Merge 00db8ec into b44c85d

concurrency.go

@@ -0,0 +1,22 @@
+package gorgonia
+
+import "runtime"
+
+const (
+	// defaultBlockSize indicates the default size to chunk an array.
+	defaultBlockSize = 64
+
+	// minParallelBlocks indicates how many blocks an array must be split up into
+	// before we decide to parallelize
+	minParallelBlocks = 4
+)
+
+// workersChan creates a channel that is limited by the number of processor cores.
+// To signal that a processor core is being used:
+// 	ch <- struct{}{}
+// When done:
+// 	<- ch
+func workersChan() chan struct{} { return make(chan struct{}, runtime.GOMAXPROCS(0)) }
+
+// calcBlocks calculuates the best number of blocks given a blocksize
+func calcBlocks(dim, blocksize int) int { return (dim + blocksize - 1) / blocksize }

const.go

@@ -77,6 +77,8 @@ const (
 	gradOnDeviceFail    = "Cannot get gradient of %v on %v"
 	makeValueFail       = "Unable to make value of %v with shape %v"
 	allocFail           = "Unable to allocate %v bytes on %v"
+
+	shapeMismatchErr = "Shape Mismatch. Expected %v. Got %v instead."
 )
 
 var empty struct{}

example_err_test.go

@@ -61,9 +61,9 @@ func Example_errorHandling() {
 	_ = nn2PlusWrong
 
 	// Output:
-	// nn: Softmax{-1}()(%9) :: Matrix float32
+	// nn: Softmax{-1, false}()(%9) :: Matrix float32
 	// An error occurs: Type inference error. Op: + false. Children: [Matrix float32, Matrix float64], OpType:Matrix a → Matrix a → Matrix a: Unable to unify while inferring type of + false: Unification Fail: float64 ~ float32 cannot be unified
-	// nn2: Softmax{-1}()(%9) :: Matrix float32
+	// nn2: Softmax{-1, false}()(%9) :: Matrix float32
 	// An error occurs (caught by recover()): Type inference error. Op: + false. Children: [Matrix float32, Matrix float64], OpType:Matrix a → Matrix a → Matrix a: Unable to unify while inferring type of + false: Unification Fail: float64 ~ float32 cannot be unified
 
 }

examples/convnet/main.go

@@ -203,6 +203,12 @@ func main() {
 	if err = m.fwd(x); err != nil {
 		log.Fatalf("%+v", err)
 	}
+
+	// Note: the correct losses should look like that
+	//
+	// The losses that are not commented out is used to test the stabilization function of Gorgonia.
+	//losses := G.Must(G.HadamardProd(G.Must(G.Neg(G.Must(G.Log(m.out)))), y))
+
 	losses := G.Must(G.Log(G.Must(G.HadamardProd(m.out, y))))
 	cost := G.Must(G.Mean(losses))
 	cost = G.Must(G.Neg(cost))