From e8292d9dbd72158c90bbbae96e3a3df8b941279c Mon Sep 17 00:00:00 2001
From: Alexandra Udaltsova <43303448+AUdaltsova@users.noreply.github.com>
Date: Wed, 25 Sep 2024 12:59:44 +0100
Subject: [PATCH 1/3] add flushing of val epoch resluts

---
 pvnet/models/base_model.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pvnet/models/base_model.py b/pvnet/models/base_model.py
index 8665bf3c..e7283b92 100644
--- a/pvnet/models/base_model.py
+++ b/pvnet/models/base_model.py
@@ -1,4 +1,3 @@
-"""Base model for all PVNet submodels"""
 import json
 import logging
 import os
@@ -743,6 +742,7 @@ def on_validation_epoch_end(self):
             print("Failed to log validation results to wandb")
             print(e)
 
+        self.validation_epoch_results = []
         horizon_maes_dict = self._horizon_maes.flush()
 
         # Create the horizon accuracy curve

From efbd95cce67c2ceee5e497e5548c6e53d2021146 Mon Sep 17 00:00:00 2001
From: Alexandra Udaltsova <43303448+AUdaltsova@users.noreply.github.com>
Date: Wed, 25 Sep 2024 13:08:00 +0100
Subject: [PATCH 2/3] add docstring back base_model.py

---
 pvnet/models/base_model.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pvnet/models/base_model.py b/pvnet/models/base_model.py
index e7283b92..630c4aae 100644
--- a/pvnet/models/base_model.py
+++ b/pvnet/models/base_model.py
@@ -1,3 +1,4 @@
+"""Base model for all PVNet submodels"""
 import json
 import logging
 import os

From ef0dd3f07021dd3e8dd6efb99fecf89c4117b3af Mon Sep 17 00:00:00 2001
From: Alexandra Udaltsova <43303448+AUdaltsova@users.noreply.github.com>
Date: Wed, 25 Sep 2024 17:59:38 +0100
Subject: [PATCH 3/3] log to csv only when end of accumbatch

---
 pvnet/models/base_model.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pvnet/models/base_model.py b/pvnet/models/base_model.py
index 630c4aae..83e67e7b 100644
--- a/pvnet/models/base_model.py
+++ b/pvnet/models/base_model.py
@@ -666,7 +666,8 @@ def validation_step(self, batch: dict, batch_idx):
         # Sensor seems to be in batch, station, time order
         y = batch[self._target_key][:, -self.forecast_len :, 0]
 
-        self._log_validation_results(batch, y_hat, accum_batch_num)
+        if (batch_idx + 1) % self.trainer.accumulate_grad_batches == 0:
+            self._log_validation_results(batch, y_hat, accum_batch_num)
 
         # Expand persistence to be the same shape as y
         losses = self._calculate_common_losses(y, y_hat)