From 1f037bf426759eddb32de09eb91e51e5a99d99e0 Mon Sep 17 00:00:00 2001
From: Henry <henry.webel@cpr.ku.dk>
Date: Mon, 5 Feb 2024 15:21:23 +0100
Subject: [PATCH] :fire::art: delete old code, try to raise error

- parsing file via include did not pick up conf.py configuration
---
 docs/docutils.conf |  4 ++++
 vaep/tf_board.py   | 57 ----------------------------------------------
 2 files changed, 4 insertions(+), 57 deletions(-)
 create mode 100644 docs/docutils.conf
 delete mode 100644 vaep/tf_board.py

diff --git a/docs/docutils.conf b/docs/docutils.conf
new file mode 100644
index 000000000..74349b17b
--- /dev/null
+++ b/docs/docutils.conf
@@ -0,0 +1,4 @@
+[general]
+nb_execution_mode: auto
+nb_execution_raise_on_error: true
+nb_merge_streams: true
\ No newline at end of file
diff --git a/vaep/tf_board.py b/vaep/tf_board.py
deleted file mode 100644
index bf8959e09..000000000
--- a/vaep/tf_board.py
+++ /dev/null
@@ -1,57 +0,0 @@
-from pathlib import Path
-from datetime import datetime
-from torch.utils.tensorboard import SummaryWriter
-
-
-class TensorboardModelNamer():
-    """PyTorch SummaryWriter helper class for experiments.
-
-    Creates new SummaryWriter for an experiment
-    """
-
-    def __init__(self, prefix_folder, root_dir=Path('runs')):
-        """[summary]
-
-        Parameters
-        ----------
-        prefix_folder : str
-            Experiment folder-name. All new setups will be written to new summary files.
-        root_dir : Path, optional
-            Root directory to store experiments, by default Path('runs')
-        """
-        self.prefix_folder = prefix_folder
-        self.root_logdir = Path(root_dir)
-        self.folder = (self.root_logdir /
-                       f'{self.prefix_folder}_{format(datetime.now(), "%y%m%d_%H%M")}')
-
-    def get_model_name(self, hidden_layers: int,
-                       neurons: list,
-                       scaler: str,
-                       ):
-        name = 'model_'
-        name += f'hl{hidden_layers:02d}'
-
-        if isinstance(neurons, str):
-            neurons = neurons.split()
-        elif not type(neurons) in [list, tuple]:
-            raise TypeError(
-                "Provide expected format for neurons: [12, 13, 14], '12 13 14' or '12_13_14'")
-
-        for x in neurons:
-            name += f'_{x}'
-
-        if isinstance(scaler, str):
-            name += f'_{scaler}'
-        else:
-            name += f'_{scaler!r}'
-        return name
-
-    def get_writer(self, hidden_layers: int,
-                   neurons: list,
-                   scaler: str,
-                   ):
-        """Return a new SummaryWriter instance for one setup in an experiment."""
-        model_name = self.get_model_name(hidden_layers=hidden_layers,
-                                         neurons=neurons,
-                                         scaler=scaler)
-        return SummaryWriter(log_dir=self.folder / model_name)