From 27b393f5ec967c6a4dc2c0d36903cdfb58c505e6 Mon Sep 17 00:00:00 2001
From: Felix Kleinert <f.kleinert@fz-juelich.de>
Date: Mon, 11 May 2020 14:24:41 +0200
Subject: [PATCH] fist compile setups
---
src/model_modules/model_class.py | 57 ++++++++++++++++++++++----------
src/run_modules/model_setup.py | 7 ++--
2 files changed, 44 insertions(+), 20 deletions(-)
diff --git a/src/model_modules/model_class.py b/src/model_modules/model_class.py
index 290a527b..a240507c 100644
--- a/src/model_modules/model_class.py
+++ b/src/model_modules/model_class.py
@@ -34,11 +34,13 @@ class AbstractModelClass(ABC):
self.__loss = None
self.model_name = self.__class__.__name__
self.__custom_objects = {}
- self.__allowed_compile_options = {'metrics': None,
- 'loss_weights': None,
- 'sample_weight_mode': None,
- 'weighted_metrics': None,
- 'target_tensors': None
+ self.__allowed_compile_options = {'optimizer': None,
+ 'loss': None,
+ 'metrics': None,
+ 'loss_weights': None,
+ 'sample_weight_mode': None,
+ 'weighted_metrics': None,
+ 'target_tensors': None
}
self.__compile_options = self.__allowed_compile_options
@@ -113,14 +115,34 @@ class AbstractModelClass(ABC):
@compile_options.setter
def compile_options(self, value: Dict) -> None:
- if not isinstance(value, dict):
- raise TypeError(f"`value' has to be a dictionary. But it is {type(value)}")
- for new_k, new_v in value.items():
- if new_k in self.__allowed_compile_options.keys():
- self.__compile_options[new_k] = new_v
+ for allow_k in self.__allowed_compile_options.keys():
+ if hasattr(self, allow_k):
+ new_v_attr = getattr(self, allow_k)
else:
- logging.warning(
- f"`{new_k}' is not a valid additional compile option. Will be ignored in keras.compile()")
+ new_v_attr = None
+ if isinstance(value, dict):
+ new_v_dic = value.pop(allow_k, None)
+ elif value is None:
+ new_v_dic = None
+ else:
+ raise TypeError(f'compile_options must be dict or None, but is {type(value)}.')
+ if (new_v_attr == new_v_dic) or ((new_v_attr is None) ^ (new_v_dic is None)):
+ if new_v_attr is not None:
+ self.__compile_options[allow_k] = new_v_attr
+ else:
+ self.__compile_options[allow_k] = new_v_dic
+ else:
+ raise SyntaxError(
+ f"Got different values for same argument: self.{allow_k}={new_v_attr} and '{allow_k}': {new_v_dic}")
+
+ # if not isinstance(value, dict):
+ # raise TypeError(f"`value' has to be a dictionary. But it is {type(value)}")
+ # for new_k, new_v in value.items():
+ # if new_k in self.__allowed_compile_options.keys():
+ # self.__compile_options[new_k] = new_v
+ # else:
+ # logging.warning(
+ # f"`{new_k}' is not a valid additional compile option. Will be ignored in keras.compile()")
def get_settings(self) -> Dict:
"""
@@ -191,9 +213,6 @@ class MyLittleModel(AbstractModelClass):
self.channels = channels
self.dropout_rate = 0.1
self.regularizer = keras.regularizers.l2(0.1)
- self.initial_lr = 1e-2
- self.optimizer = keras.optimizers.SGD(lr=self.initial_lr, momentum=0.9)
- self.lr_decay = src.model_modules.keras_extensions.LearningRateDecay(base_lr=self.initial_lr, drop=.94, epochs_drop=10)
self.epochs = 20
self.batch_size = int(256)
self.activation = keras.layers.PReLU
@@ -239,10 +258,14 @@ class MyLittleModel(AbstractModelClass):
:return: loss function
"""
- self.loss = keras.losses.mean_squared_error
+ # self.loss = keras.losses.mean_squared_error
def set_compile_options(self):
- self.compile_options = {"metrics": ["mse", "mae"]}
+ self.initial_lr = 1e-2
+ self.optimizer = keras.optimizers.SGD(lr=self.initial_lr, momentum=0.9)
+ self.lr_decay = src.model_modules.keras_extensions.LearningRateDecay(base_lr=self.initial_lr, drop=.94,
+ epochs_drop=10)
+ self.compile_options = {"loss": keras.losses.mean_squared_error, "metrics": ["mse", "mae"]}
class MyBranchedModel(AbstractModelClass):
diff --git a/src/run_modules/model_setup.py b/src/run_modules/model_setup.py
index de2d6a57..0563fc88 100644
--- a/src/run_modules/model_setup.py
+++ b/src/run_modules/model_setup.py
@@ -60,10 +60,11 @@ class ModelSetup(RunEnvironment):
self.data_store.set("channels", channels, self.scope)
def compile_model(self):
- optimizer = self.data_store.get("optimizer", self.scope)
- loss = self.model.loss
+ # optimizer = self.data_store.get("optimizer", self.scope)
+ # loss = self.model.loss
compile_options = self.model.compile_options
- self.model.compile(optimizer=optimizer, loss=loss, **compile_options)
+ # self.model.compile(optimizer=optimizer, loss=loss, **compile_options)
+ self.model.compile(**compile_options)
self.data_store.set("model", self.model, self.scope)
def _set_callbacks(self):
--
GitLab