diff --git a/CHANGELOG.md b/CHANGELOG.md
index 94a83b51d..89939c54d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -67,6 +67,21 @@ To release a new version, please update the changelog as followed:
 
 <!-- YOU CAN EDIT FROM HERE -->
 
+## [2.1.0] - 2019-5-25
+
+### Changed
+- change the format of network config, change related code and files; change layer act (PR #980)
+
+### Added
+
+### Dependencies Update
+
+### Fixed
+
+### Contributors
+- @warshallrho: #PR980
+
+
 ## [2.0.1] - 2019-5-17
 
 
@@ -460,4 +475,4 @@ To many PR for this update, please check [here](https://github.com/tensorlayer/t
 [1.10.0]: https://github.com/tensorlayer/tensorlayer/compare/1.9.1...1.10.0
 [1.9.1]: https://github.com/tensorlayer/tensorlayer/compare/1.9.0...1.9.1
 [1.9.0]: https://github.com/tensorlayer/tensorlayer/compare/1.8.5...1.9.0
-[1.8.5]: https://github.com/tensorlayer/tensorlayer/compare/1.8.4...1.8.5
+[1.8.5]: https://github.com/tensorlayer/tensorlayer/compare/1.8.4...1.8.5
\ No newline at end of file
diff --git a/docs/user/get_start_model.rst b/docs/user/get_start_model.rst
index 7545eac0b..0ff3459cd 100644
--- a/docs/user/get_start_model.rst
+++ b/docs/user/get_start_model.rst
@@ -211,10 +211,9 @@ z = f(x*W+b)
 
   class Dense(Layer):
       def __init__(self, n_units, act=None, in_channels=None, name=None):
-          super(Dense, self).__init__(name)
+          super(Dense, self).__init__(name, act=act)
 
           self.n_units = n_units
-          self.act = act
           self.in_channels = in_channels
 
           # for dynamic model, it needs the input shape to get the shape of W
diff --git a/examples/text_generation/tutorial_generate_text.py b/examples/text_generation/tutorial_generate_text.py
index 50c320632..d157b1ed5 100644
--- a/examples/text_generation/tutorial_generate_text.py
+++ b/examples/text_generation/tutorial_generate_text.py
@@ -329,4 +329,4 @@ def main_lstm_generate_text():
     # main_restore_embedding_layer()
 
     # How to generate text from a given context
-    main_lstm_generate_text()
+    main_lstm_generate_text()
\ No newline at end of file
diff --git a/tensorlayer/db.py b/tensorlayer/db.py
index cb8db8e10..7ca3e7bb5 100644
--- a/tensorlayer/db.py
+++ b/tensorlayer/db.py
@@ -13,7 +13,7 @@
 import tensorflow as tf
 
 from tensorlayer import logging
-from tensorlayer.files import net2static_graph, static_graph2net, assign_weights
+from tensorlayer.files import static_graph2net, assign_weights
 from tensorlayer.files import save_weights_to_hdf5, load_hdf5_to_weights
 from tensorlayer.files import del_folder, exists_or_mkdir
 
@@ -153,7 +153,7 @@ def save_model(self, network=None, model_name='model', **kwargs):
         s = time.time()
 
         # kwargs.update({'architecture': network.all_graphs, 'time': datetime.utcnow()})
-        kwargs.update({'architecture': net2static_graph(network), 'time': datetime.utcnow()})
+        kwargs.update({'architecture': network.config, 'time': datetime.utcnow()})
 
         try:
             params_id = self.model_fs.put(self._serialization(params))
diff --git a/tensorlayer/files/utils.py b/tensorlayer/files/utils.py
index 72fcb1824..60521c309 100644
--- a/tensorlayer/files/utils.py
+++ b/tensorlayer/files/utils.py
@@ -31,6 +31,7 @@
 from tensorflow.python.util.tf_export import keras_export
 from tensorflow.python.util import serialization
 import json
+import datetime
 
 # from six.moves import zip
 
@@ -73,7 +74,7 @@
     'load_hdf5_to_weights',
     'save_hdf5_graph',
     'load_hdf5_graph',
-    'net2static_graph',
+    # 'net2static_graph',
     'static_graph2net',
     # 'save_pkl_graph',
     # 'load_pkl_graph',
@@ -92,29 +93,29 @@ def str2func(s):
     return expr
 
 
-def net2static_graph(network):
-    saved_file = dict()
-    if network._NameNone is True:
-        saved_file.update({"name": None})
-    else:
-        saved_file.update({"name": network.name})
-    if not isinstance(network.inputs, list):
-        saved_file.update({"inputs": network.inputs._info[0].name})
-    else:
-        saved_inputs = []
-        for saved_input in network.inputs:
-            saved_inputs.append(saved_input._info[0].name)
-        saved_file.update({"inputs": saved_inputs})
-    if not isinstance(network.outputs, list):
-        saved_file.update({"outputs": network.outputs._info[0].name})
-    else:
-        saved_outputs = []
-        for saved_output in network.outputs:
-            saved_outputs.append(saved_output._info[0].name)
-        saved_file.update({"outputs": saved_outputs})
-    saved_file.update({"config": network.config})
-
-    return saved_file
+# def net2static_graph(network):
+#     saved_file = dict()
+#     # if network._NameNone is True:
+#     #     saved_file.update({"name": None})
+#     # else:
+#     #     saved_file.update({"name": network.name})
+#     # if not isinstance(network.inputs, list):
+#     #     saved_file.update({"inputs": network.inputs._info[0].name})
+#     # else:
+#     #     saved_inputs = []
+#     #     for saved_input in network.inputs:
+#     #         saved_inputs.append(saved_input._info[0].name)
+#     #     saved_file.update({"inputs": saved_inputs})
+#     # if not isinstance(network.outputs, list):
+#     #     saved_file.update({"outputs": network.outputs._info[0].name})
+#     # else:
+#     #     saved_outputs = []
+#     #     for saved_output in network.outputs:
+#     #         saved_outputs.append(saved_output._info[0].name)
+#     #     saved_file.update({"outputs": saved_outputs})
+#     saved_file.update({"config": network.config})
+#
+#     return saved_file
 
