Merge branch 'master' of https://github.com/tensorflow/swift-apis into separable-conv

Author: Shashi456

.swift-format

@@ -0,0 +1,14 @@
+{
+    "version": 1,
+    "lineLength": 100,
+    "indentation": {
+        "spaces": 4
+    },
+    "maximumBlankLines": 1,
+    "respectsExistingLineBreaks": true,
+    "blankLineBetweenMembers": {
+        "ignoreSingleLineProperties": true
+    },
+    "lineBreakBeforeControlFlowKeywords": false,
+    "lineBreakBeforeEachArgument": false
+}

Dockerfile

@@ -39,5 +39,30 @@ RUN echo "/usr/local/cuda-10.0/targets/x86_64-linux/lib/stubs" > /etc/ld.so.conf
 # Print out swift version for better debugging for toolchain problems
 RUN /swift-tensorflow-toolchain/usr/bin/swift --version
 
+# Clean out existing artifacts.
+# TODO: move into bash scripts...
+RUN rm /swift-tensorflow-toolchain/usr/lib/swift/linux/x86_64/TensorFlow.swiftinterface
+RUN rm /swift-tensorflow-toolchain/usr/lib/swift/linux/x86_64/TensorFlow.swiftdoc
+RUN rm /swift-tensorflow-toolchain/usr/lib/swift/linux/x86_64/TensorFlow.swiftmodule
+RUN rm /swift-tensorflow-toolchain/usr/lib/swift/linux/libswiftTensorFlow.so
+
 # Run SwiftPM tests
 RUN /swift-tensorflow-toolchain/usr/bin/swift test
+
+# Install into toolchain
+# TODO: Unify this with testing. (currently there is a demangling bug).
+RUN /swift-tensorflow-toolchain/usr/bin/swift build -Xswiftc -module-link-name -Xswiftc TensorFlow
+RUN cp /swift-apis/.build/debug/TensorFlow.swiftmodule /swift-tensorflow-toolchain/usr/lib/swift/linux/x86_64/
+RUN cp /swift-apis/.build/debug/libTensorFlow.so /swift-tensorflow-toolchain/usr/lib/swift/linux/
+
+WORKDIR /
+RUN git clone https://github.com/tensorflow/swift-models.git
+RUN git clone https://github.com/fastai/fastai_dev.git
+
+WORKDIR /swift-models
+
+RUN /swift-tensorflow-toolchain/usr/bin/swift build
+
+WORKDIR /fastai_dev/swift/FastaiNotebook_07_batchnorm
+
+RUN /swift-tensorflow-toolchain/usr/bin/swift build

Package.swift

@@ -22,13 +22,21 @@ let package = Package(
     products: [
         .library(
             name: "TensorFlow",
+            type: .dynamic,
             targets: ["TensorFlow"]),
     ],
     dependencies: [],
     targets: [
         .target(
             name: "TensorFlow",
             dependencies: []),
+        .target(
+            name: "Experimental",
+            dependencies: [],
+            path: "Sources/third_party/Experimental"),
+        .testTarget(
+            name: "ExperimentalTests",
+            dependencies: ["Experimental"]),
         .testTarget(
             name: "TensorFlowTests",
             dependencies: ["TensorFlow"]),

README.md

@@ -57,7 +57,7 @@ for _ in 0..<1000 {
         print("Loss: \(loss)")
         return loss
     }
-    optimizer.update(&classifier.allDifferentiableVariables, along: 𝛁model)
+    optimizer.update(&classifier, along: 𝛁model)
 }
 ```
 
@@ -69,7 +69,7 @@ for _ in 0..<1000 {
     let (loss, 𝛁ŷ) = ŷ.valueWithGradient { ŷ in softmaxCrossEntropy(logits: ŷ, labels: y) }
     print("Model output: \(ŷ), Loss: \(loss)")
     let 𝛁model = backprop(𝛁ŷ)
-    optimizer.update(&classifier.allDifferentiableVariables, along: 𝛁model)
+    optimizer.update(&classifier, along: 𝛁model)
 }
 ```
 

Sources/TensorFlow/BackwardsCompatibility.swift

@@ -15,7 +15,7 @@
 // TODO: Remove this file after 0.4.
 
 public extension Tensor where Scalar == Int32 {
-    /// Creates a tensor with the specified shape, randomly sampling scalar values from a discrete 
+    /// Creates a tensor with the specified shape, randomly sampling scalar values from a discrete
     /// uniform distribution.
     ///
     /// - Parameters:
@@ -40,7 +40,7 @@ public extension Tensor where Scalar == Int32 {
         self.init(shape: shape, scalars: scalars)
     }
 
