diff --git a/README.md b/README.md
index 5639fb87..44357d6b 100644
--- a/README.md
+++ b/README.md
@@ -19,11 +19,11 @@ from luchador.episode_runner import EpisodeRunner
 
 def main(env, agent, episodes, steps):
     # Create environment
-	Environment = get_env(env['name'])
-	env = Environment(**env['args'])
+    Environment = get_env(env['typename'])
+    env = Environment(**env['args'])
 
     # Create agent
-    Agent = get_agent(agent['name'])
+    Agent = get_agent(agent['typename'])
     agent = Agent(**agent['args'])
     agent.init(env)
 
@@ -109,7 +109,7 @@ $ python
 To use this new agent, we need to create configuration file. As this agent does not take any constructor argument, configuration file is as simple as follow.
 
 ```yaml
-name: MyRandomAgent
+typename: MyRandomAgent
 args: {}
 ```
 
@@ -163,23 +163,20 @@ Network architecture can be described using a set of layer configurations, and w
 model_type: Sequential
 layer_configs:
   - scope: layer1
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
   - scope: layer2
-    layer:
-      name: ReLU
-      args: {}
+    typename: ReLU
+    args: {}
   - scope: layer3
-    layer:
-      name: Dense
-      args:
-        n_nodes: 3
+    typename: Dense
+    args:
+      n_nodes: 3
 ```
 
 You can feed this configuration to `luchador.nn.util.make_model` then the function will return the coresponding network architecture.
@@ -190,23 +187,20 @@ But having static parameters is sometimes inconvenient. For example, although th
 model_type: Sequential
 layer_configs:
   - scope: layer1
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
   - scope: layer2
-    layer:
-      name: ReLU
-      args: {{}}
+    typename: ReLU
+    args: {{}}
   - scope: layer3
-    layer:
-      name: Dense
-      args:
-        n_nodes: {n_actions}
+    typename: Dense
+    args:
+      n_nodes: {n_actions}
 ```
 
 When you load this file with `luchador.nn.util.make_model('model.yml', n_actions=5)`, 5 is substituted at `{n_actions}`. Notice that `ReLU`'s `args` parameter became `{{}}` from `{}` so that it Python's `format` function will replace it to `{}`.
diff --git a/example/ALEEnvironment_test.yml b/example/ALEEnvironment_test.yml
index aae07ded..0f87e767 100644
--- a/example/ALEEnvironment_test.yml
+++ b/example/ALEEnvironment_test.yml
@@ -1,4 +1,4 @@
-name: ALEEnvironment
+typename: ALEEnvironment
 args:
   rom: space_invaders
 
diff --git a/example/ALEEnvironment_train.yml b/example/ALEEnvironment_train.yml
index 47412716..6a688606 100644
--- a/example/ALEEnvironment_train.yml
+++ b/example/ALEEnvironment_train.yml
@@ -1,4 +1,4 @@
-name: ALEEnvironment
+typename: ALEEnvironment
 args:
   rom: space_invaders
 
diff --git a/example/CartPole_agent.yml b/example/CartPole_agent.yml
index 0cc746a9..dc0deaf0 100644
--- a/example/CartPole_agent.yml
+++ b/example/CartPole_agent.yml
@@ -1 +1 @@
-name: CartPoleAgent
+typename: CartPoleAgent
diff --git a/example/CartPole_env.yml b/example/CartPole_env.yml
index d53ea5c3..36576feb 100644
--- a/example/CartPole_env.yml
+++ b/example/CartPole_env.yml
@@ -1,4 +1,4 @@
-name: CartPole
+typename: CartPole
 args:
   angle_limit: 12  # Degree
   distance_limit: 2.4  # meter
diff --git a/example/DQNAgent_test.yml b/example/DQNAgent_test.yml
index a799c201..428f2a60 100644
--- a/example/DQNAgent_test.yml
+++ b/example/DQNAgent_test.yml
@@ -7,7 +7,7 @@ alias:
   save_prefix: &save_prefix DQN_integration_test
   initial_parameter: &initial_parameter example/space_invaders_vanilla_dqn_99000.h5
 
-name: DQNAgent
+typename: DQNAgent
 args:
   recorder_config:
     memory_size: 100
@@ -27,26 +27,27 @@ args:
       terminal:
         dtype: bool
 
+  model_config:
+    model_file: example/vanilla_dqn.yml
+    initial_parameter: *initial_parameter
+    input_channel: *stack
+    input_height: *height
+    input_width: *width
+
   q_network_config:
-    model_config:
-      name: example/vanilla_dqn.yml
-      initial_parameter: *initial_parameter
-      input_channel: *stack
-      input_height: *height
-      input_width: *width
     q_learning_config:
       discount_rate: 0.99
       # reward is clipped between the following min and max
       min_reward: -1.0
       max_reward: 1.0
     cost_config:
-      name: SSE2
+      typename: SSE2
       args:
         # error between predicted Q value and target Q value is clipped by the following min and max
         min_delta: -1.0
         max_delta: 1.0
     optimizer_config:
-      name: NeonRMSProp
+      typename: NeonRMSProp
       args:
         decay: 0.95
         epsilon: 0.000001
diff --git a/example/DQNAgent_train.yml b/example/DQNAgent_train.yml
index 55ad3a7e..f06110ed 100644
--- a/example/DQNAgent_train.yml
+++ b/example/DQNAgent_train.yml
@@ -7,7 +7,7 @@ alias:
   save_prefix: &save_prefix DQN
   initial_parameter: &initial_parameter null
 
-name: DQNAgent
+typename: DQNAgent
 args:
   recorder_config:
     memory_size: 1000000
@@ -27,26 +27,27 @@ args:
       terminal:
         dtype: bool
 
+  model_config:
+    model_file: vanilla_dqn
+    initial_parameter: *initial_parameter
+    input_channel: *stack
+    input_height: *height
+    input_width: *width
+
   q_network_config:
-    model_config:
-      name: vanilla_dqn
-      initial_parameter: *initial_parameter
-      input_channel: *stack
-      input_height: *height
-      input_width: *width
     q_learning_config:
       discount_rate: 0.99
       # reward is clipped between the following min and max
       min_reward: -1.0
       max_reward: 1.0
     cost_config:
-      name: SSE2
+      typename: SSE2
       args:
         # error between predicted Q value and target Q value is clipped by the following min and max
         min_delta: -1.0
         max_delta: 1.0
     optimizer_config:
-      name: NeonRMSProp
+      typename: NeonRMSProp
       args:
         decay: 0.95
         epsilon: 0.000001
diff --git a/example/FlappyBirdEnv.yml b/example/FlappyBirdEnv.yml
index e884adfe..ba0227cb 100644
--- a/example/FlappyBirdEnv.yml
+++ b/example/FlappyBirdEnv.yml
@@ -1,4 +1,4 @@
-name: FlappyBird
+typename: FlappyBird
 args:
   random_seed: null
 
