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Oceania2018Oceania2018
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unify numpy dtype and tf dtype.
1 parent 9c2d5c4 commit 1142f38

19 files changed

Lines changed: 66 additions & 536 deletions

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‎src/TensorFlowNET.Core/Data/MnistModelLoader.cs‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -123,7 +123,7 @@ private NDArray ExtractImages(string file, int? limit = null)
123123

124124
bytestream.Read(buf, 0, buf.Length);
125125

126-
var data = np.frombuffer(buf, np.@byte);
126+
var data = np.frombuffer(buf, np.@byte.as_system_dtype());
127127
data = data.reshape((num_images, rows, cols, 1));
128128

129129
return data;
@@ -148,7 +148,7 @@ private NDArray ExtractLabels(string file, bool one_hot = false, int num_classes
148148

149149
bytestream.Read(buf, 0, buf.Length);
150150

151-
var labels = np.frombuffer(buf, np.uint8);
151+
var labels = np.frombuffer(buf, np.uint8.as_system_dtype());
152152

153153
if (one_hot)
154154
return DenseToOneHot(labels, num_classes);

‎src/TensorFlowNET.Core/NumPy/Implementation/NumPyImpl.Creation.cs‎

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,7 @@ namespace Tensorflow.NumPy
77
{
88
public partial class NumPyImpl
99
{
10-
public NDArray eye(int N, int? M = null, int k = 0, NumpyDType dtype = NumpyDType.Double)
10+
public NDArray eye(int N, int? M = null, int k = 0, TF_DataType dtype = TF_DataType.TF_DOUBLE)
1111
{
1212
if (!M.HasValue)
1313
M = N;
@@ -28,16 +28,16 @@ public NDArray eye(int N, int? M = null, int k = 0, NumpyDType dtype = NumpyDTyp
2828
diag_len = N + k;
2929
}
3030

31-
var diagonal_ = array_ops.ones(new TensorShape(diag_len), dtype: dtype.as_tf_dtype());
31+
var diagonal_ = array_ops.ones(new TensorShape(diag_len), dtype: dtype);
3232
var tensor = array_ops.matrix_diag(diagonal: diagonal_, num_rows: N, num_cols: M.Value, k: k);
3333
return new NDArray(tensor);
3434
}
3535

3636
public NDArray linspace<T>(T start, T stop, int num = 50, bool endpoint = true, bool retstep = false,
37-
NumpyDType dtype = NumpyDType.Double, int axis = 0)
37+
TF_DataType dtype = TF_DataType.TF_DOUBLE, int axis = 0)
3838
{
39-
var start_tensor = array_ops.constant(start, dtype: dtype.as_tf_dtype());
40-
var stop_tensor = array_ops.constant(stop, dtype: dtype.as_tf_dtype());
39+
var start_tensor = array_ops.constant(start, dtype: dtype);
40+
var stop_tensor = array_ops.constant(stop, dtype: dtype);
4141
var num_tensor = array_ops.constant(num);
4242
// var step_tensor = array_ops.constant(np.nan);
4343
Tensor result = null;

‎src/TensorFlowNET.Core/Numpy/IMemoryBlock.cs‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@ public interface IMemoryBlock
99
/// <summary>
1010
/// The size of a single item stored in <see cref="Address"/>.
1111
/// </summary>
12-
/// <remarks>Equivalent to <see cref="NumpyDType.SizeOf"/> extension.</remarks>
12+
/// <remarks>Equivalent to <see cref="TF_DataType.SizeOf"/> extension.</remarks>
1313
int ItemLength { get; }
1414

1515
/// <summary>
@@ -30,8 +30,8 @@ public interface IMemoryBlock
3030
long BytesLength { get; }
3131

3232
/// <summary>
33-
/// The <see cref="NumpyDType"/> of the type stored inside this memory block.
33+
/// The <see cref="TF_DataType"/> of the type stored inside this memory block.
3434
/// </summary>
35-
NumpyDType TypeCode { get; }
35+
TF_DataType TypeCode { get; }
3636
}
3737
}