-    /// Creates a tensor with the specified shape, randomly sampling scalar values from a discrete 
+    /// Creates a tensor with the specified shape, randomly sampling scalar values from a discrete
     /// uniform distribution, using the default random number generator.
     ///
     /// - Parameters:
@@ -63,7 +63,7 @@ public extension Tensor where Scalar == Int32 {
 
 public extension Tensor where Scalar: BinaryFloatingPoint,
                               Scalar.RawSignificand: FixedWidthInteger {
-    /// Creates a tensor with the specified shape, randomly sampling scalar values from a uniform 
+    /// Creates a tensor with the specified shape, randomly sampling scalar values from a uniform
     /// distribution between `lowerBound` and `upperBound`.
     ///
     /// - Parameters:
@@ -89,7 +89,7 @@ public extension Tensor where Scalar: BinaryFloatingPoint,
         self = (upperBound - lowerBound) * sample + lowerBound
     }
 
-    /// Creates a tensor with the specified shape, randomly sampling scalar values from a normal 
+    /// Creates a tensor with the specified shape, randomly sampling scalar values from a normal
     /// distribution.
     ///
     /// - Parameters:
@@ -128,7 +128,7 @@ public extension Tensor where Scalar: TensorFlowFloatingPoint {
         let uniform = Tensor(randomUniform: shape, generator: &generator)
         self = Tensor.glorot(fromStandardUniform: uniform, shape: shape)
     }
-    
+
     /// Performs Glorot normal initialization for the specified shape, creating a tensor by
     /// randomly sampling scalar values from a uniform distribution between `-limit` and `limit`,
     /// where limit is `sqrt(2 / (fanIn + fanOut))` and `fanIn`/`fanOut` represent the number of
@@ -200,7 +200,11 @@ public extension Conv1D where Scalar.RawSignificand: FixedWidthInteger {
     ///
     /// - Note: Use `init(filterShape:stride:padding:dilation:activation:seed:)` for faster random
     ///   initialization.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:stride:padding:dilation:activation:filterIntializer:biasInitializer:)`
+        instead.
+        """)
     init<G: RandomNumberGenerator>(
         filterShape: (Int, Int, Int),
         stride: Int = 1,
@@ -221,18 +225,22 @@ public extension Conv1D where Scalar.RawSignificand: FixedWidthInteger {
     }
 }
 
-public extension Conv1D {		
-    /// Creates a `Conv1D` layer with the specified filter shape, strides, padding, dilation and		
-    /// element-wise activation function. The filter tensor is initialized using Glorot uniform		
-    /// initialization with the specified seed. The bias vector is initialized with zeros.		
+public extension Conv1D {
+    /// Creates a `Conv1D` layer with the specified filter shape, strides, padding, dilation and
+    /// element-wise activation function. The filter tensor is initialized using Glorot uniform
+    /// initialization with the specified seed. The bias vector is initialized with zeros.
     ///
     /// - Parameters:
-    ///   - filterShape: The 3-D shape of the filter, representing	
+    ///   - filterShape: The 3-D shape of the filter, representing
     ///   - padding: The padding algorithm for convolution.
     ///   - dilation: The dilation factor for the temporal dimension.
     ///   - activation: The element-wise activation function.
     ///   - seed: The random seed for initialization. The default value is random.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:stride:padding:dilation:activation:filterIntializer:biasInitializer:)`
+        instead.
+        """)
     init(
         filterShape: (Int, Int, Int),
         stride: Int = 1,
@@ -271,7 +279,11 @@ public extension Conv2D {
     ///
     /// - Note: Use `init(filterShape:strides:padding:activation:seed:)` for faster random
     ///   initialization.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:dilations:activation:filterIntializer:biasInitializer:)`
+        instead.
+        """)
     init<G: RandomNumberGenerator>(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),
@@ -307,7 +319,11 @@ public extension Conv2D {
     ///     (dilation height, dilation width).
     ///   - activation: The element-wise activation function.
     ///   - seed: The random seed for initialization. The default value is random.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:dilations:activation:filterIntializer:biasInitializer:)`
+        instead.
+        """)
     init(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),
@@ -345,7 +361,10 @@ public extension Conv3D {
     ///
     /// - Note: Use `init(filterShape:strides:padding:activation:seed:)` for faster random
     ///   initialization.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init<G: RandomNumberGenerator>(
         filterShape: (Int, Int, Int, Int, Int),
         strides: (Int, Int, Int) = (1, 1, 1),
@@ -378,7 +397,10 @@ public extension Conv3D {
     ///   - padding: The padding algorithm for convolution.
     ///   - activation: The element-wise activation function.
     ///   - seed: The random seed for initialization. The default value is random.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init(
         filterShape: (Int, Int, Int, Int, Int),
         strides: (Int, Int, Int) = (1, 1, 1),
@@ -412,7 +434,10 @@ public extension TransposedConv2D {
     ///
     /// - Note: Use `init(filterShape:strides:padding:activation:seed:)` for faster random
     ///   initialization.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init<G: RandomNumberGenerator>(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),
@@ -443,7 +468,10 @@ public extension TransposedConv2D {
     ///   - padding: The padding algorithm for convolution.
     ///   - activation: The element-wise activation function.
     ///   - seed: The random seed for initialization. The default value is random.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),
@@ -476,7 +504,10 @@ public extension DepthwiseConv2D {
     ///
     /// - Note: Use `init(filterShape:strides:padding:activation:seed:)` for faster random
     ///   initialization.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init<G: RandomNumberGenerator>(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),
@@ -506,7 +537,10 @@ public extension DepthwiseConv2D {
     ///   - padding: The padding algorithm for convolution.
     ///   - activation: The element-wise activation function.
     ///   - seed: The random seed for initialization. The default value is random.
-    @available(*, deprecated, message: "This API will be removed after Swift for TensorFlow 0.4.")
+    @available(*, deprecated, message: """
+        This API will be removed after Swift for TensorFlow 0.4, please consider using
+        `init(filterShape:strides:padding:activation:filterIntializer:biasInitializer:)` instead.
+        """)
     init(
         filterShape: (Int, Int, Int, Int),
         strides: (Int, Int) = (1, 1),