diff --git a/example/MyRandomAgent.yml b/example/MyRandomAgent.yml
index 20aae7dd..818c5c34 100644
--- a/example/MyRandomAgent.yml
+++ b/example/MyRandomAgent.yml
@@ -1 +1 @@
-name: MyRandomAgent
+typename: MyRandomAgent
diff --git a/example/RemoteEnv.yml b/example/RemoteEnv.yml
index 4b608095..7bdf91c3 100644
--- a/example/RemoteEnv.yml
+++ b/example/RemoteEnv.yml
@@ -1,4 +1,4 @@
-name: RemoteEnv
+typename: RemoteEnv
 args:
   host: 0.0.0.0
   port: 12345
diff --git a/example/vanilla_dqn.yml b/example/vanilla_dqn.yml
index 7d3b399b..73d417f1 100644
--- a/example/vanilla_dqn.yml
+++ b/example/vanilla_dqn.yml
@@ -5,100 +5,89 @@ input:
   name: state
 layer_configs:
   - scope: layer0/preprocessing
-    layer:
-      name: TrueDiv
-      args:
-        denom: 255
+    typename: TrueDiv
+    args:
+      denom: 255
   - scope: layer1/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
-        initializers:
-          bias: &initializer1
-            name: Uniform
-            args:
-              # 1 / sqrt(8 * 8 * 32) = 0.022097
-              maxval: 0.022
-              minval: -0.022
-          weight: *initializer1
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
+      initializers:
+        bias: &initializer1
+          typename: Uniform
+          args:
+            # 1 / sqrt(8 * 8 * 32) = 0.022097
+            maxval: 0.022
+            minval: -0.022
+        weight: *initializer1
   - scope: layer1/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer2/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 64
-        filter_width: 4
-        filter_height: 4
-        strides: 2
-        padding: valid
-        initializers:
-          bias: &initializer2
-            name: Uniform
-            args:
-              # 1 / sqrt(4 * 4 * 64) = 0.03125
-              maxval: 0.031
-              minval: -0.031
-          weight: *initializer2
+    typename: Conv2D
+    args:
+      n_filters: 64
+      filter_width: 4
+      filter_height: 4
+      strides: 2
+      padding: valid
+      initializers:
+        bias: &initializer2
+          typename: Uniform
+          args:
+            # 1 / sqrt(4 * 4 * 64) = 0.03125
+            maxval: 0.031
+            minval: -0.031
+        weight: *initializer2
   - scope: layer2/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer3/conv2D
-    layer:
-      name: Conv2D
-      args:
-        filter_width: 3
-        filter_height: 3
-        n_filters: 64
-        strides: 1
-        padding: valid
-        initializers:
-          bias: &initializer3
-            name: Uniform
-            args:
-              # 1 / sqrt(3 * 3 * 64) = 0.04166
-              maxval: 0.042
-              minval: -0.042
-          weight: *initializer3
+    typename: Conv2D
+    args:
+      filter_width: 3
+      filter_height: 3
+      n_filters: 64
+      strides: 1
+      padding: valid
+      initializers:
+        bias: &initializer3
+          typename: Uniform
+          args:
+            # 1 / sqrt(3 * 3 * 64) = 0.04166
+            maxval: 0.042
+            minval: -0.042
+        weight: *initializer3
   - scope: layer3/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer4/flatten
-    layer:
-      name: Flatten
+    typename: Flatten
   - scope: layer5/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: 512
-        initializers:
-          bias: &initializer5
-            name: Uniform
-            args:
-              # 1 / sqrt(3136) = 0.01785
-              # 3136 is expected #inputs to this layer when the input size to layer0 is 84 * 84 * 4
-              maxval: 0.018
-              minval: -0.018
-          weight: *initializer5
+    typename: Dense
+    args:
+      n_nodes: 512
+      initializers:
+        bias: &initializer5
+          typename: Uniform
+          args:
+            # 1 / sqrt(3136) = 0.01785
+            # 3136 is expected #inputs to this layer when the input size to layer0 is 84 * 84 * 4
+            maxval: 0.018
+            minval: -0.018
+        weight: *initializer5
   - scope: layer5/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer6/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: {n_actions}
-        initializers:
-          bias: &initializer6
-            name: Uniform
-            args:
-              # 1 / sqrt(512) = 0.04419
-              maxval: 0.044
-              minval: -0.044
-          weight: *initializer6
+    typename: Dense
+    args:
+      n_nodes: {n_actions}
+      initializers:
+        bias: &initializer6
+          typename: Uniform
+          args:
+            # 1 / sqrt(512) = 0.04419
+            maxval: 0.044
+            minval: -0.044
+        weight: *initializer6
diff --git a/luchador/agent/base.py b/luchador/agent/base.py
index 65db5dcb..bb6ef599 100644
--- a/luchador/agent/base.py
+++ b/luchador/agent/base.py
@@ -96,12 +96,12 @@ def __str__(self):
 }
 
 
-def get_agent(name):
+def get_agent(typename):
     """Retrieve Agent class by name
 
     Parameters
     ----------
-    name : str
+    typename : str
         Name of Agent to retrieve
 
     Returns
@@ -114,11 +114,11 @@ def get_agent(name):
     ValueError
         When Agent with the given name is not found
     """
-    if name in _AGENT_MODULE_MAPPING:
-        module = 'luchador.agent.{:s}'.format(_AGENT_MODULE_MAPPING[name])
+    if typename in _AGENT_MODULE_MAPPING:
+        module = 'luchador.agent.{:s}'.format(_AGENT_MODULE_MAPPING[typename])
         importlib.import_module(module)
 
     for class_ in luchador.util.get_subclasses(BaseAgent):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
-    raise ValueError('Unknown Agent: {}'.format(name))
+    raise ValueError('Unknown Agent: {}'.format(typename))
diff --git a/luchador/agent/dqn.py b/luchador/agent/dqn.py
index b73d5ad8..42df6189 100644
--- a/luchador/agent/dqn.py
+++ b/luchador/agent/dqn.py
@@ -40,6 +40,16 @@ class DQNAgent(luchador.util.StoreMixin, BaseAgent):
         Constructor arguments for
         :class:`luchador.agent.recorder.TransitionRecorder`
 
+    model_config : dict
+        Configuration for model definition.
+
+        name : str
+            The name of network model or path to model definition file.
+        initial_parameter : str
+            Path to HDF5 file which contain the initial parameter values.
+        input_channel, input_height, input_width : int
+            The shape of input to the network
+
     q_network_config : dict
         Constructor arguments for
         :class:`luchador.agent.rl.q_learning.DeepQLearning`
@@ -75,6 +85,7 @@ class DQNAgent(luchador.util.StoreMixin, BaseAgent):
     def __init__(
             self,
             recorder_config,
+            model_config,
             q_network_config,
             action_config,
             training_config,
@@ -86,6 +97,7 @@ def __init__(
         super(DQNAgent, self).__init__()
         self._store_args(
             recorder_config=recorder_config,
+            model_config=model_config,
             q_network_config=q_network_config,
             action_config=action_config,
             training_config=training_config,
@@ -122,15 +134,28 @@ def init(self, env):
         self._init_summary_writer()
         self._summarize_layer_params()
 
+    def _gen_model_def(self, n_actions):
+        cfg = self.args['model_config']
+        fmt = luchador.get_nn_conv_format()
+        w, h, c = cfg['input_width'], cfg['input_height'], cfg['input_channel']
+        shape = (
+            '[null, {}, {}, {}]'.format(h, w, c) if fmt == 'NHWC' else
+            '[null, {}, {}, {}]'.format(c, h, w)
+        )
+        return nn.get_model_config(
+            cfg['model_file'], n_actions=n_actions, input_shape=shape)
+
     def _init_network(self, n_actions):
         cfg = self.args['q_network_config']
         self._ql = DeepQLearning(
-            model_config=cfg['model_config'],
             q_learning_config=cfg['q_learning_config'],
             cost_config=cfg['cost_config'],
             optimizer_config=cfg['optimizer_config'],
         )
-        self._ql.build(n_actions=n_actions)
+
+        model_def = self._gen_model_def(n_actions)
+        initial_parameter = self.args['model_config']['initial_parameter']
+        self._ql.build(model_def, initial_parameter)
         self._ql.sync_network()
 
     def _init_saver(self):
diff --git a/luchador/agent/rl/q_learning.py b/luchador/agent/rl/q_learning.py
index fc393677..4f6af09f 100644
--- a/luchador/agent/rl/q_learning.py
+++ b/luchador/agent/rl/q_learning.py
@@ -46,16 +46,6 @@ class DeepQLearning(luchador.util.StoreMixin, object):
 
     Parameters
     ----------
-    model_config : dict
-        Configuration for model definition.
-
-        name : str
-            The name of network model or path to model definition file.
-        initial_parameter : str
-            Path to HDF5 file which contain the initial parameter values.
-        input_channel, input_height, input_width : int
-            The shape of input to the network
-
     q_learning_config : dict
         Configuration for building target Q value.
 