‎src/TensorFlowNET.Core/Numpy/InfoOf.cs‎

Lines changed: 2 additions & 48 deletions
Original file line numberDiff line numberDiff line change
@@ -8,60 +8,14 @@ namespace Tensorflow.NumPy
88
public class InfoOf<T>
99
{
1010
public static readonly int Size;
11-
public static readonly NumpyDType NPTypeCode;
11+
public static readonly TF_DataType NPTypeCode;
1212
public static readonly T Zero;
1313
public static readonly T MaxValue;
1414
public static readonly T MinValue;
1515

1616
static InfoOf()
1717
{
18-
NPTypeCode = typeof(T).GetTypeCode();
19-
20-
switch (NPTypeCode)
21-
{
22-
case NumpyDType.Boolean:
23-
Size = 1;
24-
break;
25-
case NumpyDType.Char:
26-
Size = 2;
27-
break;
28-
case NumpyDType.Byte:
29-
Size = 1;
30-
break;
31-
case NumpyDType.Int16:
32-
Size = 2;
33-
break;
34-
case NumpyDType.UInt16:
35-
Size = 2;
36-
break;
37-
case NumpyDType.Int32:
38-
Size = 4;
39-
break;
40-
case NumpyDType.UInt32:
41-
Size = 4;
42-
break;
43-
case NumpyDType.Int64:
44-
Size = 8;
45-
break;
46-
case NumpyDType.UInt64:
47-
Size = 8;
48-
break;
49-
case NumpyDType.Single:
50-
Size = 4;
51-
break;
52-
case NumpyDType.Double:
53-
Size = 8;
54-
break;
55-
case NumpyDType.Decimal:
56-
Size = 16;
57-
break;
58-
case NumpyDType.String:
59-
break;
60-
case NumpyDType.Complex:
61-
default:
62-
Size = Marshal.SizeOf<T>();
63-
break;
64-
}
18+
Size = NPTypeCode.get_datatype_size();
6519
}
6620
}
6721
}

‎src/TensorFlowNET.Core/Numpy/NDArray.Creation.cs‎

Lines changed: 2 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -18,10 +18,8 @@ public partial class NDArray
1818

1919
public NDArray(Array value, Shape? shape = null) => _tensor = new EagerTensor(value, shape);
2020

21-
public NDArray(Shape shape, NumpyDType dtype = NumpyDType.Float)
22-
{
23-
Initialize(shape, dtype: dtype);
24-
}
21+
public NDArray(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
22+
=> _tensor = new EagerTensor(shape, dtype: dtype);
2523

2624
public NDArray(Tensor value, Shape? shape = null)
2725
{
@@ -45,11 +43,5 @@ public static NDArray Scalar<T>(T value) where T : unmanaged
4543
_ => throw new NotImplementedException("")
4644
};
4745
}
48-
49-
void Initialize(Shape shape, NumpyDType dtype = NumpyDType.Float)
50-
{
51-
// _tensor = tf.zeros(shape, dtype: dtype.as_tf_dtype());
52-
_tensor = new EagerTensor(shape, dtype: dtype.as_tf_dtype());
53-
}
5446
}
5547
}

‎src/TensorFlowNET.Core/Numpy/NDArray.cs‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@ namespace Tensorflow.NumPy
99
public partial class NDArray
1010
{
1111
Tensor _tensor;
12-
public NumpyDType dtype => _tensor.dtype.as_numpy_typecode();
12+
public TF_DataType dtype => _tensor.dtype;
1313
public ulong size => _tensor.size;
1414
public ulong dtypesize => _tensor.itemsize;
1515
public int ndim => _tensor.NDims;
@@ -40,7 +40,7 @@ public NDIterator<T> AsIterator<T>(bool autoreset = false) where T : unmanaged
4040
public T MoveNext<T>() => throw new NotImplementedException("");
4141
public NDArray reshape(Shape newshape) => new NDArray(_tensor, newshape);
4242
public NDArray astype(Type type) => throw new NotImplementedException("");
43-
public NDArray astype(NumpyDType type) => throw new NotImplementedException("");
43+
public NDArray astype(TF_DataType type) => throw new NotImplementedException("");
4444
public bool array_equal(NDArray rhs) => throw new NotImplementedException("");
4545
public NDArray ravel() => throw new NotImplementedException("");
4646
public void shuffle(NDArray nd) => throw new NotImplementedException("");

