dataset and dataloader interface polish

python/jittor/__init__.py

@@ -9,7 +9,7 @@
 # file 'LICENSE.txt', which is part of this source code package.
 # ***************************************************************
 
-__version__ = '1.3.5.32'
+__version__ = '1.3.5.33'
 from jittor_utils import lock
 with lock.lock_scope():
     ori_int = int

python/jittor/dataset/dataset.py

@@ -129,6 +129,7 @@ class Dataset(object):
         self.sampler = None
         self._disable_workers = False
         self._shuffle_rng = np.random.default_rng(1)
+        self.dataset = self
 
     def __getitem__(self, index):
         raise NotImplementedError
@@ -585,6 +586,8 @@ Example::
                     self.batch_id += 1
                     yield batch_data
 
+def DataLoader(dataset: Dataset, *args, **kargs):
+    return dataset.set_attrs(*args, **kargs)
 
 class ImageFolder(Dataset):
     """

python/jittor/misc.py

@@ -1977,3 +1977,11 @@ def isneginf(x): return _simple_for(x, "x<0 && isinf(x)")
 jt.Var.isneginf = isneginf
 def isposinf(x): return _simple_for(x, "x>0 && isinf(x)")
 jt.Var.isposinf = isposinf
+
+# fake torch interface
+def contiguous(x): return x.clone()
+jt.Var.contiguous = contiguous
+def cpu(x): return x.clone()
+jt.Var.cpu = cpu
+def to(x, *args, **kargs): return x.clone()
+jt.Var.to = to

python/jittor/nn.py

@@ -1372,7 +1372,7 @@ class ConvTranspose(Module):
                 b = self.bias.broadcast(y.shape, [0,2,3])
                 y = y + b
             return y
-
+ConvTranspose2d = ConvTranspose
 
 class ConvTranspose3d(Module):
     def __init__(self, in_channels, out_channels, kernel_size, stride=1, \