 
 @keras_export('keras.models.save_model')
@@ -149,7 +150,7 @@ def load_keras_model(model_config):
     return model
 
 
-def save_hdf5_graph(network, filepath='model.hdf5', save_weights=False):
+def save_hdf5_graph(network, filepath='model.hdf5', save_weights=False, customized_data=None):
     """Save the architecture of TL model into a hdf5 file. Support saving model weights.
 
     Parameters
@@ -160,6 +161,8 @@ def save_hdf5_graph(network, filepath='model.hdf5', save_weights=False):
         The name of model file.
     save_weights : bool
         Whether to save model weights.
+    customized_data : dict
+        The user customized meta data.
 
     Examples
     --------
@@ -177,11 +180,22 @@ def save_hdf5_graph(network, filepath='model.hdf5', save_weights=False):
 
     logging.info("[*] Saving TL model into {}, saving weights={}".format(filepath, save_weights))
 
-    saved_file = net2static_graph(network)
-    saved_file_str = str(saved_file)
+    model_config = network.config  # net2static_graph(network)
+    model_config_str = str(model_config)
+    customized_data_str = str(customized_data)
+    version_info = {
+        "tensorlayer_version": tl.__version__,
+        "backend": "tensorflow",
+        "backend_version": tf.__version__,
+        "training_device": "gpu",
+        "save_date": datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat()
+    }
+    version_info_str = str(version_info)
 
     with h5py.File(filepath, 'w') as f:
-        f.attrs["model_structure"] = saved_file_str.encode('utf8')
+        f.attrs["model_config"] = model_config_str.encode('utf8')
+        f.attrs["customized_data"] = customized_data_str.encode('utf8')
+        f.attrs["version_info"] = version_info_str.encode('utf8')
         if save_weights:
             _save_weights_to_hdf5_group(f, network.all_layers)
         f.flush()
@@ -237,29 +251,15 @@ def eval_layer(layer_kwargs):
         raise RuntimeError("Unknown layer type.")
 
 
-def static_graph2net(saved_file):
+def static_graph2net(model_config):
     layer_dict = {}
-    model_name = saved_file['name']
-    inputs_tensors = saved_file['inputs']
-    outputs_tensors = saved_file['outputs']
-    all_args = saved_file['config']
-    tf_version = saved_file['config'].pop(0)['tf_version']
-    tl_version = saved_file['config'].pop(0)['tl_version']
-    if tf_version != tf.__version__:
-        logging.warning(
-            "Saved model uses tensorflow version {}, but now you are using tensorflow version {}".format(
-                tf_version, tf.__version__
-            )
-        )
-    if tl_version != tl.__version__:
-        logging.warning(
-            "Saved model uses tensorlayer version {}, but now you are using tensorlayer version {}".format(
-                tl_version, tl.__version__
-            )
-        )
+    model_name = model_config["name"]
+    inputs_tensors = model_config["inputs"]
+    outputs_tensors = model_config["outputs"]
+    all_args = model_config["model_architecture"]
     for idx, layer_kwargs in enumerate(all_args):
-        layer_class = layer_kwargs['class']  # class of current layer
-        prev_layers = layer_kwargs.pop('prev_layer')  # name of previous layers
+        layer_class = layer_kwargs["class"]  # class of current layer
+        prev_layers = layer_kwargs.pop("prev_layer")  # name of previous layers
         net = eval_layer(layer_kwargs)
         if layer_class in tl.layers.inputs.__all__:
             net = net._nodes[0].out_tensors[0]
@@ -312,11 +312,30 @@ def load_hdf5_graph(filepath='model.hdf5', load_weights=False):
     - see ``tl.files.save_hdf5_graph``
     """
     logging.info("[*] Loading TL model from {}, loading weights={}".format(filepath, load_weights))
+
     f = h5py.File(filepath, 'r')
-    saved_file_str = f.attrs["model_structure"].decode('utf8')
-    saved_file = eval(saved_file_str)
 
-    M = static_graph2net(saved_file)
+    version_info_str = f.attrs["version_info"].decode('utf8')
+    version_info = eval(version_info_str)
+    backend_version = version_info["backend_version"]
+    tensorlayer_version = version_info["tensorlayer_version"]
+    if backend_version != tf.__version__:
+        logging.warning(
+            "Saved model uses tensorflow version {}, but now you are using tensorflow version {}".format(
+                backend_version, tf.__version__
+            )
+        )
+    if tensorlayer_version != tl.__version__:
+        logging.warning(
+            "Saved model uses tensorlayer version {}, but now you are using tensorlayer version {}".format(
+                tensorlayer_version, tl.__version__
+            )
+        )
+
+    model_config_str = f.attrs["model_config"].decode('utf8')
+    model_config = eval(model_config_str)
+
+    M = static_graph2net(model_config)
     if load_weights:
         if not ('layer_names' in f.attrs.keys()):
             raise RuntimeError("Saved model does not contain weights.")
@@ -329,55 +348,55 @@ def load_hdf5_graph(filepath='model.hdf5', load_weights=False):
     return M
 
