Merge pull request #957 from tensorlayer/fix-docs

fix docs and numpy version

Author: rundiwu

CHANGELOG.md

@@ -84,8 +84,10 @@ To release a new version, please update the changelog as followed:
 ### Deprecated
 
 ### Fixed
+- fix docs of models @zsdonghao #957
 - In `BatchNorm`, keep dimensions of mean and variance to suit `channels first` (PR #963)
 
+
 ### Removed
 
 ### Security

requirements/requirements.txt

@@ -1,5 +1,5 @@
 imageio>=2.3,<2.5
-numpy>=1.14,<1.16
+numpy>=1.16,<1.17
 progressbar2>=3.38,<3.39
 requests==2.21.0
 scikit-learn>=0.19,<0.21

tensorlayer/files/utils.py

@@ -1958,7 +1958,7 @@ def load_npz(path='', name='model.npz'):
     - `Saving dictionary using numpy <http://stackoverflow.com/questions/22315595/saving-dictionary-of-header-information-using-numpy-savez>`__
 
     """
-    d = np.load(os.path.join(path, name))
+    d = np.load(os.path.join(path, name), allow_pickle=True)
     return d['params']
 
 

tensorlayer/models/core.py

@@ -75,6 +75,7 @@ class Model(object):
     >>> from tensorlayer.models import Model
 
     Define static model
+
     >>> class CustomModel(Model):
     >>>     def __init__(self):
     >>>         super(CustomModel, self).__init__()
@@ -97,6 +98,7 @@ class Model(object):
     >>> M_static = Model(inputs=ni, outputs=nn, name="mlp")
 
     Get network information
+
     >>> print(M_static)
     ... Model(
     ...  (_inputlayer): Input(shape=[None, 784], name='_inputlayer')
@@ -106,21 +108,25 @@ class Model(object):
     ... )
 
     Forwarding through this network
+
     >>> data = np.random.normal(size=[16, 784]).astype(np.float32)
     >>> outputs_d = M_dynamic(data)
     >>> outputs_s = M_static(data)
 
     Save and load weights
+    
     >>> M_static.save_weights('./model_weights.h5')
     >>> M_static.load_weights('./model_weights.h5')
 
     Save and load the model
+
     >>> M_static.save('./model.h5')
     >>> M = Model.load('./model.h5')
 
     Convert model to layer
+
     >>> M_layer = M_static.as_layer()
-    
+
     """
 
     @property
@@ -251,7 +257,7 @@ def __call__(self, inputs, is_train=None, **kwargs):
             If 'is_train' == False, this network is set as evaluation mode
         kwargs :
             For other keyword-only arguments.
-        
+
         """
 
         self._check_mode(is_train)
@@ -694,7 +700,7 @@ def save(self, filepath, save_weights=True):
         >>> net = tl.models.vgg16()
         >>> net.save('./model.h5', save_weights=True)
         >>> new_net = Model.load('./model.h5', load_weights=True)
-        
+
         """
         # TODO: support saving LambdaLayer that includes parametric self defined function with outside variables
         if self.outputs is None: