def convert2model(model_config):
if 'name' not in model_config:
raise ValueError("config is not a model config!")
name = model_config['name'] or ''
if name.startswith('model'):
model = Model.from_config(model_config)
elif name.startswith('sequential'):
model = Sequential.from_config(model_config)
else:
raise ValueError("model config incorrect!")
return model
def __add_sequence_layer(self, layer):
"""序列模型，上一层输入只有一个模型"""
model_config = {}
if self.model_rdd:
model_config = json.loads(self.model_rdd.first().model_config)
self.layer_num += len(model_config.get('layers', []))
model = Sequential.from_config(model_config)
model.add(layer)
self.layer_num += 1
return self.model2df(model)
def build_model(self):
if self.task_index is None:
raise ValueError("task_index cannot None!!!")
with tf.device(
tf.train.replica_device_setter(
worker_device="/job:worker/task:{}".format(
self.task_index),
cluster=self.cluster)):
model_type = gmt(self.model_config)
if model_type == ModelType.SEQUENCE:
model = Sequential.from_config(self.model_config)
elif model_type == ModelType.NETWORK:
model = Model.from_config(self.model_config)
else:
raise ValueError(
"{}, unknown model type!!!".format(model_type))
self.parse_optimizer()
model.compile(**self.compile_config)
self.model = model
def run(self):
params = self.params
name = params.get('name')
model_rdd = inputRDD(name)
if not model_rdd:
raise ValueError("In Summary model_rdd cannot be empty！")
model_config = json.loads(model_rdd.first().model_config)
# model_name = model_config.get('name')
if get_mode_type(model_rdd) == ModelType.SEQUENCE:
model = Sequential.from_config(model_config)
elif get_mode_type(model_rdd) == ModelType.NETWORK:
model = Model.from_config(model_config)
else:
raise ValueError("model type incorrect!!!")
model.summary()
outputRDD('<#zzjzRddName#>_Summary', model_rdd)
def add(self, start_rdd, repeats=0):
if MODEL_CONFIG not in self.model_rdd.first():
raise ValueError('repeat units end node not exists model_config!')
model_config = json.loads(getattr(self.model_rdd.first(),
MODEL_CONFIG))
start_config = json.loads(getattr(start_rdd.first(), MODEL_CONFIG))
marker_layer = start_config['layers'][-1]
for index, layer in enumerate(model_config['layers']):
if marker_layer == layer:
layers = model_config['layers'][index + 1:]
if 'inbound_nodes' in layer:
self.model = Model.from_config(model_config)
self.repeat_networks(layers, repeats)
elif 'name' in layer['config']:
self.model = Sequential.from_config(model_config)
self.repeat_sequence(layers, repeats)
else:
raise ValueError(
"In RepeatBlock node, model type incorrect!")
return self.model2df(self.model)