@@ -90,10 +80,8 @@ class DeepQLearning(luchador.util.StoreMixin, object):
     """
     # pylint: disable=too-many-instance-attributes
     def __init__(
-            self, model_config, q_learning_config, cost_config,
-            optimizer_config):
+            self, q_learning_config, cost_config, optimizer_config):
         self._store_args(
-            model_config=model_config,
             q_learning_config=q_learning_config,
             cost_config=cost_config,
             optimizer_config=optimizer_config,
@@ -117,7 +105,7 @@ def __call__(self, q_network_maker):
         """
         self.build(q_network_maker)
 
-    def build(self, n_actions):
+    def build(self, model_def, initial_parameter):
         """Build computation graph (error and sync ops) for Q learning
 
         Parameters
@@ -126,7 +114,6 @@ def build(self, n_actions):
             The number of available actions in the environment.
         """
         # pylint: disable=too-many-locals
-        model_def = self._gen_model_def(n_actions)
         model_0, state_0, action_value_0 = _make_model(model_def, 'pre_trans')
         model_1, state_1, action_value_1 = _make_model(model_def, 'post_trans')
         sync_op = _build_sync_op(model_0, model_1, 'sync')
@@ -144,7 +131,7 @@ def build(self, n_actions):
         self._init_optimizer()
         optimize_op = self.optimizer.minimize(
             error, wrt=model_0.get_parameter_variables())
-        self._init_session()
+        self._init_session(initial_parameter)
 
         self.models = {
             'model_0': model_0,
@@ -166,17 +153,6 @@ def build(self, n_actions):
             'optimize': optimize_op,
         }
 
-    def _gen_model_def(self, n_actions):
-        cfg = self.args['model_config']
-        fmt = luchador.get_nn_conv_format()
-        w, h, c = cfg['input_width'], cfg['input_height'], cfg['input_channel']
-        shape = (
-            '[null, {}, {}, {}]'.format(h, w, c) if fmt == 'NHWC' else
-            '[null, {}, {}, {}]'.format(c, h, w)
-        )
-        return nn.get_model_config(
-            cfg['name'], n_actions=n_actions, input_shape=shape)
-
     def _build_target_q_value(self, action_value_1, reward, terminal):
         config = self.args['q_learning_config']
         # Clip rewrads
@@ -197,22 +173,22 @@ def _build_target_q_value(self, action_value_1, reward, terminal):
 
     def _build_error(self, target_q, action_value_0, action):
         config = self.args['cost_config']
-        sse2 = nn.get_cost(config['name'])(elementwise=True, **config['args'])
-        error = sse2(target_q, action_value_0)
+        args = config['args']
+        cost = nn.get_cost(config['typename'])(elementwise=True, **args)
+        error = cost(target_q, action_value_0)
         mask = action.one_hot(n_classes=action_value_0.shape[1])
         return (mask * error).mean()
 
     ###########################################################################
     def _init_optimizer(self):
         cfg = self.args['optimizer_config']
-        self.optimizer = nn.get_optimizer(cfg['name'])(**cfg['args'])
+        self.optimizer = nn.get_optimizer(cfg['typename'])(**cfg['args'])
 
-    def _init_session(self):
-        cfg = self.args['model_config']
+    def _init_session(self, initial_parameter=None):
         self.session = nn.Session()
-        if cfg.get('initial_parameter'):
-            _LG.info('Loading parameters from %s', cfg['initial_parameter'])
-            self.session.load_from_file(cfg['initial_parameter'])
+        if initial_parameter:
+            _LG.info('Loading parameters from %s', initial_parameter)
+            self.session.load_from_file(initial_parameter)
         else:
             self.session.initialize()
 
diff --git a/luchador/command/exercise.py b/luchador/command/exercise.py
index 1d7d7ad3..eb47714e 100644
--- a/luchador/command/exercise.py
+++ b/luchador/command/exercise.py
@@ -62,19 +62,19 @@ def _load_additional_sources(*files):
 def _make_agent(config_file):
     config = (
         load_config(config_file) if config_file else
-        {'name': 'NoOpAgent', 'args': {}}
+        {'typename': 'NoOpAgent', 'args': {}}
     )
-    return get_agent(config['name'])(**config.get('args', {}))
+    return get_agent(config['typename'])(**config.get('args', {}))
 
 
 def _make_env(config_file, host, port):
     config = load_config(config_file)
-    if config['name'] == 'RemoteEnv':
+    if config['typename'] == 'RemoteEnv':
         if port:
             config['args']['port'] = port
         if host:
             config['args']['host'] = host
-    return get_env(config['name'])(**config.get('args', {}))
+    return get_env(config['typename'])(**config.get('args', {}))
 
 
 def entry_point(args):
diff --git a/luchador/command/serve.py b/luchador/command/serve.py
index c4c336be..9dbfd269 100644
--- a/luchador/command/serve.py
+++ b/luchador/command/serve.py
@@ -27,7 +27,7 @@ def entry_point_env(args):
     if args.environment is None:
         raise ValueError('Environment config is not given')
     env_config = luchador.util.load_config(args.environment)
-    env = luchador.env.get_env(env_config['name'])(**env_config['args'])
+    env = luchador.env.get_env(env_config['typename'])(**env_config['args'])
     app = luchador.env.remote.create_env_app(env)
     _run_server(app, args.port)
 
diff --git a/luchador/env/base.py b/luchador/env/base.py
index 0eb4da41..53620c63 100644
--- a/luchador/env/base.py
+++ b/luchador/env/base.py
@@ -74,12 +74,12 @@ def step(self, action):
 }
 
 
-def get_env(name):
-    """Retrieve Environment class by name
+def get_env(typename):
+    """Retrieve Environment class by typename
 
     Parameters
     ----------
-    name : str
+    typename : str
         Name of Environment to retrieve
 
     Returns
@@ -97,12 +97,13 @@ def get_env(name):
     # Ubuntu 14.04.
     # TLS Error is avoidable only by upgrading underlying libc version, which
     # is not easy. So we import such environments on-demand.
-    if name in _ENVIRONMENT_MODULE_MAPPING:
-        module = 'luchador.env.{:s}'.format(_ENVIRONMENT_MODULE_MAPPING[name])
+    if typename in _ENVIRONMENT_MODULE_MAPPING:
+        module = 'luchador.env.{:s}'.format(
+            _ENVIRONMENT_MODULE_MAPPING[typename])
         importlib.import_module(module)
 
     for class_ in luchador.util.get_subclasses(BaseEnvironment):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
 
-    raise ValueError('Unknown Environment: {}'.format(name))
+    raise ValueError('Unknown Environment: {}'.format(typename))
diff --git a/luchador/nn/base/cost.py b/luchador/nn/base/cost.py
index 6a69b5dd..e6c614f6 100644
--- a/luchador/nn/base/cost.py
+++ b/luchador/nn/base/cost.py
@@ -52,13 +52,13 @@ def _build(self, target, prediction):
         pass
 