‎src/TensorFlowNET.Core/Numpy/Numpy.Creation.cs‎

Lines changed: 8 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -24,29 +24,29 @@ public static NDArray arange<T>(T start, T? end = null, T? step = null)
2424
where T : unmanaged
2525
=> new NDArray(tf.range(start, limit: end, delta: step));
2626

27-
public static NDArray empty(Shape shape, NumpyDType dtype = NumpyDType.Double)
28-
=> new NDArray(tf.zeros(shape, dtype: dtype.as_tf_dtype()));
27+
public static NDArray empty(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
28+
=> new NDArray(tf.zeros(shape, dtype: dtype));
2929

30-
public static NDArray eye(int N, int? M = null, int k = 0, NumpyDType dtype = NumpyDType.Double)
30+
public static NDArray eye(int N, int? M = null, int k = 0, TF_DataType dtype = TF_DataType.TF_DOUBLE)
3131
=> tf.numpy.eye(N, M: M, k: k, dtype: dtype);
3232

3333
public static NDArray full<T>(Shape shape, T fill_value)
3434
=> new NDArray(tf.fill(tf.constant(shape), fill_value));
3535

3636
public static NDArray linspace<T>(T start, T stop, int num = 50, bool endpoint = true, bool retstep = false,
37-
NumpyDType dtype = NumpyDType.Double, int axis = 0) where T : unmanaged
37+
TF_DataType dtype = TF_DataType.TF_DOUBLE, int axis = 0) where T : unmanaged
3838
=> tf.numpy.linspace(start, stop, num: num, endpoint: endpoint, retstep: retstep, dtype: dtype, axis: axis);
3939

4040
public static (NDArray, NDArray) meshgrid<T>(T x, T y, bool copy = true, bool sparse = false)
4141
=> tf.numpy.meshgrid(new[] { x, y }, copy: copy, sparse: sparse);
4242

43-
public static NDArray ones(Shape shape, NumpyDType dtype = NumpyDType.Double)
44-
=> new NDArray(tf.ones(shape, dtype: dtype.as_tf_dtype()));
43+
public static NDArray ones(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
44+
=> new NDArray(tf.ones(shape, dtype: dtype));
4545

4646
public static NDArray ones_like(NDArray a, Type dtype = null)
4747
=> throw new NotImplementedException("");
4848

49-
public static NDArray zeros(Shape shape, NumpyDType dtype = NumpyDType.Double)
50-
=> new NDArray(tf.zeros(shape, dtype: dtype.as_tf_dtype()));
49+
public static NDArray zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_DOUBLE)
50+
=> new NDArray(tf.zeros(shape, dtype: dtype));
5151
}
5252
}

‎src/TensorFlowNET.Core/Numpy/Numpy.cs‎

Lines changed: 20 additions & 42 deletions
Original file line numberDiff line numberDiff line change
@@ -15,46 +15,26 @@ public partial class np
1515
public static readonly Slice newaxis = new Slice(null, null, 1) { IsNewAxis = true };
1616