 
-def load_pkl_graph(name='model.pkl'):
-    """Restore TL model archtecture from a a pickle file. No parameters be restored.
-
-    Parameters
-    -----------
-    name : str
-        The name of graph file.
-
-    Returns
-    --------
-    network : TensorLayer Model.
-
-    Examples
-    --------
-    >>> # It is better to use load_hdf5_graph
-    """
-    logging.info("[*] Loading TL graph from {}".format(name))
-    with open(name, 'rb') as file:
-        saved_file = pickle.load(file)
-
-    M = static_graph2net(saved_file)
-
-    return M
-
-
-def save_pkl_graph(network, name='model.pkl'):
-    """Save the architecture of TL model into a pickle file. No parameters be saved.
-
-    Parameters
-    -----------
-    network : TensorLayer layer
-        The network to save.
-    name : str
-        The name of graph file.
-
-    Example
-    --------
-    >>> # It is better to use save_hdf5_graph
-    """
-    if network.outputs is None:
-        raise AssertionError("save_graph not support dynamic mode yet")
-
-    logging.info("[*] Saving TL graph into {}".format(name))
-
-    saved_file = net2static_graph(network)
-
-    with open(name, 'wb') as file:
-        pickle.dump(saved_file, file, protocol=pickle.HIGHEST_PROTOCOL)
-    logging.info("[*] Saved graph")
+# def load_pkl_graph(name='model.pkl'):
+#     """Restore TL model archtecture from a a pickle file. No parameters be restored.
+#
+#     Parameters
+#     -----------
+#     name : str
+#         The name of graph file.
+#
+#     Returns
+#     --------
+#     network : TensorLayer Model.
+#
+#     Examples
+#     --------
+#     >>> # It is better to use load_hdf5_graph
+#     """
+#     logging.info("[*] Loading TL graph from {}".format(name))
+#     with open(name, 'rb') as file:
+#         saved_file = pickle.load(file)
+#
+#     M = static_graph2net(saved_file)
+#
+#     return M
+#
+#
+# def save_pkl_graph(network, name='model.pkl'):
+#     """Save the architecture of TL model into a pickle file. No parameters be saved.
+#
+#     Parameters
+#     -----------
+#     network : TensorLayer layer
+#         The network to save.
+#     name : str
+#         The name of graph file.
+#
+#     Example
+#     --------
+#     >>> # It is better to use save_hdf5_graph
+#     """
+#     if network.outputs is None:
+#         raise AssertionError("save_graph not support dynamic mode yet")
+#
+#     logging.info("[*] Saving TL graph into {}".format(name))
+#
+#     saved_file = net2static_graph(network)
+#
+#     with open(name, 'wb') as file:
+#         pickle.dump(saved_file, file, protocol=pickle.HIGHEST_PROTOCOL)
+#     logging.info("[*] Saved graph")
 
 
 # Load dataset functions
diff --git a/tensorlayer/layers/convolution/binary_conv.py b/tensorlayer/layers/convolution/binary_conv.py
index 23448cf6f..cf55127d5 100644
--- a/tensorlayer/layers/convolution/binary_conv.py
+++ b/tensorlayer/layers/convolution/binary_conv.py
@@ -75,11 +75,10 @@ def __init__(
             in_channels=None,
             name=None  # 'binary_cnn2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = self._strides = strides
-        self.act = act
         self.padding = padding
         self.use_gemm = use_gemm
         self.data_format = data_format
diff --git a/tensorlayer/layers/convolution/deformable_conv.py b/tensorlayer/layers/convolution/deformable_conv.py
index 5f75bbe15..616803ba1 100644
--- a/tensorlayer/layers/convolution/deformable_conv.py
+++ b/tensorlayer/layers/convolution/deformable_conv.py
@@ -83,12 +83,11 @@ def __init__(
             in_channels=None,
             name=None  # 'deformable_conv_2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
 