 
-def get_cost(name):
-    """Retrieve Cost class by name
+def get_cost(typename):
+    """Retrieve Cost class by type
 
     Parameters
     ----------
-    name : str
-        Name of Cost to retrieve
+    typename : str
+        Type of Cost to retrieve
 
     Returns
     -------
@@ -68,12 +68,12 @@ def get_cost(name):
     Raises
     ------
     ValueError
-        When Cost with the given name is not found
+        When Cost with the given type is not found
     """
     for class_ in luchador.util.get_subclasses(BaseCost):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
-    raise ValueError('Unknown Cost: {}'.format(name))
+    raise ValueError('Unknown Cost: {}'.format(typename))
 
 
 ###############################################################################
diff --git a/luchador/nn/base/initializer.py b/luchador/nn/base/initializer.py
index 61f22cc2..01f66d71 100644
--- a/luchador/nn/base/initializer.py
+++ b/luchador/nn/base/initializer.py
@@ -48,13 +48,13 @@ def _sample(self, shape):
         pass
 
 
-def get_initializer(name):
-    """Retrieve Initializer class by name
+def get_initializer(typename):
+    """Retrieve Initializer class by type
 
     Parameters
     ----------
-    name : str
-        Name of Initializer to retrieve
+    typename : str
+        Type of Initializer to retrieve
 
     Returns
     -------
@@ -64,12 +64,12 @@ def get_initializer(name):
     Raises
     ------
     ValueError
-        When Initializer with the given name is not found
+        When Initializer with the given type is not found
     """
     for class_ in luchador.util.get_subclasses(BaseInitializer):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
-    raise ValueError('Unknown Initializer: {}'.format(name))
+    raise ValueError('Unknown Initializer: {}'.format(typename))
 
 
 ###############################################################################
diff --git a/luchador/nn/base/layer.py b/luchador/nn/base/layer.py
index dfa4f01c..d1eececd 100644
--- a/luchador/nn/base/layer.py
+++ b/luchador/nn/base/layer.py
@@ -84,13 +84,13 @@ def _build(self, input_tensor):
         )
 
 
-def get_layer(name):
-    """Retrieve Layer class by name
+def get_layer(typename):
+    """Retrieve Layer class by type
 
     Parameters
     ----------
-    name : str
-        Name of Layer to retrieve
+    typename : str
+        Type of Layer to retrieve
 
     Returns
     -------
@@ -100,12 +100,12 @@ def get_layer(name):
     Raises
     ------
     ValueError
-        When Layer with the given name is not found
+        When Layer with the given type is not found
     """
     for class_ in luchador.util.get_subclasses(BaseLayer):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
-    raise ValueError('Unknown Layer: {}'.format(name))
+    raise ValueError('Unknown Layer: {}'.format(typename))
 
 
 ###############################################################################
diff --git a/luchador/nn/base/optimizer.py b/luchador/nn/base/optimizer.py
index 497138ec..7a76d690 100644
--- a/luchador/nn/base/optimizer.py
+++ b/luchador/nn/base/optimizer.py
@@ -113,13 +113,13 @@ def get_parameter_variables(self):
         return self.slot
 
 
-def get_optimizer(name):
-    """Retrieve Optimizer class by name
+def get_optimizer(typename):
+    """Retrieve Optimizer class by type
 
     Parameters
     ----------
-    name : str
-        Name of Optimizer to retrieve
+    typename : str
+        Type of Optimizer to retrieve
 
     Returns
     -------
@@ -129,12 +129,12 @@ def get_optimizer(name):
     Raises
     ------
     ValueError
-        When Optimizer with the given name is not found
+        When Optimizer with the given type is not found
     """
     for class_ in luchador.util.get_subclasses(BaseOptimizer):
-        if class_.__name__ == name:
+        if class_.__name__ == typename:
             return class_
-    raise ValueError('Unknown Optimizer: {}'.format(name))
+    raise ValueError('Unknown Optimizer: {}'.format(typename))
 
 
 ###############################################################################
@@ -264,6 +264,14 @@ def __init__(self, learning_rate,
 
 
 class BaseAdam(BaseOptimizer):
+    """Adam optimizer [1]_
+
+    References
+    ----------
+    .. [1] Kingma, D. Ba, J 2014
+        Adam: A Method for Stochastic Optimization
+        https://arxiv.org/abs/1412.6980
+    """
     def __init__(self, learning_rate,
                  beta1=0.9, beta2=0.999,
                  epsilon=1e-08, name='Adam', **kwargs):
@@ -273,6 +281,14 @@ def __init__(self, learning_rate,
 
 
 class BaseAdamax(BaseOptimizer):
+    """Adam optimizer [1]_
+
+    References
+    ----------
+    .. [1] Kingma, D. Ba, J 2014
+        Adam: A Method for Stochastic Optimization
+        https://arxiv.org/abs/1412.6980
+    """
     def __init__(self, learning_rate,
                  beta1=0.9, beta2=0.999,
                  epsilon=1e-8, name='Adamax', **kwargs):
diff --git a/luchador/nn/model/data/vanilla_dqn.yml b/luchador/nn/model/data/vanilla_dqn.yml
index d0e8a5ba..2baeb609 100644
--- a/luchador/nn/model/data/vanilla_dqn.yml
+++ b/luchador/nn/model/data/vanilla_dqn.yml
@@ -1,65 +1,54 @@
 model_type: Sequential
 input:
-  name: Input
+  typename: Input
   args:
     dtype: uint8
     shape: {input_shape}
     name: state
 layer_configs:
   - scope: layer0/preprocessing
-    layer:
-      name: TrueDiv
-      args:
-        denom: 255
+    typename: TrueDiv
+    args:
+      denom: 255
   - scope: layer1/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
   - scope: layer1/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer2/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 64
-        filter_width: 4
-        filter_height: 4
-        strides: 2
-        padding: valid
+    typename: Conv2D
+    args:
+      n_filters: 64
+      filter_width: 4
+      filter_height: 4
+      strides: 2
+      padding: valid
   - scope: layer2/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer3/conv2D
-    layer:
-      name: Conv2D
-      args:
-        filter_width: 3
-        filter_height: 3
-        n_filters: 64
-        strides: 1
-        padding: valid
+    typename: Conv2D
+    args:
+      filter_width: 3
+      filter_height: 3
+      n_filters: 64
+      strides: 1
+      padding: valid
   - scope: layer3/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer4/flatten
-    layer:
-      name: Flatten
+    typename: Flatten
   - scope: layer5/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: 512
+    typename: Dense
+    args:
+      n_nodes: 512
   - scope: layer5/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer6/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: {n_actions}
+    typename: Dense
+    args:
+      n_nodes: {n_actions}
diff --git a/luchador/nn/model/data/vanilla_dqn_bn.yml b/luchador/nn/model/data/vanilla_dqn_bn.yml
index a9845e45..74674ec0 100644
--- a/luchador/nn/model/data/vanilla_dqn_bn.yml
+++ b/luchador/nn/model/data/vanilla_dqn_bn.yml
@@ -1,79 +1,78 @@
 model_type: Sequential
 input:
-  dtype: uint8
-  shape: {input_shape}
-  name: state
+  typename: Input
+  args:
+    dtype: uint8
+    shape: {input_shape}
+    name: state
 layer_configs:
   - scope: layer0/preprocessing
-    layer:
-      name: TrueDiv
-      args:
-        denom: 255
+    typename: TrueDiv
+    args:
+      denom: 255
   - scope: layer1/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
-        with_bias: False
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
+      with_bias: False
   - scope: layer1/BN
-    layer: &BN
-      name: BatchNormalization
-      args:
-        learn: True
-        decay: 0.999
+    typename: BatchNormalization
+    args:
+      learn: True
+      decay: 0.999
   - scope: layer1/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer2/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 64
-        filter_width: 4
-        filter_height: 4
-        strides: 2
-        padding: valid
-        with_bias: False
+    typename: Conv2D
+    args:
+      n_filters: 64
+      filter_width: 4
+      filter_height: 4
+      strides: 2
+      padding: valid
+      with_bias: False
   - scope: layer2/BN
-    layer: *BN
+    typename: BatchNormalization
+    args:
+      learn: True
+      decay: 0.999
   - scope: layer2/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer3/conv2D
-    layer:
-      name: Conv2D
-      args:
-        filter_width: 3
-        filter_height: 3
-        n_filters: 64
-        strides: 1
-        padding: valid
-        with_bias: False
+    typename: Conv2D
+    args:
+      filter_width: 3
+      filter_height: 3
+      n_filters: 64
+      strides: 1
+      padding: valid
+      with_bias: False
   - scope: layer3/BN
-    layer: *BN
+    typename: BatchNormalization
+    args:
+      learn: True
+      decay: 0.999
   - scope: layer3/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer4/flatten
-    layer:
-      name: Flatten
+    typename: Flatten
   - scope: layer5/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: 512
-        with_bias: False
+    typename: Dense
+    args:
+      n_nodes: 512
+      with_bias: False
   - scope: layer5/BN
-    layer: *BN
+    typename: BatchNormalization
+    args:
+      learn: True
+      decay: 0.999
   - scope: layer5/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer6/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: {n_actions}
+    typename: Dense
+    args:
+      n_nodes: {n_actions}
diff --git a/luchador/nn/model/sequential.py b/luchador/nn/model/sequential.py
index 7e5edbff..30c5304e 100644
--- a/luchador/nn/model/sequential.py
+++ b/luchador/nn/model/sequential.py
@@ -36,6 +36,11 @@ def __repr__(self):
             'output': self.output,
         })
 