1717
// https://docs.scipy.org/doc/numpy-1.16.0/user/basics.types.html
18-
public static readonly Type bool_ = typeof(bool);
19-
public static readonly Type bool8 = bool_;
20-
public static readonly Type @bool = bool_;
21-
22-
public static readonly Type @char = typeof(char);
23-
24-
public static readonly Type @byte = typeof(byte);
25-
public static readonly Type uint8 = typeof(byte);
26-
public static readonly Type ubyte = uint8;
27-
28-
29-
public static readonly Type int16 = typeof(short);
30-
31-
public static readonly Type uint16 = typeof(ushort);
32-
33-
public static readonly Type int32 = typeof(int);
34-
35-
public static readonly Type uint32 = typeof(uint);
36-
37-
public static readonly Type int_ = typeof(long);
38-
public static readonly Type int64 = int_;
39-
public static readonly Type intp = int_; //TODO! IntPtr?
40-
public static readonly Type int0 = int_;
41-
42-
public static readonly Type uint64 = typeof(ulong);
43-
public static readonly Type uint0 = uint64;
44-
public static readonly Type @uint = uint64;
45-
46-
public static readonly Type float32 = typeof(float);
47-
48-
public static readonly Type float_ = typeof(double);
49-
public static readonly Type float64 = float_;
50-
public static readonly Type @double = float_;
51-
52-
public static readonly Type complex_ = typeof(Complex);
53-
public static readonly Type complex128 = complex_;
54-
public static readonly Type complex64 = complex_;
55-
public static readonly Type @decimal = typeof(decimal);
56-
57-
public static Type chars => throw new NotSupportedException("Please use char with extra dimension.");
18+
#region data type
19+
public static readonly TF_DataType @bool = TF_DataType.TF_BOOL;
20+
public static readonly TF_DataType @char = TF_DataType.TF_INT8;
21+
public static readonly TF_DataType @byte = TF_DataType.TF_INT8;
22+
public static readonly TF_DataType uint8 = TF_DataType.TF_UINT8;
23+
public static readonly TF_DataType ubyte = TF_DataType.TF_UINT8;
24+
public static readonly TF_DataType int16 = TF_DataType.TF_INT16;
25+
public static readonly TF_DataType uint16 = TF_DataType.TF_UINT16;
26+
public static readonly TF_DataType int32 = TF_DataType.TF_INT32;
27+
public static readonly TF_DataType uint32 = TF_DataType.TF_UINT32;
28+
public static readonly TF_DataType int64 = TF_DataType.TF_INT64;
29+
public static readonly TF_DataType uint64 = TF_DataType.TF_UINT64;
30+
public static readonly TF_DataType float32 = TF_DataType.TF_FLOAT;
31+
public static readonly TF_DataType float64 = TF_DataType.TF_DOUBLE;
32+
public static readonly TF_DataType @double = TF_DataType.TF_DOUBLE;
33+
public static readonly TF_DataType @decimal = TF_DataType.TF_DOUBLE;
34+
public static readonly TF_DataType complex_ = TF_DataType.TF_COMPLEX;
35+
public static readonly TF_DataType complex64 = TF_DataType.TF_COMPLEX64;
36+
public static readonly TF_DataType complex128 = TF_DataType.TF_COMPLEX128;
37+
#endregion
5838

5939
public static double nan => double.NaN;
6040
public static double NAN => double.NaN;
@@ -70,8 +50,6 @@ public partial class np
7050
public static double Infinity => double.PositiveInfinity;
7151
public static double infinity => double.PositiveInfinity;
7252

73-
74-
7553
public static bool array_equal(NDArray a, NDArray b)
7654
=> throw new NotImplementedException("");
7755

‎src/TensorFlowNET.Core/Numpy/NumpyDType.cs‎

Lines changed: 0 additions & 90 deletions
This file was deleted.

‎src/TensorFlowNET.Core/Operations/array_ops.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -224,7 +224,7 @@ private static TF_DataType _get_dtype_from_nested_lists<T>(IEnumerable<T> list_o
224224
dtype = t.dtype.as_base_dtype();
225225
break;
226226
case NDArray t:
227-
dtype = t.dtype.as_tf_dtype();
227+
dtype = t.dtype;
228228
break;
229229
}
230230

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