         self.offset_layer = offset_layer
         self.n_filter = n_filter
         self.filter_size = filter_size
-        self.act = act
         self.padding = padding
         self.W_init = W_init
         self.b_init = b_init
diff --git a/tensorlayer/layers/convolution/depthwise_conv.py b/tensorlayer/layers/convolution/depthwise_conv.py
index d6136ede3..b11233c27 100644
--- a/tensorlayer/layers/convolution/depthwise_conv.py
+++ b/tensorlayer/layers/convolution/depthwise_conv.py
@@ -82,10 +82,9 @@ def __init__(
             in_channels=None,
             name=None  # 'depthwise_conv2d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.filter_size = filter_size
         self.strides = self._strides = strides
-        self.act = act
         self.padding = padding
         self.dilation_rate = self._dilation_rate = dilation_rate
         self.data_format = data_format
diff --git a/tensorlayer/layers/convolution/dorefa_conv.py b/tensorlayer/layers/convolution/dorefa_conv.py
index ed9b32dd8..dc7979967 100644
--- a/tensorlayer/layers/convolution/dorefa_conv.py
+++ b/tensorlayer/layers/convolution/dorefa_conv.py
@@ -81,13 +81,12 @@ def __init__(
             in_channels=None,
             name=None  # 'dorefa_cnn2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.bitW = bitW
         self.bitA = bitA
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = self._strides = strides
-        self.act = act
         self.padding = padding
         self.use_gemm = use_gemm
         self.data_format = data_format
diff --git a/tensorlayer/layers/convolution/expert_conv.py b/tensorlayer/layers/convolution/expert_conv.py
index d7e59a0e8..50ea12cb9 100644
--- a/tensorlayer/layers/convolution/expert_conv.py
+++ b/tensorlayer/layers/convolution/expert_conv.py
@@ -71,8 +71,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'cnn1d_layer',
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.n_filter = shape[-1]
         self.filter_size = shape[0]
         self.shape = shape
@@ -191,8 +190,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'cnn2d_layer',
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.n_filter = shape[-1]
         self.filter_size = (shape[0], shape[1])
         self.shape = shape
@@ -310,8 +308,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'cnn3d_layer'
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.n_filter = shape[-1]
         self.filter_size = (shape[0], shape[1], shape[2])
         self.shape = shape
diff --git a/tensorlayer/layers/convolution/expert_deconv.py b/tensorlayer/layers/convolution/expert_deconv.py
index cb5cd6773..f23c752ad 100644
--- a/tensorlayer/layers/convolution/expert_deconv.py
+++ b/tensorlayer/layers/convolution/expert_deconv.py
@@ -80,8 +80,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'decnn1d_layer',
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.shape = shape
         self.outputs_shape = outputs_shape
         self.strides = strides
@@ -215,8 +214,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'decnn2d_layer',
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.shape = shape
         self.outputs_shape = outputs_shape
         self.strides = strides
@@ -342,8 +340,7 @@ def __init__(
             b_init=tl.initializers.constant(value=0.0),
             name=None  # 'decnn3d_layer',
     ):
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.shape = shape
         self.outputs_shape = outputs_shape
         self.strides = strides
diff --git a/tensorlayer/layers/convolution/group_conv.py b/tensorlayer/layers/convolution/group_conv.py
index 34d8c10e6..bc35d4e00 100644
--- a/tensorlayer/layers/convolution/group_conv.py
+++ b/tensorlayer/layers/convolution/group_conv.py
@@ -73,12 +73,11 @@ def __init__(
             in_channels=None,
             name=None  # 'groupconv',
     ):  # Windaway
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = self._strides = strides
         self.n_group = n_group
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self.dilation_rate = self._dilation_rate = dilation_rate
diff --git a/tensorlayer/layers/convolution/quan_conv.py b/tensorlayer/layers/convolution/quan_conv.py
index e235dfeb4..75ee3943c 100644
--- a/tensorlayer/layers/convolution/quan_conv.py
+++ b/tensorlayer/layers/convolution/quan_conv.py
@@ -82,13 +82,12 @@ def __init__(
             in_channels=None,
             name=None  # 'quan_cnn2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.bitW = bitW
         self.bitA = bitA
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = self._strides = strides
-        self.act = act
         self.padding = padding
         self.use_gemm = use_gemm
         self.data_format = data_format
diff --git a/tensorlayer/layers/convolution/separable_conv.py b/tensorlayer/layers/convolution/separable_conv.py
index b6ae62446..ca1c66d49 100644
--- a/tensorlayer/layers/convolution/separable_conv.py
+++ b/tensorlayer/layers/convolution/separable_conv.py
@@ -84,11 +84,10 @@ def __init__(
             in_channels=None,
             name=None  # 'seperable1d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = strides
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self.dilation_rate = dilation_rate
@@ -232,11 +231,10 @@ def __init__(
             in_channels=None,
             name=None  # 'seperable2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = strides
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self.dilation_rate = dilation_rate
diff --git a/tensorlayer/layers/convolution/simplified_conv.py b/tensorlayer/layers/convolution/simplified_conv.py
index c00ff8fe7..536d4e52e 100644
--- a/tensorlayer/layers/convolution/simplified_conv.py
+++ b/tensorlayer/layers/convolution/simplified_conv.py
@@ -70,11 +70,10 @@ def __init__(
             in_channels=None,
             name=None  # 'conv1d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.stride = stride
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self.dilation_rate = dilation_rate
@@ -201,11 +200,10 @@ def __init__(
             in_channels=None,
             name=None  # 'conv2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self._strides = self.strides = strides
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self._dilation_rate = self.dilation_rate = dilation_rate
@@ -335,11 +333,10 @@ def __init__(
             in_channels=None,
             name=None  # 'conv3d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self._strides = self.strides = strides
-        self.act = act
         self.padding = padding
         self.data_format = data_format
         self._dilation_rate = self.dilation_rate = dilation_rate
diff --git a/tensorlayer/layers/convolution/simplified_deconv.py b/tensorlayer/layers/convolution/simplified_deconv.py
index 847062859..57beff0f4 100644
--- a/tensorlayer/layers/convolution/simplified_deconv.py
+++ b/tensorlayer/layers/convolution/simplified_deconv.py
@@ -71,12 +71,11 @@ def __init__(
             in_channels=None,
             name=None  # 'decnn2d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = strides
         self.padding = padding
-        self.act = act
         self.data_format = data_format
         self.dilation_rate = dilation_rate
         self.W_init = W_init
@@ -199,12 +198,11 @@ def __init__(
             in_channels=None,
             name=None  # 'decnn3d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = strides
         self.padding = padding
-        self.act = act
         self.data_format = data_format
         self.W_init = W_init
         self.b_init = b_init
diff --git a/tensorlayer/layers/convolution/super_resolution.py b/tensorlayer/layers/convolution/super_resolution.py
index 35fee8722..21d765e03 100644
--- a/tensorlayer/layers/convolution/super_resolution.py
+++ b/tensorlayer/layers/convolution/super_resolution.py
@@ -53,9 +53,8 @@ def __init__(
             in_channels=None,
             name=None  # 'subpixel_conv1d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.scale = scale
-        self.act = act
         self.in_channels = in_channels
         self.out_channels = int(self.in_channels / self.scale)
 
