From 9d87b9c6697c7077858fcea5957b4378fb339763 Mon Sep 17 00:00:00 2001
From: Falco Weichselbaum <f.weichselbaum@fz-juelich.de>
Date: Wed, 20 Oct 2021 19:49:25 +0200
Subject: [PATCH] deactivated not working advanced_paddings.py import, changed
some other keras imports to tensorflow.keras as keras,
*.model.fit_generator() changed to *.model.fit() which is said to have the
same functionality - Commit suffers from PicklingError with RLocks when
trying to save Callback in Epoch 0002
---
mlair/model_modules/flatten.py | 2 +-
mlair/model_modules/model_class.py | 6 +++---
mlair/run_modules/training.py | 34 +++++++++++++++---------------
run.py | 3 ++-
4 files changed, 23 insertions(+), 22 deletions(-)
diff --git a/mlair/model_modules/flatten.py b/mlair/model_modules/flatten.py
index dd1e8e21..98a55bfc 100644
--- a/mlair/model_modules/flatten.py
+++ b/mlair/model_modules/flatten.py
@@ -3,7 +3,7 @@ __date__ = '2019-12-02'
from typing import Union, Callable
-import keras
+import tensorflow.keras as keras
def get_activation(input_to_activate: keras.layers, activation: Union[Callable, str], **kwargs):
diff --git a/mlair/model_modules/model_class.py b/mlair/model_modules/model_class.py
index 9a0e97db..be4f4b22 100644
--- a/mlair/model_modules/model_class.py
+++ b/mlair/model_modules/model_class.py
@@ -120,12 +120,12 @@ import mlair.model_modules.keras_extensions
__author__ = "Lukas Leufen, Felix Kleinert"
__date__ = '2020-05-12'
-import keras
+import tensorflow.keras as keras
from mlair.model_modules import AbstractModelClass
-from mlair.model_modules.inception_model import InceptionModelBase
+#from mlair.model_modules.inception_model import InceptionModelBase
from mlair.model_modules.flatten import flatten_tail
-from mlair.model_modules.advanced_paddings import PadUtils, Padding2D, SymmetricPadding2D
+#from mlair.model_modules.advanced_paddings import PadUtils, Padding2D, SymmetricPadding2D
from mlair.model_modules.loss import l_p_loss
diff --git a/mlair/run_modules/training.py b/mlair/run_modules/training.py
index 27dd4445..cb538abb 100644
--- a/mlair/run_modules/training.py
+++ b/mlair/run_modules/training.py
@@ -137,14 +137,14 @@ class Training(RunEnvironment):
checkpoint = self.callbacks.get_checkpoint()
if not os.path.exists(checkpoint.filepath) or self._create_new_model:
- history = self.model.fit_generator(generator=self.train_set,
- steps_per_epoch=len(self.train_set),
- epochs=self.epochs,
- verbose=2,
- validation_data=self.val_set,
- validation_steps=len(self.val_set),
- callbacks=self.callbacks.get_callbacks(as_dict=False),
- workers=psutil.cpu_count(logical=False))
+ history = self.model.fit(self.train_set,
+ steps_per_epoch=len(self.train_set),
+ epochs=self.epochs,
+ verbose=2,
+ validation_data=self.val_set,
+ validation_steps=len(self.val_set),
+ callbacks=self.callbacks.get_callbacks(as_dict=False),
+ workers=psutil.cpu_count(logical=False))
else:
logging.info("Found locally stored model and checkpoints. Training is resumed from the last checkpoint.")
self.callbacks.load_callbacks()
@@ -152,15 +152,15 @@ class Training(RunEnvironment):
self.model = keras.models.load_model(checkpoint.filepath)
hist: History = self.callbacks.get_callback_by_name("hist")
initial_epoch = max(hist.epoch) + 1
- _ = self.model.fit_generator(generator=self.train_set,
- steps_per_epoch=len(self.train_set),
- epochs=self.epochs,
- verbose=2,
- validation_data=self.val_set,
- validation_steps=len(self.val_set),
- callbacks=self.callbacks.get_callbacks(as_dict=False),
- initial_epoch=initial_epoch,
- workers=psutil.cpu_count(logical=False))
+ _ = self.model.fit(self.train_set,
+ steps_per_epoch=len(self.train_set),
+ epochs=self.epochs,
+ verbose=2,
+ validation_data=self.val_set,
+ validation_steps=len(self.val_set),
+ callbacks=self.callbacks.get_callbacks(as_dict=False),
+ initial_epoch=initial_epoch,
+ workers=psutil.cpu_count(logical=False))
history = hist
try:
lr = self.callbacks.get_callback_by_name("lr")
diff --git a/run.py b/run.py
index fbe6aa26..954f8532 100644
--- a/run.py
+++ b/run.py
@@ -3,6 +3,7 @@ __date__ = '2020-06-29'
import argparse
from mlair.workflows import DefaultWorkflow
+from mlair.model_modules.model_class import MyLittleModelHourly as chosen_model
from mlair.helpers import remove_items
from mlair.configuration.defaults import DEFAULT_PLOT_LIST
import os
@@ -28,7 +29,7 @@ def main(parser_args):
stations=["DEBW013", "DEBW087", "DEBW107", "DEBW076"],
train_model=False, create_new_model=True, network="UBA",
evaluate_bootstraps=False, # plot_list=["PlotCompetitiveSkillScore"],
- competitors=["test_model", "test_model2"],
+ competitors=["test_model", "test_model2"], model=chosen_model,
competitor_path=os.path.join(os.getcwd(), "data", "comp_test"),
**parser_args.__dict__, start_script=__file__)
workflow.run()
--
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