read tensor data as numpy array instead of python list (#1287)

* read tensor data as numpy array instead of python list

this is faster by 700 times

* apply code-format changes

* read char tensor as numpy array instead of python list

pytengine/tengine/tensor.py

@@ -132,10 +132,10 @@ class Tensor(object):
         if ctype is ctypes.c_char:
             _LIB.get_tensor_buffer.restype = ctypes.POINTER(ctype)
             res = _LIB.get_tensor_buffer(ctypes.c_void_p(self.tensor))
-            return res[:size]
+            return np.ctypeslib.as_array(ctypes.cast(res, ctypes.POINTER(ctype)), (size,))
         _LIB.get_tensor_buffer.restype = ctypes.POINTER(ctype)
         res = _LIB.get_tensor_buffer(ctypes.c_void_p(self.tensor))
-        return res[:size]
+        return np.ctypeslib.as_array(ctypes.cast(res, ctypes.POINTER(ctype)), (size,))
 
     def ascontiguousarray(self,value):
         if self.dtype.enum == 2:

source/device/tim-vx/timvx_dump.c

@@ -462,7 +462,7 @@ void extract_feature_from_tensor_timvx(const char* comment, const char* layer_na
     {
         strcpy(save_dir, env_path);
 
-        if ('/' == save_dir[strlen(env_path)  - 1] || '\\' == save_dir[strlen(env_path) - 1])
+        if ('/' == save_dir[strlen(env_path) - 1] || '\\' == save_dir[strlen(env_path) - 1])
         {
 #ifdef _MSC_VER
             save_dir[strlen(env_path)] = '\\';