import TensorFlowAPI
 // This is the Swift version of TensorFlow classes and objects
 import PerfectTensorFlow
 
-// To keep the naming consistency with TensorFlow in other languages such as 
+// To keep the naming consistency with TensorFlow in other languages such as
 // Python or Java, making an alias of `TensorFlow` Class is a good idea:
 public typealias TF = TensorFlow
 ```
@@ -111,7 +111,7 @@ public typealias TF = TensorFlow
 ⚠️NOTE⚠️ Prior to use **ANY ACTUAL FUNCTIONS** of Perfect TensorFlow framework, `TF.Open()` must be called first:
 
 ``` swift
-// this action will load all api functions defined 
+// this action will load all api functions defined
 // in /usr/local/lib/libtensorflow.so
 try TF.Open()
 ```

README.zh_CN.md

@@ -81,7 +81,7 @@ Sources
 
 Perfect-TensorFlow 是基于其C语言函数库基础上的，简单说来就是您的计算机上在运行时必须安装 `libtensorflow.so`动态链接库。
 
-本项目包含了一个用于快速安装该链接库 CPU v1.2.0版本的脚本，默认安装路径为`/usr/local/lib/libtensorflow.so`。您可以根据平台要求下载并运行 [`install.sh`](https://github.com/PerfectlySoft/Perfect-TensorFlow/blob/master/install.sh)。运行该脚本之前请确定 `wget`已经安装到您的计算机上；如果还没装，请首先用`brew install wget`（适用于macOS）或者 `sudo apt-get install wget` （适用于Ubuntu）命令安装`wget`组件。
+本项目包含了一个用于快速安装该链接库 CPU v1.2.1版本的脚本，默认安装路径为`/usr/local/lib/libtensorflow.so`。您可以根据平台要求下载并运行 [`install.sh`](https://github.com/PerfectlySoft/Perfect-TensorFlow/blob/master/install.sh)。运行该脚本之前请确定 `wget`已经安装到您的计算机上；如果还没装，请首先用`brew install wget`（适用于macOS）或者 `sudo apt-get install wget` （适用于Ubuntu）命令安装`wget`组件。
 
 
 更多的安装选项，如需要在同一台计算机上同时安装CPU/GPU或者多个不同版本，请参考官网网站： [Installing TensorFlow for C](https://www.tensorflow.org/install/install_c)

Sources/PerfectTensorFlow/APILoader.swift

@@ -695,6 +695,42 @@ public class TFLib {
   /// On failure, output_values[] contains NULLs.
   public static var SessionRun: @convention(c) (OpaquePointer, UnsafePointer<TF_Buffer>?, UnsafePointer<TF_Output>?, UnsafePointer<OpaquePointer>?, Int32, UnsafePointer<TF_Output>?, UnsafeMutablePointer<OpaquePointer>?, Int32, UnsafePointer<OpaquePointer>?, Int32, UnsafeMutablePointer<TF_Buffer>?, OpaquePointer) -> Void = { _, _, _, _, _, _, _, _, _, _, _, _ in }
 
+  /// Lists all devices in a TF_Session.
+  ///
+  /// Caller takes ownership of the returned TF_DeviceList* which must eventually
+  /// be freed with a call to TF_DeleteDeviceList.
+  public static var SessionListDevices: @convention(c) (OpaquePointer, OpaquePointer) -> OpaquePointer? = { _, _ in return nil }
+
+  /// Deallocates the device list.
+  public static var DeleteDeviceList: @convention(c) (OpaquePointer) -> Void = { _ in}
+
+  /// Counts the number of elements in the device list.
+  public static var DeviceListCount: @convention(c) (OpaquePointer) -> Int32 = { _ in return 0 }
+
+  /// Retrieves the full name of the device (e.g. /job:worker/replica:0/...)
+  /// The return value will be a pointer to a null terminated string. The caller
+  /// must not modify or delete the string. It will be deallocated upon a call to
+  /// TF_DeleteDeviceList.
+  ///
+  /// If index is out of bounds, an error code will be set in the status object,
+  /// and a null pointer will be returned.
+  public static var DeviceListName: @convention(c) (OpaquePointer, Int32, OpaquePointer) -> UnsafePointer<CChar>? = { _, _, _ in return nil }
+
+  /// Retrieves the type of the device at the given index.
+  ///
+  /// The caller must not modify or delete the string. It will be deallocated upon
+  /// a call to TF_DeleteDeviceList.
+  ///
+  /// If index is out of bounds, an error code will be set in the status object,
+  /// and a null pointer will be returned.
+  public static var DeviceListType: @convention(c) (OpaquePointer, Int32, OpaquePointer) -> UnsafePointer<CChar>? = { _, _, _ in return nil }
+
+  /// Retrieve the amount of memory associated with a given device.