+    def serialize(self):
+        ret = self.layer.serialize()
+        ret['scope'] = self.scope
+        return ret
+
 
 class Sequential(BaseModel):
     """Network architecture which produces single output from single input
@@ -243,10 +248,7 @@ def serialize(self):
         """
         return {
             'model_type': self.__class__.__name__,
-            'layer_configs': [{
-                'scope': cfg.scope,
-                'layer': cfg.layer.serialize(),
-            } for cfg in self.layer_configs]
+            'layer_configs': [cfg.serialize() for cfg in self.layer_configs]
         }
 
     ###########################################################################
@@ -271,12 +273,12 @@ def make_sequential_model(layer_configs):
         Resulting model
     """
     model = Sequential()
-    for layer_config in layer_configs:
-        layer_cfg = layer_config['layer']
-        if 'name' not in layer_cfg:
+    for config in layer_configs:
+        if 'typename' not in config:
             raise RuntimeError('Layer name is not given')
-        args = layer_cfg.get('args', {})
-        _LG.debug('    Constructing: %s: %s', layer_cfg['name'], args)
-        layer = get_layer(layer_cfg['name'])(**args)
-        model.add_layer(layer=layer, scope=layer_config.get('scope', ''))
+        args = config.get('args', {})
+
+        _LG.debug('    Constructing: %s: %s', config['typename'], args)
+        layer = get_layer(config['typename'])(**args)
+        model.add_layer(layer=layer, scope=config.get('scope', ''))
     return model
diff --git a/luchador/nn/model/util.py b/luchador/nn/model/util.py
index f242a272..d0db23e6 100644
--- a/luchador/nn/model/util.py
+++ b/luchador/nn/model/util.py
@@ -30,7 +30,7 @@ def _get_input():
 
 
 def _make_input(input_config):
-    if input_config['name'] == 'Input':
+    if input_config['typename'] == 'Input':
         return _get_input()(**input_config['args'])
 
 
diff --git a/luchador/util/mixin.py b/luchador/util/mixin.py
index aaea1702..d37730d0 100644
--- a/luchador/util/mixin.py
+++ b/luchador/util/mixin.py
@@ -133,6 +133,6 @@ def serialize(self):
         for key, val in self.args.items():
             args[key] = val.serialize() if hasattr(val, 'serialize') else val
         return {
-            'name': self.__class__.__name__,
+            'typename': self.__class__.__name__,
             'args': args
         }
diff --git a/tests/integration/data/dqn/ALEEnvironment_train.yml b/tests/integration/data/dqn/ALEEnvironment_train.yml
index 47412716..6a688606 100644
--- a/tests/integration/data/dqn/ALEEnvironment_train.yml
+++ b/tests/integration/data/dqn/ALEEnvironment_train.yml
@@ -1,4 +1,4 @@
-name: ALEEnvironment
+typename: ALEEnvironment
 args:
   rom: space_invaders
 
diff --git a/tests/integration/data/dqn/DQNAgent_train.yml b/tests/integration/data/dqn/DQNAgent_train.yml
index 342e43b7..a6497c48 100644
--- a/tests/integration/data/dqn/DQNAgent_train.yml
+++ b/tests/integration/data/dqn/DQNAgent_train.yml
@@ -7,7 +7,7 @@ alias:
   save_prefix: &save_prefix DQN_integration_test
   initial_parameter: &initial_parameter tests/integration/data/dqn/dqn_integration_test_initial.h5
 
-name: DQNAgent
+typename: DQNAgent
 args:
   recorder_config:
     memory_size: 100
@@ -27,26 +27,27 @@ args:
       terminal:
         dtype: bool
 
+  model_config:
+    model_file: vanilla_dqn
+    initial_parameter: *initial_parameter
+    input_channel: *stack
+    input_height: *height
+    input_width: *width
+
   q_network_config:
-    model_config:
-      name: vanilla_dqn
-      initial_parameter: *initial_parameter
-      input_channel: *stack
-      input_height: *height
-      input_width: *width
     q_learning_config:
       discount_rate: 0.99
       # reward is clipped between the following min and max
       min_reward: -1.0
       max_reward: 1.0
     cost_config:
-      name: SSE2
+      typename: SSE2
       args:
         # error between predicted Q value and target Q value is clipped by the following min and max
         min_delta: -1.0
         max_delta: 1.0
     optimizer_config:
-      name: RMSProp
+      typename: RMSProp
       args:
         decay: 0.95
         epsilon: 0.000001
diff --git a/tests/integration/data/env/cartpole/agent.yml b/tests/integration/data/env/cartpole/agent.yml
index 0cc746a9..dc0deaf0 100644
--- a/tests/integration/data/env/cartpole/agent.yml
+++ b/tests/integration/data/env/cartpole/agent.yml
@@ -1 +1 @@
-name: CartPoleAgent
+typename: CartPoleAgent
diff --git a/tests/integration/data/env/cartpole/env.yml b/tests/integration/data/env/cartpole/env.yml
index bc5ddc11..67015163 100644
--- a/tests/integration/data/env/cartpole/env.yml
+++ b/tests/integration/data/env/cartpole/env.yml
@@ -1,4 +1,4 @@
-name: CartPole
+typename: CartPole
 args:
   angle_limit: 12  # Degree
   distance_limit: 2.4  # meter
diff --git a/tests/integration/data/initializer/constant.yml b/tests/integration/data/initializer/constant.yml
index 561323c0..306d2daf 100644
--- a/tests/integration/data/initializer/constant.yml
+++ b/tests/integration/data/initializer/constant.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Constant
+  typename: Constant
   args:
     value: 3.2
 
