Merge pull request #306 from huningxin/fix_resample2d_sizes

Use unsigned long type for sizes option of resample2d

index.bs

@@ -2097,7 +2097,7 @@ enum MLInterpolationMode {
 dictionary MLResample2dOptions {
   MLInterpolationMode mode = "nearest-neighbor";
   sequence<float> scales;
-  sequence<long> sizes;
+  sequence<unsigned long> sizes;
   sequence<long> axes;
 };
 
@@ -2112,7 +2112,7 @@ partial interface MLGraphBuilder {
             - *mode*: an {{MLInterpolationMode}}. The interpolation algorithm used to fill the output tensor values.
                 If not set, it is assumed to be the *Nearest Neighbor* interpolation.
             - *scales*: a sequence of {{float}} of length 2. Each value represents the scaling factor used to scale in each spatial dimensions of input, [scale_height, scale_width]. If not set, the values are assumed to be [1.0, 1.0].
-            - *sizes*: a sequence of {{long}} of length 2. The target sizes for each spatial dimensions of input, [size_height, size_width]. When the target sizes are specified, the *options.scales* argument is ignored as the scaling factor values are derived from the target sizes of each spatial dimension of input.
+            - *sizes*: a sequence of {{unsigned long}} of length 2. The target sizes for each spatial dimensions of input, [size_height, size_width]. When the target sizes are specified, the *options.scales* argument is ignored as the scaling factor values are derived from the target sizes of each spatial dimension of input.
             - *axes*: a sequence of {{long}} of length 2. The two consecutive dimensions of the input tensor to which the interpolation algorithm applies. The valid values in the sequence are [0, 1], [1, 2] or [2, 3]. When not specified, the sequence is assumed to be [2, 3].
 
     **Returns:** an {{MLOperand}}. The output 4-D tensor.