@@ -151,10 +150,9 @@ def __init__(
             in_channels=None,
             name=None  # 'subpixel_conv2d'
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.scale = scale
         self.n_out_channels = n_out_channels
-        self.act = act
         self.in_channels = in_channels
 
         if self.in_channels is not None:
diff --git a/tensorlayer/layers/convolution/ternary_conv.py b/tensorlayer/layers/convolution/ternary_conv.py
index 9a97c7bec..33e01507c 100644
--- a/tensorlayer/layers/convolution/ternary_conv.py
+++ b/tensorlayer/layers/convolution/ternary_conv.py
@@ -75,11 +75,10 @@ def __init__(
             in_channels=None,
             name=None  # 'ternary_cnn2d',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_filter = n_filter
         self.filter_size = filter_size
         self.strides = self._strides = strides
-        self.act = act
         self.padding = padding
         self.use_gemm = use_gemm
         self.data_format = data_format
diff --git a/tensorlayer/layers/core.py b/tensorlayer/layers/core.py
index ce98f156c..d98ea312e 100644
--- a/tensorlayer/layers/core.py
+++ b/tensorlayer/layers/core.py
@@ -17,6 +17,36 @@
 
 _global_layer_name_dict = {}  # TODO: better implementation?
 
+_act_dict = {
+    "relu": tf.nn.relu,
+    "relu6": tf.nn.relu6,
+    "leaky_relu": tf.nn.leaky_relu,
+    "lrelu": tf.nn.leaky_relu,
+    "softplus": tf.nn.softplus,
+    "tanh": tf.nn.tanh,
+    "sigmoid": tf.nn.sigmoid,
+}
+
+
+def str2act(act):
+    if len(act) > 5 and act[0:5] == "lrelu":
+        try:
+            alpha = float(act[5:])
+            return lambda x: tf.nn.leaky_relu(x, alpha=alpha)
+        except Exception as e:
+            raise Exception("{} can not be parsed as a float".format(act[5:]))
+
+    if len(act) > 10 and act[0:10] == "leaky_relu":
+        try:
+            alpha = float(act[10:])
+            return lambda x: tf.nn.leaky_relu(x, alpha=alpha)
+        except Exception as e:
+            raise Exception("{} can not be parsed as a float".format(act[10:]))
+
+    if act not in _act_dict.keys():
+        raise Exception("Unsupported act: {}".format(act))
+    return _act_dict[act]
+
 
 class Layer(object):
     """The basic :class:`Layer` class represents a single layer of a neural network.
@@ -47,11 +77,12 @@ class Layer(object):
 
     """
 
-    def __init__(self, name=None, *args, **kwargs):
+    def __init__(self, name=None, act=None, *args, **kwargs):
         """
         Initializing the Layer.
 
         :param name: str or None
+        :param name: str or function or None
         """
 
         # Layer constants
@@ -84,6 +115,10 @@ def __init__(self, name=None, *args, **kwargs):
                 _global_layer_name_dict[name] = 0
 
         self.name = name
+        if isinstance(act, str):
+            self.act = str2act(act)
+        else:
+            self.act = act
 
         # Layer building state
         self._built = False
@@ -479,7 +514,8 @@ def _release_memory(self):
     def get_args(self):
         init_args = {}
         init_args.update({"layer_type": "modellayer"})
-        init_args["model"] = utils.net2static_graph(self.layer_args["model"])
+        # init_args["model"] = utils.net2static_graph(self.layer_args["model"])
+        init_args["model"] = self.layer_args["model"].config
         return init_args
 
 
diff --git a/tensorlayer/layers/dense/base_dense.py b/tensorlayer/layers/dense/base_dense.py
index a5b800f04..e4c96af50 100644
--- a/tensorlayer/layers/dense/base_dense.py
+++ b/tensorlayer/layers/dense/base_dense.py
@@ -63,10 +63,9 @@ def __init__(
             name=None,  # 'dense',
     ):
 