diff --git a/tests/integration/data/initializer/kaiming_conv2d_normal.yml b/tests/integration/data/initializer/kaiming_conv2d_normal.yml
index bc1699cc..304f6312 100644
--- a/tests/integration/data/initializer/kaiming_conv2d_normal.yml
+++ b/tests/integration/data/initializer/kaiming_conv2d_normal.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Kaiming
+  typename: Kaiming
   args:
     uniform: False
 
diff --git a/tests/integration/data/initializer/kaiming_conv2d_uniform.yml b/tests/integration/data/initializer/kaiming_conv2d_uniform.yml
index ec19facf..637cb427 100644
--- a/tests/integration/data/initializer/kaiming_conv2d_uniform.yml
+++ b/tests/integration/data/initializer/kaiming_conv2d_uniform.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Kaiming
+  typename: Kaiming
   args:
     uniform: True
 
diff --git a/tests/integration/data/initializer/kaiming_normal.yml b/tests/integration/data/initializer/kaiming_normal.yml
index 473edb74..bbe17a8d 100644
--- a/tests/integration/data/initializer/kaiming_normal.yml
+++ b/tests/integration/data/initializer/kaiming_normal.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Kaiming
+  typename: Kaiming
   args:
     uniform: False
 
diff --git a/tests/integration/data/initializer/kaiming_uniform.yml b/tests/integration/data/initializer/kaiming_uniform.yml
index 9968844f..e2198908 100644
--- a/tests/integration/data/initializer/kaiming_uniform.yml
+++ b/tests/integration/data/initializer/kaiming_uniform.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Kaiming
+  typename: Kaiming
   args:
     uniform: True
 
diff --git a/tests/integration/data/initializer/normal.yml b/tests/integration/data/initializer/normal.yml
index d7edcc4c..8b9f9e61 100644
--- a/tests/integration/data/initializer/normal.yml
+++ b/tests/integration/data/initializer/normal.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Normal
+  typename: Normal
   args:
     mean: &mean 5.3
     stddev: &stddev 9.0
diff --git a/tests/integration/data/initializer/uniform.yml b/tests/integration/data/initializer/uniform.yml
index ffe6b3fb..aad2be74 100644
--- a/tests/integration/data/initializer/uniform.yml
+++ b/tests/integration/data/initializer/uniform.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Uniform
+  typename: Uniform
   args:
     minval: -2.0 
     maxval: 6.0
diff --git a/tests/integration/data/initializer/xavier_conv2d_normal.yml b/tests/integration/data/initializer/xavier_conv2d_normal.yml
index aa18b971..9f703d0d 100644
--- a/tests/integration/data/initializer/xavier_conv2d_normal.yml
+++ b/tests/integration/data/initializer/xavier_conv2d_normal.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Xavier
+  typename: Xavier
   args:
     uniform: False
 
diff --git a/tests/integration/data/initializer/xavier_conv2d_uniform.yml b/tests/integration/data/initializer/xavier_conv2d_uniform.yml
index 579129e4..a6135d99 100644
--- a/tests/integration/data/initializer/xavier_conv2d_uniform.yml
+++ b/tests/integration/data/initializer/xavier_conv2d_uniform.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Xavier
+  typename: Xavier
   args:
     uniform: True
 
diff --git a/tests/integration/data/initializer/xavier_normal.yml b/tests/integration/data/initializer/xavier_normal.yml
index 0ee59e11..d8adf64e 100644
--- a/tests/integration/data/initializer/xavier_normal.yml
+++ b/tests/integration/data/initializer/xavier_normal.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Xavier
+  typename: Xavier
   args:
     uniform: False
 
diff --git a/tests/integration/data/initializer/xavier_uniform.yml b/tests/integration/data/initializer/xavier_uniform.yml
index 2a637551..f3101fdf 100644
--- a/tests/integration/data/initializer/xavier_uniform.yml
+++ b/tests/integration/data/initializer/xavier_uniform.yml
@@ -1,5 +1,5 @@
 initializer:
-  name: Xavier
+  typename: Xavier
   args:
     uniform: True
 
diff --git a/tests/integration/data/layer/batch_normalization_2d_learn.yml b/tests/integration/data/layer/batch_normalization_2d_learn.yml
index 285be4a6..909db718 100644
--- a/tests/integration/data/layer/batch_normalization_2d_learn.yml
+++ b/tests/integration/data/layer/batch_normalization_2d_learn.yml
@@ -2,7 +2,7 @@ run:
   iteration: 10
 
 layer:
-  name: BatchNormalization
+  typename: BatchNormalization
   args:
     scale: 2.0
     offset: 0.5
diff --git a/tests/integration/data/layer/batch_normalization_2d_not_learn.yml b/tests/integration/data/layer/batch_normalization_2d_not_learn.yml
index 2960c83e..504ec7bf 100644
--- a/tests/integration/data/layer/batch_normalization_2d_not_learn.yml
+++ b/tests/integration/data/layer/batch_normalization_2d_not_learn.yml
@@ -2,7 +2,7 @@ run:
   iteration: 10
 
 layer:
-  name: BatchNormalization
+  typename: BatchNormalization
   args:
     scale: 2.0
     offset: 0.5
diff --git a/tests/integration/data/layer/batch_normalization_4d_learn.yml b/tests/integration/data/layer/batch_normalization_4d_learn.yml
index 285be4a6..909db718 100644
--- a/tests/integration/data/layer/batch_normalization_4d_learn.yml
+++ b/tests/integration/data/layer/batch_normalization_4d_learn.yml
@@ -2,7 +2,7 @@ run:
   iteration: 10
 
 layer:
-  name: BatchNormalization
+  typename: BatchNormalization
   args:
     scale: 2.0
     offset: 0.5
diff --git a/tests/integration/data/layer/batch_normalization_4d_not_learn.yml b/tests/integration/data/layer/batch_normalization_4d_not_learn.yml
index 2960c83e..504ec7bf 100644
--- a/tests/integration/data/layer/batch_normalization_4d_not_learn.yml
+++ b/tests/integration/data/layer/batch_normalization_4d_not_learn.yml
@@ -2,7 +2,7 @@ run:
   iteration: 10
 
 layer:
-  name: BatchNormalization
+  typename: BatchNormalization
   args:
     scale: 2.0
     offset: 0.5
diff --git a/tests/integration/data/layer/conv2d_same.yml b/tests/integration/data/layer/conv2d_same.yml
index 6932c976..10989564 100644
--- a/tests/integration/data/layer/conv2d_same.yml
+++ b/tests/integration/data/layer/conv2d_same.yml
@@ -1,5 +1,5 @@
 layer:
-  name: Conv2D
+  typename: Conv2D
   args:
     filter_height: 7
     filter_width: 5
diff --git a/tests/integration/data/layer/conv2d_valid.yml b/tests/integration/data/layer/conv2d_valid.yml
index fed44ee3..26c2f02c 100644
--- a/tests/integration/data/layer/conv2d_valid.yml
+++ b/tests/integration/data/layer/conv2d_valid.yml
@@ -1,5 +1,5 @@
 layer:
-  name: Conv2D
+  typename: Conv2D
   args:
     filter_height: 7
     filter_width: 5
diff --git a/tests/integration/data/layer/conv2d_without_bias.yml b/tests/integration/data/layer/conv2d_without_bias.yml
index dbf55104..9ded5730 100644
--- a/tests/integration/data/layer/conv2d_without_bias.yml
+++ b/tests/integration/data/layer/conv2d_without_bias.yml
@@ -1,5 +1,5 @@
 layer:
-  name: Conv2D
+  typename: Conv2D
   args:
     filter_height: 7
     filter_width: 5
diff --git a/tests/integration/data/layer/dense.yml b/tests/integration/data/layer/dense.yml
index 8d88c5f9..e9dab38f 100644
--- a/tests/integration/data/layer/dense.yml
+++ b/tests/integration/data/layer/dense.yml
@@ -1,5 +1,5 @@
 layer:
-  name: Dense
+  typename: Dense
   args:
     n_nodes: 7
     with_bias: True
diff --git a/tests/integration/data/layer/dense_without_bias.yml b/tests/integration/data/layer/dense_without_bias.yml
index f319b608..430d34dc 100644
--- a/tests/integration/data/layer/dense_without_bias.yml
+++ b/tests/integration/data/layer/dense_without_bias.yml
@@ -1,5 +1,5 @@
 layer:
-  name: Dense
+  typename: Dense
   args:
     n_nodes: 7
     with_bias: False
diff --git a/tests/integration/data/layer/flatten.yml b/tests/integration/data/layer/flatten.yml
index 19192d9e..8dec35c0 100644
--- a/tests/integration/data/layer/flatten.yml
+++ b/tests/integration/data/layer/flatten.yml
@@ -1,4 +1,4 @@
 layer:
-  name: Flatten
+  typename: Flatten
 
