fixes #37 general datatype for scalar

tensorboardX/x2num.py

@@ -8,7 +8,7 @@ def makenp(x, modality=None):
         if modality == 'IMG' and x.dtype == np.uint8:
             return x.astype(np.float32)/255.0
         return x
-    if isinstance(x, float) or isinstance(x, int):
+    if np.isscalar(x):
         return np.array([x])
     if 'torch' in str(type(x)):
         return pytorch_np(x, modality)

tests/test_numpy.py

@@ -0,0 +1,17 @@
+from tensorboardX import x2num
+import numpy as np
+def test_scalar():
+    res = x2num.makenp(1.1)
+    assert isinstance(res, np.ndarray) and res.shape == (1,)
+    res = x2num.makenp(1000000000000000000000)
+    assert isinstance(res, np.ndarray) and res.shape == (1,)
+    res = x2num.makenp(np.float16(1.00000087))
+    assert isinstance(res, np.ndarray) and res.shape == (1,)
+    res = x2num.makenp(np.float128(1.00008+9))
+    assert isinstance(res, np.ndarray) and res.shape == (1,)
+    res = x2num.makenp(np.int64(100000000000))
+    assert isinstance(res, np.ndarray) and res.shape == (1,)
+
+
+def test_make_grid():
+    pass