SINGA-295 - Add an example of image classification using GoogleNet

fixed a bug in tensor.py to_numpy()
apache · Jan 23, 2017 · 8c990f7 · 8c990f7
1 parent 114592b
commit 8c990f7
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Showing 3 changed files with 5 additions and 11 deletions.
diff --git a/examples/imagenet/googlenet/README.md b/examples/imagenet/googlenet/README.md
@@ -1,7 +1,7 @@
 ---
 name: GoogleNet on ImageNet
 SINGA version: 1.0.1
-SINGA commit:
+SINGA commit: 4e47499e5c3ad3a8081abb0a9a2fca0f6d317241
 parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz
 parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d
 license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet

diff --git a/examples/imagenet/googlenet/serve.py b/examples/imagenet/googlenet/serve.py
@@ -66,25 +66,19 @@ def setup(self, input_sample_shape):
 
     def forward(self, flag, x):
         '''pad zeros'''
-        dev = x.device
-        x.to_host()
         tmp = tensor.to_numpy(x)
         shape = add_to_tuple(x.shape)
         ret = np.zeros(shape)
         ret[:,:,:-1, :-1] = tmp
         y = tensor.from_numpy(ret)
-        x.to_device(dev)
-        y.to_device(dev)
+        y.to_device(x.device)
         return y
 
     def backward(self, falg, dy):
         '''remove paddings'''
-        dev = dy.device
-        dy.to_host()
         tmp = tensor.to_numpy(dy)
         dx = tensor.from_numpy(tmp[:,:,:-1,:-1])
-        dx.to_device(dev)
-        dy.to_device(dev)
+        dx.to_device(dy.device)
         return dx, []
 
 # b_specs = {'init': 'constant', 'value': 0, 'lr_mult': 2, 'decay_mult': 0}

diff --git a/python/singa/tensor.py b/python/singa/tensor.py
@@ -578,9 +578,9 @@ def to_numpy(t):
     '''
     th = to_host(t)
     if th.dtype == core_pb2.kFloat32:
-        np_array = ret.singa_tensor.GetFloatValue(int(th.size()))
+        np_array = th.singa_tensor.GetFloatValue(int(th.size()))
     elif th.dtype == core_pb2.kInt:
-        np_array = ret.singa_tensor.GetIntValue(int(th.size()))
+        np_array = th.singa_tensor.GetIntValue(int(th.size()))
     else:
         print 'Not implemented yet for ', th.dtype
     return np_array.reshape(th.shape)