Skip to content
This repository has been archived by the owner on Mar 12, 2020. It is now read-only.

Commit

Permalink
Reimplementing with Tensorflow.NET in progress
Browse files Browse the repository at this point in the history
  • Loading branch information
Deepak Kumar committed Apr 2, 2019
1 parent dcef16e commit 8c789fe
Show file tree
Hide file tree
Showing 7 changed files with 234 additions and 70 deletions.
6 changes: 5 additions & 1 deletion Backends/SiaNet.Backend.ArrayFire/Backend/SiaNetBackend.cs
View file
Original file line number Diff line number Diff line change
Expand Up @@ -642,7 +642,7 @@ public Tensor L2Normalize(Tensor x, int axis = -1)

public Tensor RandomBernoulli(long[] shape, float p)
{
//shape = shape.Reverse().ToArray();
shape = shape.Reverse().ToArray();
var result = RandomUniform(shape, 0, 1);
result = result > p;
return result;
Expand Down Expand Up @@ -707,6 +707,10 @@ private int CorrDim(int dimCount, int dim)
break;
}
}
else
{
dim = dimCount - dim - 1;
}

return dim;
}
Expand Down
132 changes: 114 additions & 18 deletions Backends/SiaNet.Backend.CNTK/SiaNetBackend.cs
View file
Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,9 @@ private Variable In(Tensor x)

private Variable In(float value, params long[] shape)
{
return new Parameter(BackendUtil.CastShapeInt(shape), CNTK.DataType.Float, value);
shape = ShiftShapeN(shape);

return new Parameter(BackendUtil.CastShapeInt(shape.ToArray()), CNTK.DataType.Float, value);
}

private NDArrayTensor Out(Variable x)
Expand Down Expand Up @@ -63,11 +65,17 @@ public Tensor Add(float a, Tensor b)

public Tensor Argmax(Tensor x, int dim = -1)
{
if (dim < 0)
dim = CorrDim(x.DimCount, dim);

return Out(C.Argmax(In(x), new Axis(dim)));
}

public Tensor Argmin(Tensor x, int dim = -1)
{
if (dim < 0)
dim = CorrDim(x.DimCount, dim);

return Out(C.Argmin(In(x), new Axis(dim)));
}

Expand Down Expand Up @@ -115,7 +123,18 @@ public Tensor CreateVariable(float[] data, long[] shape, string name = "")
{
var arr = new CNTK.NDArrayView(BackendUtil.CastShapeInt(shape), data, DeviceManager.Current);
var v = new CNTK.Variable(BackendUtil.CastShapeInt(shape), VariableKind.Parameter, CNTK.DataType.Float, arr, false, new AxisVector(), false, name, name);
return Out(v);
Tensor result = null;

if (shape.Length == 2)
result = Transpose(Out(v), 1, 0);
else if (shape.Length == 3)
result = Transpose(Out(v), 1, 2, 0);
else if (shape.Length == 4)
result = Transpose(Out(v), 1, 2, 3, 0);
else
result = Out(v);

return result;
}

public Tensor Diag(Tensor x)
Expand Down Expand Up @@ -250,7 +269,8 @@ public Engine.DataType GetDataType(Tensor x)

public long[] GetShape(Tensor x)
{
return Array.ConvertAll(In(x).Shape.Dimensions.ToArray(), i => (long)i);
var shape = ShiftShapeN(In(x).Shape.Dimensions.ToArray());
return Array.ConvertAll(shape.ToArray(), i => (long)i);
}

public Tensor GreaterThan(Tensor a, Tensor b)
Expand Down Expand Up @@ -346,13 +366,17 @@ public float Max(Tensor x)

public Tensor Max(Tensor x, int dim)
{
dim = dim < 0 ? x.DimCount + dim : dim;
if (dim < 0)
dim = CorrDim(x.DimCount, dim);

return Out(C.ReduceMax(In(x), new Axis(dim)));
}

public Tensor Max(Tensor x, params int[] dim)
public Tensor Max(Tensor x, params int[] dims)
{
foreach (var item in dim)
dims = dims.Reverse().ToArray();

foreach (var item in dims)
{
x = Max(x, item);
}
Expand All @@ -377,13 +401,15 @@ public float Mean(Tensor x)

public Tensor Mean(Tensor x, int dim)
{
dim = dim < 0 ? x.DimCount + dim : dim;
if (dim < 0)
dim = CorrDim(x.DimCount, dim);
return Out(C.ReduceMean(In(x), new Axis(dim)));
}

public Tensor Mean(Tensor x, params int[] dim)
public Tensor Mean(Tensor x, params int[] dims)
{
foreach (var item in dim)
dims = dims.Reverse().ToArray();
foreach (var item in dims)
{
x = Mean(x, item);
}
Expand All @@ -398,17 +424,21 @@ public float Min(Tensor x)

public Tensor Min(Tensor x, int dim)
{
dim = dim < 0 ? x.DimCount + dim : dim;
if (dim < 0)
dim = CorrDim(x.DimCount, dim);