 input: input_mnist_10x4x28x27.h5
diff --git a/tests/integration/data/layer/relu.yml b/tests/integration/data/layer/relu.yml
index 9726c362..1be06380 100644
--- a/tests/integration/data/layer/relu.yml
+++ b/tests/integration/data/layer/relu.yml
@@ -1,4 +1,4 @@
 layer:
-  name: ReLU
+  typename: ReLU
 
 input: input_randn_5x3.h5
diff --git a/tests/integration/data/layer/sigmoid.yml b/tests/integration/data/layer/sigmoid.yml
index 23185f07..dc195a5b 100644
--- a/tests/integration/data/layer/sigmoid.yml
+++ b/tests/integration/data/layer/sigmoid.yml
@@ -1,4 +1,4 @@
 layer:
-  name: Sigmoid
+  typename: Sigmoid
 
 input: input_randn_5x3.h5
diff --git a/tests/integration/data/layer/softmax.yml b/tests/integration/data/layer/softmax.yml
index f6d5f006..ff623fc9 100644
--- a/tests/integration/data/layer/softmax.yml
+++ b/tests/integration/data/layer/softmax.yml
@@ -1,4 +1,4 @@
 layer:
-  name: Softmax
+  typename: Softmax
 
 input: input_randn_5x3.h5
diff --git a/tests/integration/data/layer/softplus.yml b/tests/integration/data/layer/softplus.yml
index b71ce69b..375bdbef 100644
--- a/tests/integration/data/layer/softplus.yml
+++ b/tests/integration/data/layer/softplus.yml
@@ -1,4 +1,4 @@
 layer:
-  name: Softplus
+  typename: Softplus
 
 input: input_randn_5x3.h5
diff --git a/tests/integration/data/layer/tanh.yml b/tests/integration/data/layer/tanh.yml
index 5040bb43..466cb50f 100644
--- a/tests/integration/data/layer/tanh.yml
+++ b/tests/integration/data/layer/tanh.yml
@@ -1,4 +1,4 @@
 layer:
-  name: Tanh
+  typename: Tanh
 
 input: input_randn_5x3.h5
diff --git a/tests/integration/data/layer/true_div.yml b/tests/integration/data/layer/true_div.yml
index 9b172d11..efab0b3f 100644
--- a/tests/integration/data/layer/true_div.yml
+++ b/tests/integration/data/layer/true_div.yml
@@ -1,5 +1,5 @@
 layer:
-  name: TrueDiv
+  typename: TrueDiv
   args:
     denom: 255
 
diff --git a/tests/integration/data/model/dqn.yml b/tests/integration/data/model/dqn.yml
index 275f1783..6530524c 100644
--- a/tests/integration/data/model/dqn.yml
+++ b/tests/integration/data/model/dqn.yml
@@ -1,71 +1,59 @@
 model_type: Sequential
 input:
-  name: Input
+  typename: Input
   args:
     dtype: uint8
     shape: {input_shape}
     name: state
 layer_configs:
   - scope: layer0/preprocessing
-    layer:
-      name: TrueDiv
-      args:
-        denom: 255
+    typename: TrueDiv
+    args:
+      denom: 255
   - scope: layer1/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 32
-        filter_width: 8
-        filter_height: 8
-        strides: 4
-        padding: valid
+    typename: Conv2D
+    args:
+      n_filters: 32
+      filter_width: 8
+      filter_height: 8
+      strides: 4
+      padding: valid
   - scope: layer1/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer2/conv2D
-    layer:
-      name: Conv2D
-      args:
-        n_filters: 64
-        filter_width: 4
-        filter_height: 4
-        strides: 2
-        padding: valid
-        with_bias: False
+    typename: Conv2D
+    args:
+      n_filters: 64
+      filter_width: 4
+      filter_height: 4
+      strides: 2
+      padding: valid
+      with_bias: False
   - scope: layer2/BatchNormalization
-    layer:
-      name: BatchNormalization
-      args:
-        learn: True
+    typename: BatchNormalization
+    args:
+      learn: True
   - scope: layer2/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer3/flatten
-    layer:
-      name: Flatten
+    typename: Flatten
   - scope: layer4/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: 512
-        with_bias: False
+    typename: Dense
+    args:
+      n_nodes: 512
+      with_bias: False
   - scope: layer4/BatchNormalization
-    layer:
-      name: BatchNormalization
-      args:
-        learn: True
+    typename: BatchNormalization
+    args:
+      learn: True
   - scope: layer4/ReLU
-    layer:
-      name: ReLU
+    typename: ReLU
   - scope: layer5/dense
-    layer:
-      name: Dense
-      args:
-        n_nodes: {n_actions}
-        with_bias: False
+    typename: Dense
+    args:
+      n_nodes: {n_actions}
+      with_bias: False
   - scope: layer5/BatchNormalization
-    layer:
-      name: BatchNormalization
-      args:
-        learn: True
+    typename: BatchNormalization
+    args:
+      learn: True
diff --git a/tests/integration/data/optimizer/Adam.yml b/tests/integration/data/optimizer/Adam.yml
index 025cc0d8..3e26f38d 100644
--- a/tests/integration/data/optimizer/Adam.yml
+++ b/tests/integration/data/optimizer/Adam.yml
@@ -1,4 +1,4 @@
-name: Adam
+typename: Adam
 args:
   learning_rate: 0.001
   beta1: 0.9
diff --git a/tests/integration/data/optimizer/Adamax.yml b/tests/integration/data/optimizer/Adamax.yml
index ef37afd2..8c104de1 100644
--- a/tests/integration/data/optimizer/Adamax.yml
+++ b/tests/integration/data/optimizer/Adamax.yml
@@ -1,4 +1,4 @@
-name: Adamax
+typename: Adamax
 args:
   learning_rate: 0.001
   beta1: 0.9
diff --git a/tests/integration/data/optimizer/GravesRMSProp.yml b/tests/integration/data/optimizer/GravesRMSProp.yml
index 647bfcfe..14b82ab9 100644
--- a/tests/integration/data/optimizer/GravesRMSProp.yml
+++ b/tests/integration/data/optimizer/GravesRMSProp.yml
@@ -1,4 +1,4 @@
-name: GravesRMSProp
+typename: GravesRMSProp
 args:
   learning_rate: 0.001
   decay1: 0.95
diff --git a/tests/integration/data/optimizer/NeonRMSProp.yml b/tests/integration/data/optimizer/NeonRMSProp.yml
index 95792970..3fa43ff9 100644
--- a/tests/integration/data/optimizer/NeonRMSProp.yml
+++ b/tests/integration/data/optimizer/NeonRMSProp.yml
@@ -1,4 +1,4 @@
-name: NeonRMSProp
+typename: NeonRMSProp
 args:
   learning_rate: 0.001
   decay: 0.95
diff --git a/tests/integration/data/optimizer/RMSProp_with_moment.yml b/tests/integration/data/optimizer/RMSProp_with_moment.yml
index 194e26c5..27cc0cf8 100644
--- a/tests/integration/data/optimizer/RMSProp_with_moment.yml
+++ b/tests/integration/data/optimizer/RMSProp_with_moment.yml
@@ -1,4 +1,4 @@
-name: RMSProp
+typename: RMSProp
 args:
   learning_rate: 0.001
   decay: 0.95
diff --git a/tests/integration/data/optimizer/RMSProp_without_moment.yml b/tests/integration/data/optimizer/RMSProp_without_moment.yml
index 27c64dd8..06a2c56d 100644
--- a/tests/integration/data/optimizer/RMSProp_without_moment.yml
+++ b/tests/integration/data/optimizer/RMSProp_without_moment.yml
@@ -1,4 +1,4 @@
-name: RMSProp
+typename: RMSProp
 args:
   learning_rate: 0.001
   decay: 0.95
diff --git a/tests/integration/data/optimizer/SGD.yml b/tests/integration/data/optimizer/SGD.yml
index 671f2391..3dd2451d 100644
--- a/tests/integration/data/optimizer/SGD.yml
+++ b/tests/integration/data/optimizer/SGD.yml
@@ -1,3 +1,3 @@
-name: SGD
+typename: SGD
 args:
   learning_rate: 0.001
diff --git a/tests/integration/test_initializer_compatibility/run_initializer.py b/tests/integration/test_initializer_compatibility/run_initializer.py
index c47e692c..100a7307 100644
--- a/tests/integration/test_initializer_compatibility/run_initializer.py
+++ b/tests/integration/test_initializer_compatibility/run_initializer.py
@@ -30,8 +30,8 @@ def _parse_command_line_args():
     return ap.parse_args()
 
