diff --git a/src/TensorFlowNET.Core/Operations/random_ops.cs b/src/TensorFlowNET.Core/Operations/random_ops.cs
index bd718768..c722c9c0 100644
--- a/src/TensorFlowNET.Core/Operations/random_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/random_ops.cs
@@ -80,7 +80,7 @@ namespace Tensorflow
}
public static Tensor random_uniform(Tensor shape,
- long minval = 0,
+ int minval = 0,
Tensor maxval = null,
TF_DataType dtype = TF_DataType.TF_FLOAT,
int? seed = null,
diff --git a/src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs b/src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs
index 48eddf3b..12422289 100644
--- a/src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs
+++ b/src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs
@@ -58,51 +58,18 @@ namespace Tensorflow
case NDArray value:
result = new[] { value };
break;
-#if _REGEN
- %types=["sbyte", "bool", "byte", "short", "ushort", "int", "uint", "long", "ulong", "float", "double", "Complex"]
- %foreach types%
- case #1 value:
- result = new[] { NDArray.Scalar(value) };
- break;
- %
-#else
- case sbyte value:
- result = new[] { NDArray.Scalar(value) };
- break;
case bool value:
result = new[] { NDArray.Scalar(value) };
break;
case byte value:
result = new[] { NDArray.Scalar(value) };
break;
- case short value:
- result = new[] { NDArray.Scalar(value) };
- break;
- case ushort value:
- result = new[] { NDArray.Scalar(value) };
- break;
case int value:
result = new[] { NDArray.Scalar(value) };
break;
- case uint value:
- result = new[] { NDArray.Scalar(value) };
- break;
- case long value:
- result = new[] { NDArray.Scalar(value) };
- break;
- case ulong value:
- result = new[] { NDArray.Scalar(value) };
- break;
case float value:
result = new[] { NDArray.Scalar(value) };
break;
- case double value:
- result = new[] { NDArray.Scalar(value) };
- break;
- case Complex value:
- result = new[] { NDArray.Scalar(value) };
- break;
-#endif
default:
break;
}
diff --git a/src/TensorFlowNET.Core/TensorFlow.Binding.csproj b/src/TensorFlowNET.Core/TensorFlow.Binding.csproj
index ea93f37d..031d2b10 100644
--- a/src/TensorFlowNET.Core/TensorFlow.Binding.csproj
+++ b/src/TensorFlowNET.Core/TensorFlow.Binding.csproj
@@ -60,7 +60,7 @@ https://tensorflownet.readthedocs.io
-
+
diff --git a/src/TensorFlowNET.Hub/MnistModelLoader.cs b/src/TensorFlowNET.Hub/MnistModelLoader.cs
index 4fdd69b6..82096452 100644
--- a/src/TensorFlowNET.Hub/MnistModelLoader.cs
+++ b/src/TensorFlowNET.Hub/MnistModelLoader.cs
@@ -116,7 +116,7 @@ namespace Tensorflow.Hub
throw new Exception($"Invalid magic number {magic} in MNIST image file: {file}");
var num_images = Read32(bytestream);
- num_images = limit == null ? num_images : Math.Min(num_images, (uint)limit);
+ num_images = limit == null ? num_images : Math.Min(num_images, (int)limit);
var rows = Read32(bytestream);
var cols = Read32(bytestream);
@@ -125,8 +125,8 @@ namespace Tensorflow.Hub
bytestream.Read(buf, 0, buf.Length);
- var data = np.frombuffer(buf, np.uint8);
- data = data.reshape((int)num_images, (int)rows, (int)cols, 1);
+ var data = np.frombuffer(buf, np.@byte);
+ data = data.reshape(num_images, rows, cols, 1);
return data;
}
@@ -144,7 +144,7 @@ namespace Tensorflow.Hub
throw new Exception($"Invalid magic number {magic} in MNIST label file: {file}");
var num_items = Read32(bytestream);
- num_items = limit == null ? num_items : Math.Min(num_items, (uint)limit);
+ num_items = limit == null ? num_items : Math.Min(num_items, (int)limit);
var buf = new byte[num_items];
@@ -174,11 +174,11 @@ namespace Tensorflow.Hub
return labels_one_hot;
}
- private uint Read32(FileStream bytestream)
+ private int Read32(FileStream bytestream)
{
var buffer = new byte[sizeof(uint)];
var count = bytestream.Read(buffer, 0, 4);
- return np.frombuffer(buffer, ">u4").Data()[0];
+ return np.frombuffer(buffer, ">u4").Data()[0];
}
}
}
diff --git a/src/TensorFlowNET.Hub/Tensorflow.Hub.csproj b/src/TensorFlowNET.Hub/Tensorflow.Hub.csproj
index abb80f67..640e1515 100644
--- a/src/TensorFlowNET.Hub/Tensorflow.Hub.csproj
+++ b/src/TensorFlowNET.Hub/Tensorflow.Hub.csproj
@@ -2,7 +2,7 @@
Tensorflow.Hub
netstandard2.0
- 0.0.5
+ 0.0.6
Kerry Jiang, Haiping Chen
SciSharp STACK
Apache 2.0
@@ -13,7 +13,8 @@
TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models.
SciSharp.TensorFlowHub
true
- Fix GetNextBatch() bug.
+ Fix GetNextBatch() bug.
+Change to NumSharp compact version.
https://avatars3.githubusercontent.com/u/44989469?s=200&v=4
TensorFlow.Hub
@@ -21,6 +22,6 @@
DEBUG;TRACE
-
+
\ No newline at end of file