Skip to content

fix: More generic array cast #1257

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jun 22, 2024
Merged

fix: More generic array cast #1257

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
88 changes: 59 additions & 29 deletions src/TensorFlowNET.Core/Tensors/tensor_util.cs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ public static NDArray MakeNdarray(TensorProto tensor)

T[] ExpandArrayToSize<T>(IList<T> src)
{
if(src.Count == 0)
if (src.Count == 0)
{
return new T[0];
}
Expand All @@ -77,7 +77,7 @@ T[] ExpandArrayToSize<T>(IList<T> src)
var first_elem = src[0];
var last_elem = src[src.Count - 1];
T[] res = new T[num_elements];
for(long i = 0; i < num_elements; i++)
for (long i = 0; i < num_elements; i++)
{
if (i < pre) res[i] = first_elem;
else if (i >= num_elements - after) res[i] = last_elem;
Expand Down Expand Up @@ -121,7 +121,7 @@ T[] ExpandArrayToSize<T>(IList<T> src)
$"https://www.tensorflow.org/api_docs/python/tf/dtypes for supported TF dtypes.");
}

if(values.size == 0)
if (values.size == 0)
{
return np.zeros(shape, tensor_dtype);
}
Expand All @@ -135,23 +135,47 @@ T[] ExpandArrayToSize<T>(IList<T> src)
TF_DataType.TF_QINT32
};

private static TOut[,] ConvertArray2D<TIn, TOut>(TIn[,] inputArray, Func<TIn, TOut> converter)
private static Array ConvertArray<TOut>(Array inputArray, Func<object, TOut> converter)
{
var rows = inputArray.GetLength(0);
var cols = inputArray.GetLength(1);
var outputArray = new TOut[rows, cols];
if (inputArray == null)
throw new ArgumentNullException(nameof(inputArray));

for (var i = 0; i < rows; i++)
var elementType = typeof(TOut);
var lengths = new int[inputArray.Rank];
for (var i = 0; i < inputArray.Rank; i++)
{
for (var j = 0; j < cols; j++)
{
outputArray[i, j] = converter(inputArray[i, j]);
}
lengths[i] = inputArray.GetLength(i);
}

var outputArray = Array.CreateInstance(elementType, lengths);

FillArray(inputArray, outputArray, converter, new int[inputArray.Rank], 0);

return outputArray;
}

private static void FillArray<TIn, TOut>(Array inputArray, Array outputArray, Func<TIn, TOut> converter, int[] indices, int dimension)
{
if (dimension == inputArray.Rank - 1)
{
for (int i = 0; i < inputArray.GetLength(dimension); i++)
{
indices[dimension] = i;
var inputValue = (TIn)inputArray.GetValue(indices);
var convertedValue = converter(inputValue);
outputArray.SetValue(convertedValue, indices);
}
}
else
{
for (int i = 0; i < inputArray.GetLength(dimension); i++)
{
indices[dimension] = i;
FillArray(inputArray, outputArray, converter, indices, dimension + 1);
}
}
}

/// <summary>
/// Create a TensorProto, invoked in graph mode
/// </summary>
Expand All @@ -171,24 +195,30 @@ public static TensorProto make_tensor_proto(object values, TF_DataType dtype = T
var origin_dtype = values.GetDataType();
if (dtype == TF_DataType.DtInvalid)
dtype = origin_dtype;
else if(origin_dtype != dtype)
else if (origin_dtype != dtype)
{
var new_system_dtype = dtype.as_system_dtype();

values = values switch

if (dtype != TF_DataType.TF_STRING && dtype != TF_DataType.TF_VARIANT && dtype != TF_DataType.TF_RESOURCE)
{
if (values is Array arrayValues)
{
values = dtype switch
{
TF_DataType.TF_INT32 => ConvertArray(arrayValues, Convert.ToInt32),
TF_DataType.TF_FLOAT => ConvertArray(arrayValues, Convert.ToSingle),
TF_DataType.TF_DOUBLE => ConvertArray(arrayValues, Convert.ToDouble),
_ => values,
};
} else
{
values = Convert.ChangeType(values, new_system_dtype);
}

} else
{
long[] longValues when dtype == TF_DataType.TF_INT32 => longValues.Select(x => (int)x).ToArray(),
long[] longValues => values,
float[] floatValues when dtype == TF_DataType.TF_DOUBLE => floatValues.Select(x => (double)x).ToArray(),
float[] floatValues => values,
float[,] float2DValues when dtype == TF_DataType.TF_DOUBLE => ConvertArray2D(float2DValues, Convert.ToDouble),
float[,] float2DValues => values,
double[] doubleValues when dtype == TF_DataType.TF_FLOAT => doubleValues.Select(x => (float)x).ToArray(),
double[] doubleValues => values,
double[,] double2DValues when dtype == TF_DataType.TF_FLOAT => ConvertArray2D(double2DValues, Convert.ToSingle),
double[,] double2DValues => values,
_ => Convert.ChangeType(values, new_system_dtype),
};

}
dtype = values.GetDataType();
}

Expand Down Expand Up @@ -306,7 +336,7 @@ bool hasattr(Graph property, string attr)

if (tensor is EagerTensor eagerTensor)
{
if(tensor.dtype == tf.int64)
if (tensor.dtype == tf.int64)
return new Shape(tensor.ToArray<long>());
else
return new Shape(tensor.ToArray<int>());
Expand Down Expand Up @@ -481,7 +511,7 @@ bool hasattr(Graph property, string attr)
var d_ = new int[value.size];
foreach (var (index, d) in enumerate(value.ToArray<int>()))
d_[index] = d >= 0 ? d : -1;

ret = ret.merge_with(new Shape(d_));
}
return ret;
Expand Down