public static NDArray StandardizeSingleArray(NDArray x)
{
if (x == null)
{
return(null);
}
else if (K.IsTensor(x))
{
var shape = x.Shape;
if (shape == null || shape[0] == 0)
{
throw new Exception(String.Format("When feeding symbolic tensors to a model, we expect thetensors to have a static batch size. Got tensor with shape: {0}", shape.ToString()));
}
return(x);
}
else if (x.Dimension == 1)
{
x = nd.ExpandDims(x, 1);
}
return(x);
}
public static NDArrayList StandardizeInputData(NDArrayList data, string[] names, Shape[] shapes = null, bool check_batch_axis = true, string exception_prefix = "", bool check_last_layer_shape = true)
{
if (names == null)
{
if (data != null && data.Length == 0)
{
throw new Exception("Error when checking model " + exception_prefix + ": expected no data");
}
return(new NDArrayList());
}
if (data == null)
{
return((from _ in Enumerable.Range(0, names.Length)
select new NDArray()).ToList());
}
data = (from x in data
select StandardizeSingleArray(x)).ToList();
if (data.Length != names.Length)
{
if (data[0].Shape != null)
{
throw new Exception("Error when checking model " + exception_prefix + ": the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see " + names.Length.ToString() + " array(s), but instead got the following list of " + data.Length.ToString());
}
else if (names.Length > 1)
{
throw new Exception("Error when checking model " + exception_prefix + ": you are passing a list as input to your model, but the model expects a list of " + names.Length.ToString());
}
}
// Check shapes compatibility.
if (shapes != null)
{
foreach (var i in Enumerable.Range(0, names.Length))
{
if (shapes[i] != null && !K.IsTensor(data[i]))
{
var data_shape = data[i].Shape;
var shape = shapes[i];
if (data[i].Dimension != shape.Dimension)
{
throw new Exception("Error when checking " + exception_prefix + ": expected " + names[i] + " to have " + shape.Dimension.ToString() + " dimensions, but got array with shape " + data_shape.ToString());
}
if (!check_batch_axis)
{
data_shape = data_shape[1];
shape = shape[1];
}
foreach (var _tup_1 in Enumerable.Zip(data_shape.Data, shape.Data, (d, s) => { return(d, s); }))
{
var dim = _tup_1.Item1;
var ref_dim = _tup_1.Item2;
if (ref_dim != dim && ref_dim > 0)
{
// ignore shape difference in last layer only if loss is
// multi_hot_sparse_categorical_crossentropy,
// last layer can only be dense or activation layer
if (!check_last_layer_shape && (names[i].ToLower().StartsWith("dense") || names[i].ToLower().StartsWith("activation")))
{
continue;
}
throw new Exception("Error when checking " + exception_prefix + ": expected " + names[i] + " to have shape " + shape.ToString() + " but got array with shape " + data_shape.ToString());
}
}
}
}
}
return(data);
}