DataBatch support gpu (apache#2797)

* DataBatch support gpu

* DataBatch support gpu and storage data use NDArray

* DataBatch support gpu and storage data use NDArray

* DataBatch support gpu and storage data use NDArray

* fix DataBatch init error and support shuffer

python/mxnet/io.py

@@ -16,6 +16,7 @@
 from .base import check_call, ctypes2docstring
 from .ndarray import NDArray
 from .ndarray import array
+from .ndarray import concatenate
 
 
 class DataBatch(object):
@@ -307,11 +308,11 @@ def _init_data(data, allow_empty, default_name):
         raise TypeError("Input must be NDArray, numpy.ndarray, " + \
                 "a list of them or dict with them as values")
     for k, v in data.items():
-        if isinstance(v, NDArray):
-            data[k] = v.asnumpy()
-    for k, v in data.items():
-        if not isinstance(v, np.ndarray):
-            raise TypeError(("Invalid type '%s' for %s, "  % (type(v), k)) + \
+        if not isinstance(v, NDArray):
+            try:
+                data[k] = array(v)
+            except:
+                raise TypeError(("Invalid type '%s' for %s, "  % (type(v), k)) + \
                     "should be NDArray or numpy.ndarray")
 
     return list(data.items())
@@ -348,8 +349,8 @@ def __init__(self, data, label=None, batch_size=1, shuffle=False, last_batch_han
         if shuffle:
             idx = np.arange(self.data[0][1].shape[0])
             np.random.shuffle(idx)
-            self.data = [(k, v[idx]) for k, v in self.data]
-            self.label = [(k, v[idx]) for k, v in self.label]
+            self.data = [(k, array(v.asnumpy()[idx], v.context)) for k, v in self.data]
+            self.label = [(k, array(v.asnumpy()[idx], v.context)) for k, v in self.label]
 
         self.data_list = [x[1] for x in self.data] + [x[1] for x in self.label]
         self.num_source = len(self.data_list)
@@ -411,11 +412,10 @@ def _getdata(self, data_source):
         """Load data from underlying arrays, internal use only"""
         assert(self.cursor < self.num_data), "DataIter needs reset."
         if self.cursor + self.batch_size <= self.num_data:
-            return [array(x[1][self.cursor:self.cursor+self.batch_size]) for x in data_source]
+            return [x[1][self.cursor:self.cursor+self.batch_size] for x in data_source]
         else:
             pad = self.batch_size - self.num_data + self.cursor
-            return [array(np.concatenate((x[1][self.cursor:], x[1][:pad]),
-                                         axis=0)) for x in data_source]
+            return [concatenate([x[1][self.cursor:], x[1][:pad]]) for x in data_source]
 
     def getdata(self):
         return self._getdata(self.data)