-        super(Dense, self).__init__(name)
+        super(Dense, self).__init__(name, act=act)
 
         self.n_units = n_units
-        self.act = act
         self.W_init = W_init
         self.b_init = b_init
         self.in_channels = in_channels
diff --git a/tensorlayer/layers/dense/binary_dense.py b/tensorlayer/layers/dense/binary_dense.py
index 4067ac4c3..77adde3b0 100644
--- a/tensorlayer/layers/dense/binary_dense.py
+++ b/tensorlayer/layers/dense/binary_dense.py
@@ -49,9 +49,8 @@ def __init__(
             in_channels=None,
             name=None,  #'binary_dense',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_units = n_units
-        self.act = act
         self.use_gemm = use_gemm
         self.W_init = W_init
         self.b_init = b_init
diff --git a/tensorlayer/layers/dense/dorefa_dense.py b/tensorlayer/layers/dense/dorefa_dense.py
index 80ae3365c..07e9c339e 100644
--- a/tensorlayer/layers/dense/dorefa_dense.py
+++ b/tensorlayer/layers/dense/dorefa_dense.py
@@ -56,11 +56,10 @@ def __init__(
             in_channels=None,
             name=None,  #'dorefa_dense',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.bitW = bitW
         self.bitA = bitA
         self.n_units = n_units
-        self.act = act
         self.use_gemm = use_gemm
         self.W_init = W_init
         self.b_init = b_init
diff --git a/tensorlayer/layers/dense/dropconnect.py b/tensorlayer/layers/dense/dropconnect.py
index d68e6c762..449221f42 100644
--- a/tensorlayer/layers/dense/dropconnect.py
+++ b/tensorlayer/layers/dense/dropconnect.py
@@ -65,14 +65,13 @@ def __init__(
             in_channels=None,
             name=None,  # 'dropconnect',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
 
         if isinstance(keep, numbers.Real) and not (keep > 0 and keep <= 1):
             raise ValueError("keep must be a scalar tensor or a float in the " "range (0, 1], got %g" % keep)
 
         self.keep = keep
         self.n_units = n_units
-        self.act = act
         self.W_init = W_init
         self.b_init = b_init
         self.in_channels = in_channels
diff --git a/tensorlayer/layers/dense/quan_dense.py b/tensorlayer/layers/dense/quan_dense.py
index 5a2513259..f5c42492f 100644
--- a/tensorlayer/layers/dense/quan_dense.py
+++ b/tensorlayer/layers/dense/quan_dense.py
@@ -54,9 +54,8 @@ def __init__(
             in_channels=None,
             name=None,  #'quan_dense',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_units = n_units
-        self.act = act
         self.bitW = bitW
         self.bitA = bitA
         self.use_gemm = use_gemm
diff --git a/tensorlayer/layers/dense/ternary_dense.py b/tensorlayer/layers/dense/ternary_dense.py
index 27efb9090..778636155 100644
--- a/tensorlayer/layers/dense/ternary_dense.py
+++ b/tensorlayer/layers/dense/ternary_dense.py
@@ -49,9 +49,8 @@ def __init__(
             in_channels=None,
             name=None,  #'ternary_dense',
     ):
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.n_units = n_units
-        self.act = act
         self.use_gemm = use_gemm
         self.W_init = W_init
         self.b_init = b_init
diff --git a/tensorlayer/layers/merge.py b/tensorlayer/layers/merge.py
index 346a65962..6f49374ca 100644
--- a/tensorlayer/layers/merge.py
+++ b/tensorlayer/layers/merge.py
@@ -111,9 +111,8 @@ def __init__(
             name=None,  #'elementwise',
     ):
 
-        super(Elementwise, self).__init__(name)
+        super(Elementwise, self).__init__(name, act=act)
         self.combine_fn = combine_fn
-        self.act = act
 
         self.build(None)
         self._built = True
diff --git a/tensorlayer/layers/normalization.py b/tensorlayer/layers/normalization.py
index d8cec274c..1f2b25f81 100644
--- a/tensorlayer/layers/normalization.py
+++ b/tensorlayer/layers/normalization.py
@@ -195,8 +195,7 @@ def __init__(
             data_format='channels_last',
             name=None,
     ):
-        super(BatchNorm, self).__init__(name=name)
-        self.act = act
+        super(BatchNorm, self).__init__(name=name, act=act)
         self.decay = decay
         self.epsilon = epsilon
         self.data_format = data_format
@@ -441,8 +440,7 @@ def __init__(
             gamma_init=tl.initializers.random_normal(mean=1.0, stddev=0.002), num_features=None,
             data_format='channels_last', name=None
     ):
-        super(InstanceNorm, self).__init__(name=name)
-        self.act = act
+        super(InstanceNorm, self).__init__(name=name, act=act)
         self.epsilon = epsilon
         self.beta_init = beta_init
         self.gamma_init = gamma_init
@@ -651,10 +649,9 @@ def __init__(
     ):
 
         # super(LayerNorm, self).__init__(prev_layer=prev_layer, act=act, name=name)
-        super(LayerNorm, self).__init__(name)
+        super(LayerNorm, self).__init__(name, act=act)
         self.center = center
         self.scale = scale
-        self.act = act
         self.epsilon = epsilon
         self.begin_norm_axis = begin_norm_axis
         self.begin_params_axis = begin_params_axis
@@ -730,10 +727,9 @@ class GroupNorm(Layer):
 
     def __init__(self, groups=32, epsilon=1e-06, act=None, data_format='channels_last', name=None):  #'groupnorm'):
         # super(GroupNorm, self).__init__(prev_layer=prev_layer, act=act, name=name)
-        super().__init__(name)
+        super().__init__(name, act=act)
         self.groups = groups
         self.epsilon = epsilon
-        self.act = act
         self.data_format = data_format
 