+  ///
+  /// If index is out of bounds, an error code will be set in the status object,
+  /// and -1 will be returned.
+  public static var DeviceListMemoryBytes: @convention(c) (OpaquePointer, Int32, OpaquePointer) -> Int64 = { _, _, _ in return 0 }
+
   /// Set up the graph with the intended feeds (inputs) and fetches (outputs) for a
   /// sequence of partial run calls.
   ///
@@ -758,7 +794,13 @@ public class TFLib {
       throw Panic.DLL(reason: String(cString: dlerror()))
     }//end lib
     libDLL = lib
-    // AddGradients = try LoadFunction(lib, "TF_AddGradients")
+    // SessionListDevices = try LoadFunction(lib, "TF_SessionListDevices")
+    // DeleteDeviceList = try LoadFunction(lib, "TF_DeleteDeviceList")
+    // DeviceListCount = try LoadFunction(lib, "TF_DeviceListCount")
+    // DeviceListName = try LoadFunction(lib, "TF_DeviceListName")
+    // DeviceListType = try LoadFunction(lib, "TF_DeviceListType")
+    // DeviceListMemoryBytes = try LoadFunction(lib, "TF_DeviceListMemoryBytes")
+    AddGradients = try LoadFunction(lib, "TF_AddGradients")
     SetAttrValueProto = try LoadFunction(lib, "TF_SetAttrValueProto")
     GetAllOpList = try LoadFunction(lib, "TF_GetAllOpList")
     DeleteLibraryHandle = try LoadFunction(lib, "TF_DeleteLibraryHandle")

Sources/PerfectTensorFlow/PerfectTensorFlow.swift

@@ -1930,6 +1930,33 @@ public class TensorFlow {
 
     let session: OpaquePointer
 
+    /// return all devices for this session in a dictionary.
+    /// each key in the dictionary represents a device name,
+    /// and the value is a tuple of device type and its memory size, in bytes
+    public var devices: [String:(`type`:String, memory: Int64)] {
+      var dev: [String:(`type`:String, memory: Int64)] = [:]
+
+      guard let _ = TFLib.libDLL, let status = try? Status(),
+        let list = TFLib.SessionListDevices(session, status.status),
+        status.code == .OK else { return dev }
+
+      defer { TFLib.DeleteDeviceList(list) }
+      for i in 0 ..< TFLib.DeviceListCount(list) {
+        if let nm = TFLib.DeviceListName(list, i, status.status),
+          status.code == .OK,
+          let tp = TFLib.DeviceListType(list, i, status.status),
+          status.code == .OK {
+          let mem = TFLib.DeviceListMemoryBytes(list, i, status.status)
+          if status.code == .OK,
+            let dname = String(utf8String: nm),
+            let dtype = String(utf8String: tp) {
+            dev[dname] = (type: dtype, memory: mem)
+          }
+        }
+      }
+      return dev
+    }
+
     /// Return a new execution session with the associated graph, or NULL on error. *graph must be a valid graph (not deleted or nullptr). This function will prevent the graph from being deleted until TF_DeleteSession() is called. Does not take ownership of opts.
     /// - parameters:
     ///   - graph: the parent graph

Sources/TensorFlowAPI/include/TensorFlowAPI.h

@@ -124,6 +124,7 @@ typedef struct TF_WhileParams {
 // API for driving Graph execution.
