fix tutorials

apache · Jun 13, 2019 · 9282b89 · 9282b89
1 parent 8a148f3
commit 9282b89
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Showing 3 changed files with 6 additions and 5 deletions.
diff --git a/tutorials/frontend/deploy_model_on_android.py b/tutorials/frontend/deploy_model_on_android.py
@@ -260,10 +260,10 @@ def transform_image(image):
 
 input_name = 'input_1'
 shape_dict = {input_name: x.shape}
-func, params = relay.frontend.from_keras(keras_mobilenet_v2, shape_dict)
+mod, params = relay.frontend.from_keras(keras_mobilenet_v2, shape_dict)
 
 with relay.build_config(opt_level=3):
-    graph, lib, params = relay.build(func, target=target,
+    graph, lib, params = relay.build(mod[mod.entry_func], target=target,
                                      target_host=target_host, params=params)
 
 # After `relay.build`, you will get three return values: graph,

diff --git a/tutorials/frontend/deploy_model_on_rasp.py b/tutorials/frontend/deploy_model_on_rasp.py
@@ -140,8 +140,9 @@ def transform_image(image):
 
 # We support MXNet static graph(symbol) and HybridBlock in mxnet.gluon
 shape_dict = {'data': x.shape}
-func, params = relay.frontend.from_mxnet(block, shape_dict)
+mod, params = relay.frontend.from_mxnet(block, shape_dict)
 # we want a probability so add a softmax operator
+func = mod[mod.entry_func]
 func = relay.Function(func.params, relay.nn.softmax(func.body), None, func.type_params, func.attrs)
 
 ######################################################################

diff --git a/tutorials/frontend/deploy_ssd_gluoncv.py b/tutorials/frontend/deploy_ssd_gluoncv.py
@@ -76,9 +76,9 @@
 block = model_zoo.get_model(model_name, pretrained=True)
 
 def build(target):
-    net, params = relay.frontend.from_mxnet(block, {"data": dshape})
+    mod, params = relay.frontend.from_mxnet(block, {"data": dshape})
     with relay.build_config(opt_level=3):
-        graph, lib, params = relay.build(net, target, params=params)
+        graph, lib, params = relay.build(mod[mod.entry_func], target, params=params)
     return graph, lib, params
 
 ######################################################################