         logging.info(
@@ -847,8 +843,7 @@ def __init__(
             name=None,  #'switchnorm',
     ):
         # super(SwitchNorm, self).__init__(prev_layer=prev_layer, act=act, name=name)
-        super().__init__(name)
-        self.act = act
+        super().__init__(name, act=act)
         self.epsilon = epsilon
         self.beta_init = beta_init
         self.gamma_init = gamma_init
diff --git a/tensorlayer/models/core.py b/tensorlayer/models/core.py
index c811b9648..c1197ed55 100644
--- a/tensorlayer/models/core.py
+++ b/tensorlayer/models/core.py
@@ -437,15 +437,43 @@ def config(self):
         if self._config is not None and len(self._config) > 0:
             return self._config
         else:
-            _config = []
-            _config.append({"tf_version": tf.__version__})
-            _config.append({"tl_version": tl.__version__})
+            # _config = []
+            _config = {}
+            if self._NameNone is True:
+                _config.update({"name": None})
+            else:
+                _config.update({"name": self.name})
+            # versionInfo = {
+            #     "tensorlayer_version": tl.__version__,
+            #     "backend": "tensorflow",
+            #     "backend_version": tf.__version__,
+            #     "training_device": "gpu",
+            # }
+            # _config.update(versionInfo)
             # if self.outputs is None:
             #     raise RuntimeError(
             #         "Dynamic mode does not support config yet."
             #     )
+            model_architecture = []
             for layer in self.all_layers:
-                _config.append(layer.config)
+                model_architecture.append(layer.config)
+            _config["model_architecture"] = model_architecture
+            if self.inputs is not None:
+                if not isinstance(self.inputs, list):
+                    _config.update({"inputs": self.inputs._info[0].name})
+                else:
+                    config_inputs = []
+                    for config_input in self.inputs:
+                        config_inputs.append(config_input._info[0].name)
+                    _config.update({"inputs": config_inputs})
+            if self.outputs is not None:
+                if not isinstance(self.outputs, list):
+                    _config.update({"outputs": self.outputs._info[0].name})
+                else:
+                    config_outputs = []
+                    for config_output in self.outputs:
+                        config_outputs.append(config_output._info[0].name)
+                    _config.update({"outputs": config_outputs})
             if self._nodes_fixed or self.outputs is None:
                 self._config = _config
 
@@ -714,7 +742,7 @@ def release_memory(self):
         for layer in self.all_layers:
             layer._release_memory()
 
-    def save(self, filepath, save_weights=True):
+    def save(self, filepath, save_weights=True, customized_data=None):
         """
         Save model into a given file.
         This function save can save both the architecture of neural networks and weights (optional).
@@ -726,6 +754,8 @@ def save(self, filepath, save_weights=True):
             Filename into which the model will be saved.
         save_weights : bool
             Whether to save model weights.
+        customized_data : dict
+            The user customized meta data.
 
         Examples
         --------
@@ -739,7 +769,9 @@ def save(self, filepath, save_weights=True):
             raise RuntimeError(
                 "Model save() not support dynamic mode yet.\nHint: you can use Model save_weights() to save the weights in dynamic mode."
             )
-        utils.save_hdf5_graph(network=self, filepath=filepath, save_weights=save_weights)
+        utils.save_hdf5_graph(
+            network=self, filepath=filepath, save_weights=save_weights, customized_data=customized_data
+        )
 
     @staticmethod
     def load(filepath, load_weights=True):
diff --git a/tests/layers/test_layers_convolution.py b/tests/layers/test_layers_convolution.py
index 0f5979d5b..b768600de 100644
--- a/tests/layers/test_layers_convolution.py
+++ b/tests/layers/test_layers_convolution.py
@@ -33,7 +33,7 @@ def setUpClass(cls):
         )(cls.n2)
 
         cls.n4 = tl.layers.SeparableConv1d(
-            n_filter=32, filter_size=3, strides=2, padding='SAME', act=tf.nn.relu, name='separable_1d'
+            n_filter=32, filter_size=3, strides=2, padding='SAME', act='relu', name='separable_1d'
         )(cls.n3)
 
         cls.n5 = tl.layers.SubpixelConv1d(scale=2, act=tf.nn.relu, in_channels=32, name='subpixel_1d')(cls.n4)
@@ -462,6 +462,29 @@ def test_layer_n4(self):
 #         self.assertEqual(self.net2.count_params(), 19392)
 #         self.assertEqual(self.net2.outputs.get_shape().as_list()[1:], [299, 299, 64])
 
+
+class Exception_test(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        print("##### begin testing exception in activation #####")
+
+    def test_exception(cls):
+
+        cls.batch_size = 5
+        cls.inputs_shape = [cls.batch_size, 400, 400, 3]
+        cls.input_layer = Input(cls.inputs_shape, name='input_layer')
+
+        try:
+            cls.n1 = tl.layers.Conv2dLayer(
+                act='activation', shape=(5, 5, 3, 32), strides=(1, 2, 2, 1), padding='SAME',
+                b_init=tf.constant_initializer(value=0.0), name='conv2dlayer'
+            )(cls.input_layer)
+        except Exception as e:
+            cls.assertIsInstance(e, Exception)
+            print(e)
+
+
 if __name__ == '__main__':
 
