add old optimizer initializers back (#36)

Author: marcrasi

Sources/DeepLearning/Optimizer.swift

@@ -35,13 +35,11 @@ public class Adam<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
     public let decay: Scalar
 
     public init(
-        for _: __shared Model,
         learningRate: Scalar = 1e-3,
         beta1: Scalar = 0.9,
         beta2: Scalar = 0.999,
         epsilon: Scalar = 1e-8,
-        decay: Scalar = 0,
-        scalarType: Scalar.Type
+        decay: Scalar = 0
     ) {
         precondition(learningRate >= 0, "Learning rate must be non-negative")
         precondition(0 <= beta1 && beta1 <= 1, "Beta parameter must be between 0 and 1")
@@ -55,6 +53,23 @@ public class Adam<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
         self.decay = decay
     }
 
+    public convenience init(
+        for _: __shared Model,
+        learningRate: Scalar = 1e-3,
+        beta1: Scalar = 0.9,
+        beta2: Scalar = 0.999,
+        epsilon: Scalar = 1e-8,
+        decay: Scalar = 0,
+        scalarType: Scalar.Type
+    ) {
+        self.init(
+            learningRate: learningRate,
+            beta1: beta1,
+            beta2: beta2,
+            epsilon: epsilon,
+            decay: decay)
+    }
+
     private var step: Scalar = 0
     private var firstMoments = Model.AllDifferentiableVariables.zero
     private var secondMoments = Model.AllDifferentiableVariables.zero
@@ -84,12 +99,10 @@ public class RMSProp<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
     public let decay: Scalar
 
     public init(
-        for _: __shared Model,
         learningRate: Scalar = 0.001,
         rho: Scalar = 0.9,
         epsilon: Scalar = 1e-8,
-        decay: Scalar = 0,
-        scalarType: Scalar.Type
+        decay: Scalar = 0
     ) {
         precondition(learningRate >= 0, "Learning rate must be non-negative")
         precondition(rho >= 0, "Rho must be non-negative")
@@ -101,6 +114,17 @@ public class RMSProp<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
         self.decay = decay
     }
 
+    public convenience init(
+        for _: __shared Model,
+        learningRate: Scalar = 0.001,
+        rho: Scalar = 0.9,
+        epsilon: Scalar = 1e-8,
+        decay: Scalar = 0,
+        scalarType: Scalar.Type
+    ) {
+        self.init(learningRate: learningRate, rho: rho, epsilon: epsilon, decay: decay)
+    }
+
     private var step: Scalar = 0
     private var alpha = Model.AllDifferentiableVariables.zero
 
@@ -125,12 +149,10 @@ public class SGD<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
     public let nesterov: Bool
 
     public init(
-        for _: __shared Model,
         learningRate: Scalar = 0.01,
         momentum: Scalar = 0,
         decay: Scalar = 0,
-        nesterov: Bool = false,
-        scalarType: Scalar.Type
+        nesterov: Bool = false
     ) {
         precondition(learningRate >= 0, "Learning rate must be non-negative")
         precondition(momentum >= 0, "Momentum must be non-negative")
@@ -142,6 +164,17 @@ public class SGD<Model: Layer, Scalar: TensorFlowFloatingPoint>: Optimizer
         self.nesterov = nesterov
     }
 
+    public convenience init(
+        for _: __shared Model,
+        learningRate: Scalar = 0.01,
+        momentum: Scalar = 0,
+        decay: Scalar = 0,
+        nesterov: Bool = false,
+        scalarType: Scalar.Type
+    ) {
+        self.init(learningRate: learningRate, momentum: momentum, decay: decay, nesterov: nesterov)
+    }
+
     private var step: Scalar = 0
     private var velocity = Model.AllDifferentiableVariables.zero