diff --git a/src/model_modules/model_class.py b/src/model_modules/model_class.py
index bb4801acfb5c3a643aecbcfad9cfdb758258d0ef..1a5dd9da38520d6d732253015e8a67325e24c460 100644
--- a/src/model_modules/model_class.py
+++ b/src/model_modules/model_class.py
@@ -27,6 +27,7 @@ class AbstractModelClass(ABC):
self.__model = None
self.__loss = None
+ self.model_name = self.__class__.__name__
def __getattr__(self, name: str) -> Any:
diff --git a/src/plotting/postprocessing_plotting.py b/src/plotting/postprocessing_plotting.py
index 01a565e3db284e56bf0b8c94420b71268fd21a80..d3f6a56a2ec42e41454f0ced8853cb8d1001e495 100644
--- a/src/plotting/postprocessing_plotting.py
+++ b/src/plotting/postprocessing_plotting.py
@@ -527,7 +527,7 @@ class PlotTimeSeries(RunEnvironment):
for i_year in range(end - start + 1):
data_year = data.sel(index=f"{start + i_year}")
for i_half_of_year in range(factor):
- pos = 2 * i_year + i_half_of_year
+ pos = factor * i_year + i_half_of_year
plot_data = self._create_plot_data(data_year, factor, i_half_of_year)
self._plot_orig(axes[pos], plot_data)
self._plot_ahead(axes[pos], plot_data)
diff --git a/src/run_modules/model_setup.py b/src/run_modules/model_setup.py
index 7049af591cdf73434459d4c3f5f6c11e80ab64c0..2c73dad4bc57e529a417a2d4f4e476dfd7624c5a 100644
--- a/src/run_modules/model_setup.py
+++ b/src/run_modules/model_setup.py
@@ -28,8 +28,10 @@ class ModelSetup(RunEnvironment):
path = self.data_store.get("experiment_path", "general")
exp_name = self.data_store.get("experiment_name", "general")
self.scope = "general.model"
- self.checkpoint_name = os.path.join(path, f"{exp_name}_model-best.h5")
- self.callbacks_name = os.path.join(path, f"{exp_name}_model-best-callbacks-%s.pickle")
+ self.path = os.path.join(path, f"{exp_name}_%s")
+ self.model_name = self.path % "%s.h5"
+ self.checkpoint_name = self.path % "model-best.h5"
+ self.callbacks_name = self.path % "model-best-callbacks-%s.pickle"
self._run()
def _run(self):
@@ -79,8 +81,8 @@ class ModelSetup(RunEnvironment):
def load_weights(self):
try:
- self.model.load_weights(self.checkpoint_name)
- logging.info('reload weights...')
+ self.model.load_weights(self.model_name)
+ logging.info(f"reload weights from model {self.model_name} ...")
except OSError:
logging.info('no weights to reload...')
@@ -93,12 +95,12 @@ class ModelSetup(RunEnvironment):
def get_model_settings(self):
model_settings = self.model.get_settings()
self.data_store.set_args_from_dict(model_settings, self.scope)
+ self.model_name = self.model_name % self.data_store.get_default("model_name", self.scope, "my_model")
+ self.data_store.set("model_name", self.model_name, self.scope)
def plot_model(self): # pragma: no cover
with tf.device("/cpu:0"):
- path = self.data_store.get("experiment_path", "general")
- name = self.data_store.get("experiment_name", "general") + "_model.pdf"
- file_name = os.path.join(path, name)
+ file_name = f"{self.model_name.split(sep='.')[0]}.pdf"
keras.utils.plot_model(self.model, to_file=file_name, show_shapes=True, show_layer_names=True)
diff --git a/src/run_modules/post_processing.py b/src/run_modules/post_processing.py
index 03d2e36e8662a573b96c970747e9fe4445244e9b..3c50799b939da2bc8517d1e58dd2c73baebe367b 100644
--- a/src/run_modules/post_processing.py
+++ b/src/run_modules/post_processing.py
@@ -55,10 +55,8 @@ class PostProcessing(RunEnvironment):
try:
model = self.data_store.get("best_model", "general")
except NameNotFoundInDataStore:
- logging.info("no model saved in data store. trying to load model from experiment")
- path = self.data_store.get("experiment_path", "general")
- name = f"{self.data_store.get('experiment_name', 'general')}_my_model.h5"
- model_name = os.path.join(path, name)
+ logging.info("no model saved in data store. trying to load model from experiment path")
+ model_name = self.data_store.get("model_name", "general.model")
model = keras.models.load_model(model_name)
return model
diff --git a/src/run_modules/training.py b/src/run_modules/training.py
index e2a98f27c65e6050b0edae2bbc178abbf97ab646..ff2cffcdf01fd9e917bf1120984c6b65e1f5a13d 100644
--- a/src/run_modules/training.py
+++ b/src/run_modules/training.py
@@ -28,6 +28,7 @@ class Training(RunEnvironment):
self.lr_sc = self.data_store.get("lr_decay", "general.model")
self.hist = self.data_store.get("hist", "general.model")
self.experiment_name = self.data_store.get("experiment_name", "general")
+ self._trainable = self.data_store.get("trainable", "general")
self._run()
def _run(self) -> None:
@@ -44,8 +45,11 @@ class Training(RunEnvironment):
"""
self.set_generators()
self.make_predict_function()
- self.train()
- self.save_model()
+ if self._trainable:
+ self.train()
+ self.save_model()
+ else:
+ logging.info("No training has started, because trainable parameter was false.")
def make_predict_function(self) -> None:
"""
@@ -117,11 +121,9 @@ class Training(RunEnvironment):
def save_model(self) -> None:
"""
- save model in local experiment directory. Model is named as <experiment_name>_my_model.h5 .
+ save model in local experiment directory. Model is named as <experiment_name>_<custom_model_name>.h5 .
"""
- path = self.data_store.get("experiment_path", "general")
- name = f"{self.data_store.get('experiment_name', 'general')}_my_model.h5"
- model_name = os.path.join(path, name)
+ model_name = self.data_store.get("model_name", "general.model")
logging.debug(f"save best model to {model_name}")
self.model.save(model_name)
self.data_store.set("best_model", self.model, "general")