     tl.logging.set_verbosity(tl.logging.DEBUG)
diff --git a/tests/layers/test_layers_core_act.py b/tests/layers/test_layers_core_act.py
new file mode 100644
index 000000000..0da41fea0
--- /dev/null
+++ b/tests/layers/test_layers_core_act.py
@@ -0,0 +1,109 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import os
+import unittest
+
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+
+import tensorflow as tf
+import tensorlayer as tl
+from tensorlayer.layers import *
+from tensorlayer.models import *
+
+from tests.utils import CustomTestCase
+
+
+class Layer_Convolution_2D_Test(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        print("##### begin testing activation #####")
+
+    @classmethod
+    def tearDownClass(cls):
+        pass
+        # tf.reset_default_graph()
+
+    def test_layer_core_act(cls):
+
+        cls.batch_size = 5
+        cls.inputs_shape = [cls.batch_size, 400, 400, 3]
+        cls.input_layer = Input(cls.inputs_shape, name='input_layer')
+
+        cls.n1 = tl.layers.Conv2dLayer(
+            act=tf.nn.relu, shape=(5, 5, 3, 32), strides=(1, 2, 2, 1), padding='SAME',
+            b_init=tf.constant_initializer(value=0.0), name='conv2dlayer'
+        )(cls.input_layer)
+
+        cls.n2 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="relu", name='conv2d')(cls.n1)
+
+        cls.n3 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="leaky_relu",
+                                  b_init=None)(cls.n2)
+
+        cls.n4 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="lrelu", b_init=None)(cls.n2)
+
+        cls.n5 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="sigmoid",
+                                  in_channels=32)(cls.n4)
+
+        cls.n6 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="tanh", in_channels=32)(cls.n5)
+
+        cls.n7 = tl.layers.Conv2d(
+            n_filter=32, filter_size=(3, 3), strides=(2, 2), act="leaky_relu0.22", in_channels=32
+        )(cls.n6)
+
+        cls.n8 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="lrelu0.22",
+                                  in_channels=32)(cls.n7)
+
+        cls.n9 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="softplus",
+                                  in_channels=32)(cls.n8)
+
+        cls.n10 = tl.layers.Conv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), act="relu6", in_channels=32)(cls.n9)
+
+        cls.model = Model(cls.input_layer, cls.n8)
+
+
+class Exception_test(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        print("##### begin testing exception in activation #####")
+
+    def test_exception(cls):
+
+        cls.batch_size = 5
+        cls.inputs_shape = [cls.batch_size, 400, 400, 3]
+        cls.input_layer = Input(cls.inputs_shape, name='input_layer')
+
+        try:
+            cls.n1 = tl.layers.Conv2dLayer(
+                act='activation', shape=(5, 5, 3, 32), strides=(1, 2, 2, 1), padding='SAME',
+                b_init=tf.constant_initializer(value=0.0), name='conv2dlayer'
+            )(cls.input_layer)
+        except Exception as e:
+            cls.assertIsInstance(e, Exception)
+            print(e)
+
+        try:
+            cls.n2 = tl.layers.Conv2dLayer(
+                act='leaky_relu0.2x', shape=(5, 5, 3, 32), strides=(1, 2, 2, 1), padding='SAME',
+                b_init=tf.constant_initializer(value=0.0), name='conv2dlayer'
+            )(cls.input_layer)
+        except Exception as e:
+            cls.assertIsInstance(e, Exception)
+            print(e)
+
+        try:
+            cls.n3 = tl.layers.Conv2dLayer(
+                act='lrelu0.2x', shape=(5, 5, 3, 32), strides=(1, 2, 2, 1), padding='SAME',
+                b_init=tf.constant_initializer(value=0.0), name='conv2dlayer'
+            )(cls.input_layer)
+        except Exception as e:
+            cls.assertIsInstance(e, Exception)
+            print(e)
+
+
+if __name__ == '__main__':
+
+    tl.logging.set_verbosity(tl.logging.DEBUG)
+
+    unittest.main()
diff --git a/tests/models/test_model_save_graph.py b/tests/models/test_model_save_graph.py
index 95229938b..057ac921f 100644
--- a/tests/models/test_model_save_graph.py
+++ b/tests/models/test_model_save_graph.py
@@ -178,7 +178,7 @@ class Reuse_ModelLayer_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing save_graph, load_graph, including ModelLayer and reuse  #####")
+        print("##### begin testing save_graph, load_graph, including ModelLayer and reuse #####")
 
     def test_save(self):
         input_shape = (None, 784)
@@ -195,7 +195,7 @@ class Vgg_LayerList_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing save_graph, load_graph, including LayerList  #####")
+        print("##### begin testing save_graph, load_graph, including LayerList #####")
 
     def test_save(self):
         M1 = tl.models.vgg16(mode='static')
@@ -211,7 +211,7 @@ class List_inputs_outputs_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing model with list inputs and outputs  #####")
+        print("##### begin testing model with list inputs and outputs #####")
 
     def test_list_inputs_outputs(self):
         ni_1 = Input(shape=[4, 16])
@@ -344,7 +344,7 @@ class ElementWise_lambda_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing elementwise lambda layer  #####")
+        print("##### begin testing elementwise lambda layer #####")
 
     def test_elementwise_no_para_with_args(self):
         # z = mean + noise * tf.exp(std * 0.5) + foo
@@ -467,7 +467,7 @@ class Dynamic_config_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing exception in dynamic mode  #####")
+        print("##### begin testing exception in dynamic mode #####")
 
     def test_dynamic_config(self):
         M1 = basic_dynamic_model()
@@ -480,7 +480,7 @@ class Exception_test(CustomTestCase):
 
     @classmethod
     def setUpClass(cls):
-        print("##### begin testing exception in dynamic mode  #####")
+        print("##### begin testing exception in dynamic mode #####")
 
     def test_exception(self):
         M1 = basic_dynamic_model()