Sources/TensorFlow/Bindings/EagerExecution.swift

@@ -68,10 +68,11 @@ internal struct TFE_Op: TFTensorOperation {
         let count = input._tensorHandleCount
         var buffer = UnsafeMutableBufferPointer<CTensorHandle>.allocate(capacity: Int(count))
         defer { buffer.deallocate() }
-        let pointer = UnsafeMutablePointer<OpaquePointer?>(buffer.baseAddress)
         input._unpackTensorHandles(into: buffer.baseAddress)
-        TFE_OpAddInputList(op, pointer, count, status)
-        // TODO: checkOk(status)
+        for i in 0..<Int(count) {
+            TFE_OpAddInput(op, buffer[i], status)
+            checkOk(status)
+        }
     }
 
     @inlinable @inline(__always)

Sources/TensorFlow/Bindings/EagerExecution.swift.gyb

@@ -68,10 +68,11 @@ internal struct TFE_Op: TFTensorOperation {
         let count = input._tensorHandleCount
         var buffer = UnsafeMutableBufferPointer<CTensorHandle>.allocate(capacity: Int(count))
         defer { buffer.deallocate() }
-        let pointer = UnsafeMutablePointer<OpaquePointer?>(buffer.baseAddress)
         input._unpackTensorHandles(into: buffer.baseAddress)
-        TFE_OpAddInputList(op, pointer, count, status)
-        // TODO: checkOk(status)
+        for i in 0..<Int(count) {
+            TFE_OpAddInput(op, buffer[i], status)
+            checkOk(status)
+        }
     }
 
     @inlinable @inline(__always)
@@ -271,7 +272,12 @@ internal struct TFE_Op: TFTensorOperation {
         _ name: String,
         _ value: (In) -> Out
     ) {
-        _tffunc(value).utf8CString.withUnsafeBufferPointer { buffer in
+        updateAttribute(name, _TensorFunctionPointer(name: _tffunc(value)))
+    }
+
+    @inlinable @inline(__always)
+    internal func updateAttribute(_ name: String, _ value: _TensorFunctionPointer) {
+        value.name.utf8CString.withUnsafeBufferPointer { buffer in
             // utf8CString is null-terminated; TFE_OpSetAttrFunctionName wants
             // non-null-terminated.
             TFE_OpSetAttrFunctionName(op, name, buffer.baseAddress, buffer.count - 1)

Sources/TensorFlow/Context.swift

@@ -66,6 +66,8 @@ public struct Context {
     internal var randomNumberGenerator: AnyRandomNumberGenerator =
         AnyRandomNumberGenerator(PhiloxRandomNumberGenerator(uint64Seed: UInt64(time(nil))))
 
+    internal var globalTensorCount: Int = 0
+
     /// Creates a context with default properties.
     public init() {}
 

Sources/TensorFlow/Core/DataTypes.swift

@@ -84,8 +84,7 @@ extension Int64: TensorFlowIndex {}
 public protocol TensorFlowFloatingPoint:
     TensorFlowScalar & BinaryFloatingPoint & Differentiable & ElementaryFunctions
     where Self.RawSignificand: FixedWidthInteger,
-          Self == Self.TangentVector,
-          Self == Self.AllDifferentiableVariables {}
+          Self == Self.TangentVector {}
 
 extension Float: TensorFlowFloatingPoint {}
 extension Double: TensorFlowFloatingPoint {}