return Out(C.ReduceMin(In(x), new Axis(dim)));
}

public Tensor Min(Tensor x, params int[] dim)
public Tensor Min(Tensor x, params int[] dims)
{
foreach (var item in dim)
dims = dims.Reverse().ToArray();
foreach (var item in dims)
{
x = Min(x, item);
}


return x;
}

Expand Down Expand Up @@ -475,6 +505,7 @@ public Tensor RandomUniform(long[] shape, float min, float max, int? seed = null

public Tensor Reshape(Tensor x, params long[] shape)
{
shape = shape.Reverse().ToArray();
return Out(C.Reshape(In(x), BackendUtil.CastShapeInt(shape)));
}

Expand Down Expand Up @@ -522,13 +553,13 @@ public Tensor SliceCols(Tensor x, long start, long end)
{
end = end + 1;
var t = C.Transpose(In(x));
return Out(C.Transpose(C.Slice(t, AxisVector.Repeat(new Axis(1), 1), IntVector.Repeat((int)start, 1), IntVector.Repeat((int)end, 1))));
return Out(C.Slice(In(x), AxisVector.Repeat(new Axis(0), 1), IntVector.Repeat((int)start, 1), IntVector.Repeat((int)end, 1)));
}

public Tensor SliceRows(Tensor x, long start, long end)
{
end = end + 1;
return Out(C.Slice(In(x), AxisVector.Repeat(new Axis(0), 1), IntVector.Repeat((int)start, 1), IntVector.Repeat((int)end, 1)));
return Out(C.Slice(In(x), AxisVector.Repeat(new Axis(x.DimCount - 1), 1), IntVector.Repeat((int)start, 1), IntVector.Repeat((int)end, 1)));
}

public Tensor Softmax(Tensor x, int axis = -1)
Expand Down Expand Up @@ -575,13 +606,16 @@ public float Sum(Tensor x)

public Tensor Sum(Tensor x, int dim)
{
dim = dim < 0 ? x.DimCount + dim : dim;
if (dim < 0)
dim = CorrDim(x.DimCount, dim);

return Out(C.ReduceSum(In(x), new Axis(dim)));
}

public Tensor Sum(Tensor x, params int[] dim)
public Tensor Sum(Tensor x, params int[] dims)
{
foreach (var item in dim)
dims = dims.Reverse().ToArray();
foreach (var item in dims)
{
x = Sum(x, item);
}
Expand All @@ -601,7 +635,21 @@ public Tensor Tanh(Tensor x)

public Tensor Tile(Tensor x, int n, int axis = 0)
{
return x;
if (axis < 0)
axis = x.DimCount + axis;

uint[] dims = new uint[x.DimCount];
for (int i = 0; i < dims.Length; i++)
{
if (i == axis)
dims[i] = (uint)n;
else
dims[i] = 1;
}

dims = dims.Reverse().ToArray();

return Out(C.Splice(VariableVector.Repeat(In(x), n), new Axis(axis)));
}

public Tensor Transpose(Tensor x)
Expand All @@ -614,6 +662,8 @@ public Tensor Transpose(Tensor x, params int[] dims)
if (dims.Length != x.DimCount)
throw new InvalidOperationException("The number of permutation indices must equal the number of tensor dimensions");

dims = dims.Select(i => (dims.Length - i - 1)).Reverse().ToArray();

var result = In(x);
foreach (var swap in SwapsForPermutation(dims))
{
Expand Down Expand Up @@ -660,5 +710,51 @@ public ActivationFunc GetActFunc()
{
return new SiaNetActivations(this);
}

private int CorrDim(int dimCount, int dim)
{
if (dim < 0)
{
switch (dim)
{
case 0:
dim = dimCount - 1;
break;
default:
dim = dim - 1;
break;
}
}
else
{
dim = dimCount - dim - 1;
}

return dim;
}

private long[] ShiftShapeN(params long[] shape)
{
if (shape.Length == 1)
return shape;

var n = shape.Last();
var list = shape.ToList();
list.RemoveAt(shape.Length - 1);
list.Insert(0, n);
return list.ToArray();
}

private int[] ShiftShapeN(params int[] shape)
{
if (shape.Length == 1)
return shape;

var n = shape.Last();
var list = shape.ToList();
list.RemoveAt(shape.Length - 1);
list.Insert(0, n);
return list.ToArray();
}
}
}
2 changes: 1 addition & 1 deletion Backends/SiaNet.Backend.TensorFlow/SiaNet.Backend.TensorFlow.csproj
View file
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
</PropertyGroup>

<ItemGroup>
<PackageReference Include="TensorFlow.NET" Version="0.5.1" />
<PackageReference Include="TensorFlow.NET" Version="0.5.2" />
</ItemGroup>

<ItemGroup>
Expand Down
Loading

0 comments on commit 8c789fe

Please sign in to comment.