 
-def _create_initializer(name, args):
-    return nn.get_initializer(name)(**args)
+def _create_initializer(typename, args):
+    return nn.get_initializer(typename)(**args)
 
 
 def _transpose_needed(initializer, shape):
diff --git a/tests/integration/test_layer_numerical_compatibility/run_layer.py b/tests/integration/test_layer_numerical_compatibility/run_layer.py
index 5c226063..84c03ff2 100644
--- a/tests/integration/test_layer_numerical_compatibility/run_layer.py
+++ b/tests/integration/test_layer_numerical_compatibility/run_layer.py
@@ -93,8 +93,8 @@ def _run_forward_prop(layer, input_value, parameter_file, iteration=1):
     return output
 
 
-def _load_layer(cfg):
-    return nn.get_layer(cfg['name'])(**cfg.get('args', {}))
+def _create_layer(typename, args=None):
+    return nn.get_layer(typename)(**(args or {}))
 
 
 def _load_input_value(filepath):
@@ -150,7 +150,7 @@ def _main():
     cfg, input_file, param_file = _load_config(args.config)
 
     output = _run_forward_prop(
-        layer=_load_layer(cfg['layer']),
+        layer=_create_layer(**cfg['layer']),
         input_value=_load_input_value(input_file),
         parameter_file=param_file,
         **cfg.get('run', {})
diff --git a/tests/integration/test_optimizer_numerical_compatibility/run_optimizer.py b/tests/integration/test_optimizer_numerical_compatibility/run_optimizer.py
index 6ded8085..80cd2f13 100644
--- a/tests/integration/test_optimizer_numerical_compatibility/run_optimizer.py
+++ b/tests/integration/test_optimizer_numerical_compatibility/run_optimizer.py
@@ -65,7 +65,7 @@ def _optimize(optimizer, loss, wrt, n_ite):
 
 def _load_optimizer(filepath):
     cfg = load_config(filepath)
-    return get_optimizer(cfg['name'])(**cfg.get('args', {}))
+    return get_optimizer(cfg['typename'])(**cfg.get('args', {}))
 
 
 def _save_result(filepath, result):
diff --git a/tests/integration/test_serialization/serialize_model.py b/tests/integration/test_serialization/serialize_model.py
index e10d4a6a..e018043d 100644
--- a/tests/integration/test_serialization/serialize_model.py
+++ b/tests/integration/test_serialization/serialize_model.py
@@ -55,26 +55,30 @@ def _parse_command_line_args():
 
 def _make_optimizer(filepath):
     cfg = load_config(filepath)
-    return nn.get_optimizer(cfg['name'])(**cfg['args'])
+    return nn.get_optimizer(cfg['typename'])(**cfg['args'])
+
+
+def _gen_model_def(model_file):
+    fmt = luchador.get_nn_conv_format()
+    w, h, c = WIDTH, HEIGHT, CHANNEL
+    shape = (
+        '[null, {}, {}, {}]'.format(h, w, c) if fmt == 'NHWC' else
+        '[null, {}, {}, {}]'.format(c, h, w)
+    )
+    return nn.get_model_config(
+        model_file, n_actions=N_ACTIONS, input_shape=shape)
 
 
 def _build_network(model_filepath, optimizer_filepath, initial_parameter):
     _LG.info('Building Q networks')
     dql = DeepQLearning(
-        model_config={
-            'name': model_filepath,
-            'initial_parameter': initial_parameter,
-            'input_channel': CHANNEL,
-            'input_height': HEIGHT,
-            'input_width': WIDTH,
-        },
         q_learning_config={
             'discount_rate': 0.99,
             'min_reward': -1.0,
             'max_reward': 1.0,
         },
         cost_config={
-            'name': 'SSE2',
+            'typename': 'SSE2',
             'args': {
                 'min_delta': -1.0,
                 'max_delta': 1.0
@@ -82,7 +86,8 @@ def _build_network(model_filepath, optimizer_filepath, initial_parameter):
         },
         optimizer_config=load_config(optimizer_filepath),
     )
-    dql.build(n_actions=N_ACTIONS)
+    model_def = _gen_model_def(model_filepath)
+    dql.build(model_def, initial_parameter)
     _LG.info('Syncing models')
     dql.sync_network()
     return dql
diff --git a/tests/integration/test_server_client/launch_remote_env.py b/tests/integration/test_server_client/launch_remote_env.py
index 82e1a535..bec29892 100644
--- a/tests/integration/test_server_client/launch_remote_env.py
+++ b/tests/integration/test_server_client/launch_remote_env.py
@@ -22,7 +22,7 @@ def _main():
         'http://localhost:{}/create'.format(args.man_port),
         json={
             'environment': {
-                'name': 'ALEEnvironment',
+                'typename': 'ALEEnvironment',
                 'args': {
                     'rom': 'breakout.bin',
                     'display_screen': True,
diff --git a/tests/unit/nn/model_test.py b/tests/unit/nn/model_test.py
index 747397f7..1c65f89f 100644
--- a/tests/unit/nn/model_test.py
+++ b/tests/unit/nn/model_test.py
@@ -1,3 +1,4 @@
+"""Test nn.model.util module"""
 from __future__ import absolute_import
 
 import unittest
@@ -7,6 +8,7 @@
 
 
 class UtilTest(unittest.TestCase):
+    """Test model [de]serialization"""
     longMessage = True
     maxDiff = None