 
 typedef struct TF_Session TF_Session;
+typedef struct TF_DeviceList TF_DeviceList;
 
 // Load plugins containing custom ops and kernels
 

Tests/PerfectTensorFlowTests/PerfectTensorFlowTests.swift

@@ -181,13 +181,20 @@ class PerfectTensorFlowTests: XCTestCase {
       }
 
       let n0 = def0.node
-      let n1 = def1.node // n1 may have two more operations: M1/M2, but gradients are the same
+      let n1 = def1.node
+      XCTAssertEqual(n0.count, n1.count)
       for i in 0 ..< n0.count {
-        let a = n0[i]
-        let b = n1[i]
-        print(a.name, b.name)
-        XCTAssertEqual(a, b)
+        let n = n0[i]
+        let m = n1[i]
+        XCTAssertEqual(n.name, m.name)
+        XCTAssertEqual(n.op, m.op)
+        for key in n.attr.keys {
+          let v = n.attr[key]
+          let w = m.attr[key]
+          XCTAssertEqual(v, w)
+        }
       }
+
     }
     public func buildSuccessGraph() throws ->
       (graph: TF.Graph, inputs:[TF.Output], outputs: [TF.Output])
@@ -205,12 +212,12 @@ class PerfectTensorFlowTests: XCTestCase {
       //        |         |
       //      Const_0    Const_1
       //
-      let srcA:[Float] = [1,2,3,4]
-      let srcB:[Float] = [1,0,0,1]
+      let srcA:[[Float]] = [[1,2],[3,4]]
+      let srcB:[[Float]] = [[1,0],[0,1]]
 
       // create tensors for these matrices
-      let tA = try TF.Tensor.Array(dimensions: [2,2], value: srcA)
-      let tB = try TF.Tensor.Array(dimensions: [2,2], value: srcB)
+      let tA = try TF.Tensor.Matrix(srcA)
+      let tB = try TF.Tensor.Matrix(srcB)
 
       let g = try TF.Graph()
       // adding tensors to graph
@@ -247,12 +254,12 @@ class PerfectTensorFlowTests: XCTestCase {
       //        |         |
       //        |         |
       //      Const_0   Const_1
-      let srcA:[Float] = [1,2,3,4]
-      let srcB:[Float] = [1,0,0,1]
+      let srcA:[[Float]] = [[1,2],[3,4]]
+      let srcB:[[Float]] = [[1,0],[0,1]]
 
       // create tensors for these matrices
-      let tA = try TF.Tensor.Array(dimensions: [2,2], value: srcA)
-      let tB = try TF.Tensor.Array(dimensions: [2,2], value: srcB)
+      let tA = try TF.Tensor.Matrix(srcA)
+      let tB = try TF.Tensor.Matrix(srcB)
 
       let g = try TF.Graph()
       // adding tensors to graph
@@ -262,8 +269,8 @@ class PerfectTensorFlowTests: XCTestCase {
 
       let C: TF.Operation
       if providingDX {
-        let srcC: [Float] = [1, 1, 1, 1]
-        let tC = try TF.Tensor.Array(dimensions: [2,2], value: srcC)
+        let srcC: [[Float]] = [[1, 1], [1, 1]]
+        let tC = try TF.Tensor.Matrix(srcC)
         C = try g.const(tensor: tC, name: "GradInputs")
       } else {
         C = try g.OnesLike(inp: M, name: "OnesLike")
@@ -276,8 +283,8 @@ class PerfectTensorFlowTests: XCTestCase {
 
     public func addGradients(_ providingDX: Bool, graph: TF.Graph, inputs: [TF.Output], outputs: [TF.Output]) throws -> [TF.Output] {
       if providingDX {
-        let dxArray:[Float] = [1,1,1,1]
-        let dxValue = try TF.Tensor.Array(dimensions: [2,2], value: dxArray)
+        let dxArray:[[Float]] = [[1, 1], [1, 1]]
+        let dxValue = try TF.Tensor.Matrix(dxArray)
         let dx = try graph.const(tensor: dxValue, name: "GradInputs").asOutput(0)
         return try graph.addGradients(y: outputs, x: inputs, dx: [dx])
       } else {
@@ -1181,7 +1188,7 @@ class PerfectTensorFlowTests: XCTestCase {
   }
 
   func testVersion() {
-    XCTAssertEqual(TF.Version, "1.2.0")
+    XCTAssertEqual(TF.Version, "1.2.1")
   }
 
   func testSize() {

install.sh

@@ -1,6 +1,7 @@
 OSABR=$(echo $(uname)|tr '[:upper:]' '[:lower:]')
 DWN=/tmp/libtensorflow.tgz
-URL=https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-$OSABR-x86_64-1.2.0.tar.gz
+VERSION=1.2.1
+URL=https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-$OSABR-x86_64-$VERSION.tar.gz
 echo $URL
 wget $URL -O $DWN
 sudo tar xvf $DWN -C /usr/local ./lib/libtensorflow.so

test.sh

@@ -1,17 +1,18 @@
 # This script is for CI Server
+VERSION=1.2.1
 echo 'Clean Temp Files'
 rm -rf /tmp/testdata
 echo 'Unzip test pack'
 tar xzf testpack.tgz -C /tmp/
 if  [[ $OSTYPE =~ darwin* ]]; then
 	echo 'get darwin library'
-	curl https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.2.0.tar.gz -o /tmp/testdata/darwin.lib.tgz
+	curl https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-$VERSION.tar.gz -o /tmp/testdata/darwin.lib.tgz
 	mkdir /tmp/testdata/darwin
 	echo 'expand darwin library'
 	tar xzf /tmp/testdata/darwin.lib.tgz -C /tmp/testdata/darwin
 else
 	echo 'get linux library'
-	curl https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.2.0.tar.gz -o /tmp/testdata/linux.lib.tgz
+	curl https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-$VERSION.tar.gz -o /tmp/testdata/linux.lib.tgz
 	mkdir /tmp/testdata/linux
 	echo 'expand linux library'
 	tar xzf /tmp/testdata/linux.lib.tgz -C /tmp/testdata/linux