[Util] fixes and doc for numpy_to_hls_code

src/finn/backend/fpgadataflow/utils.py

-import numpy as np
 import sys
-from finn.core.utils import pack_innermost_dim_as_hex_string
+
+import numpy as np
+
 from finn.core.datatype import DataType
+from finn.core.utils import pack_innermost_dim_as_hex_string
+
 
 def numpy_to_hls_code(ndarray, dtype, hls_var_name, pack_innermost_dim=True):
-    "Return C++ code representation of a numpy ndarray."
+    """Return C++ code representation of a numpy ndarray with FINN DataType
+    dtype, using hls_var_name as the resulting C++ variable name. If
+    pack_innermost_dim is specified, the innermost dimension of the ndarray
+    will be packed into a hex string using array2hexstring.
+    """
     hls_dtype = dtype.get_hls_datatype_str()
-    if pack_innermost_dim:
-        idimlen = ndarray.shape[-1]
-        ndarray = pack_innermost_dim_as_hex_string(ndarray, dtype, idimlen)
-        hls_dtype = "ap_uint<%d>" % (idimlen * dtype.bitwidth())
     if type(ndarray) != np.ndarray or ndarray.dtype != np.float32:
         # try to convert to a float numpy array (container dtype is float)
         ndarray = np.asarray(ndarray, dtype=np.float32)
+    if pack_innermost_dim:
+        idimlen = ndarray.shape[-1]
+        idimbits = idimlen * dtype.bitwidth()
+        ndarray = pack_innermost_dim_as_hex_string(ndarray, dtype, idimbits)
+        hls_dtype = "ap_uint<%d>" % idimbits
     ndims = ndarray.ndim
     # add type string and variable name
     # e.g. "const ap_uint<64>" "weightMem0"
@@ -22,11 +30,12 @@ def numpy_to_hls_code(ndarray, dtype, hls_var_name, pack_innermost_dim=True):
         ret += "[%d]" % ndarray.shape[d]
     orig_printops = np.get_printoptions()
     np.set_printoptions(threshold=sys.maxsize)
+
     # define a function to convert a single element into a C++ init string
     # a single element can be a hex string if we are using packing
     def elem2str(x):
-        if type(x) == str:
-            return "%s(%s, 16)" % (hls_dtype, x)
+        if type(x) == str or type(x) == np.str_ or type(x) == np.str:
+            return '%s("%s", 16)' % (hls_dtype, x)
         elif type(x) == np.float32:
             if dtype == DataType.FLOAT32:
                 return str(x)
@@ -34,7 +43,8 @@ def numpy_to_hls_code(ndarray, dtype, hls_var_name, pack_innermost_dim=True):
                 return str(int(x))
         else:
             raise Exception("Unsupported type for numpy_to_hls_code")
-    strarr = np.array2string(ndarray, separator=", ", formatter={'all': elem2str})
+
+    strarr = np.array2string(ndarray, separator=", ", formatter={"all": elem2str})
     np.set_printoptions(**orig_printops)
     strarr = strarr.replace("[", "{").replace("]", "}")
     ret = ret + " = \n" + strarr + ";"