Migrate model (HF commit ca258a0) to pvnet version 5.3.0.post0+git.489723d6.dirty

README.md

@@ -3,54 +3,54 @@ language: en
 library_name: pytorch
 license: mit
 ---
+<!--
+Do not remove elements like the above surrounded by two curly braces and do not add any more of them. These entries are required by the PVNet library and are automaticall infilled when the model is uploaded to huggingface
+-->
 
+<!-- Title - e.g. PVNet2, WindNet, PVNet India -->
+# TEMPLATE
 
-
-
-
-
-# PVNet2
-
+<!-- Provide a longer summary of what this model is/does. -->
 ## Model Description
 
-<!-- Provide a longer summary of what this model is/does. -->
-This model class uses satellite data, numerical weather predictions, and recent Grid Service Point( GSP) PV power output to forecast the near-term (~8 hours) PV power output at all GSPs. More information can be found in the model repo [1] and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
+<!-- e.g.
+This model class uses satellite data, and numerical weather predictions to forecast the near-term (up to 8 hours ahead) PV power output at all Grid Service Points (GSPs) in Great Britain. More information can be found in the model repo [1]. The model repo also includes links to our workshop paper on this model and some experimental notes.
+-->
 
 - **Developed by:** openclimatefix
 - **Model type:** Fusion model
 - **Language(s) (NLP):** en
 - **License:** mit
 
-
 # Training Details
 
 ## Data
 
-<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-The model is trained on data from 2019-2022 and validated on data from 2022-2023. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) for more details.
+<!-- eg.
+The model is trained on data from 2019-2022 and validated on data from 2022-2023. It uses NWP data from ECMWF IFS model, and the UK Met Office UKV model. It uses satellite data from the EUMETSAT MSG SEVIRI instrument.
 
+See the data_config.yaml file for more information on the channels and window-size used for each input data source.
+-->
 
+<!-- The preprocessing section is not strictly nessessary but perhaps nice to have -->
 ### Preprocessing
 
+<!-- eg.
 Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Dataset [2].
-
+-->
 
 ## Results
 
-The training logs for the current model can be found here:
- - [https://wandb.ai/openclimatefix/NL-Solar/runs/l06ylklb](https://wandb.ai/openclimatefix/NL-Solar/runs/l06ylklb)
-
-
-The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
-
-Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
+<!-- Do not remove the lines below -->
+The training logs for this model commit can be found here:
+ - [https://wandb.ai/openclimatefix/NL-Solar/runs/re47gi6l](https://wandb.ai/openclimatefix/NL-Solar/runs/re47gi6l)
 
 
+<!-- The hardware section is also just nice to have -->
 ### Hardware
-
 Trained on a single NVIDIA Tesla T4
 
+<!-- Do not remove the section below -->
 ### Software
 
 This model was trained using the following Open Climate Fix packages:
@@ -58,17 +58,10 @@ This model was trained using the following Open Climate Fix packages:
 - [1] https://github.com/openclimatefix/PVNet
 - [2] https://github.com/openclimatefix/ocf-data-sampler
 
+<!-- Especially do not change the two lines below -->
 The versions of these packages can be found below:
- - pvnet==4.1.18
- - ocf-data-sampler==0.2.34
-
-
----
-**Migration Note**: This model (HF commit 246b434b72c68edbbc13f1e5fc74e7699034aede) was migrated on 2025-09-10 to pvnet version 5.0.6.post0+git.e31d0340.dirty
-
-
----
-**Migration Note**: This model was migrated on 2025-10-15 to pvnet version 5.1.0.post0+git.c15f1d4e.dirty
+ - pvnet==5.1.0.post0+git.c15f1d4e.dirty
+ - ocf-data-sampler==0.5.27.post2+git.e15368d8.dirty
 
 
 ---

data_config.yaml

@@ -1,9 +1,14 @@
 general:
-  description: Config for training the saved PVNet model
-  name: PVNet current
+  description: Initial config for NL model
+  name: Netherlands_pvnet_config
 input_data:
   nwp:
     ecmwf:
+      provider: ecmwf
+      zarr_path: PLACEHOLDER.zarr
+      interval_start_minutes: -120
+      interval_end_minutes: 2220
+      time_resolution_minutes: 60
       accum_channels:
       - direct_shortwave_radiation_flux_gl
       - downward_longwave_radiation_flux_gl
@@ -21,88 +26,86 @@ input_data:
       - snow_depth_gl
       - temperature_sl
       - total_precipitation_rate_gl
-      - visibility_sl
       - wind_u_component_10m
       - wind_v_component_10m
-      dropout_fraction: 1.0
+      image_size_pixels_height: 32
+      image_size_pixels_width: 32
       dropout_timedeltas_minutes:
-      - -180
-      image_size_pixels_height: 30
-      image_size_pixels_width: 30
-      interval_end_minutes: 2160
-      interval_start_minutes: -120
+      - -360
+      dropout_fraction: 1.0
       max_staleness_minutes: null
       normalisation_constants:
+        temperature_sl:
+          mean: 283.48333740234375
+          std: 3.692270040512085
+        downward_shortwave_radiation_flux_gl:
+          mean: 11458988.0
+          std: 13025427.0
+        downward_longwave_radiation_flux_gl:
+          mean: 27187026.0
+          std: 15855867.0
         cloud_cover_high:
           mean: 0.3961029052734375
           std: 0.42244860529899597
-        cloud_cover_low:
-          mean: 0.44901806116104126
-          std: 0.3791404366493225
         cloud_cover_medium:
           mean: 0.3288780450820923
           std: 0.38039860129356384
+        cloud_cover_low:
+          mean: 0.44901806116104126
+          std: 0.3791404366493225
         cloud_cover_total:
           mean: 0.7049227356910706
           std: 0.37487083673477173
-        diff_direct_shortwave_radiation_flux_gl:
-          mean: 469169.5
-          std: 818950.6875
-        diff_downward_longwave_radiation_flux_gl:
-          mean: 1136464.0
-          std: 131942.03125
-        diff_downward_shortwave_radiation_flux_gl:
-          mean: 420584.6875
-          std: 715366.3125
-        diff_downward_ultraviolet_radiation_flux_gl:
-          mean: 48265.4765625
-          std: 81605.25
+        visibility_sl:
+          mean: 12905302.0
+          std: 16294988.0
+        snow_depth_gl:
+          mean: 8.107526082312688e-05
+          std: 0.000913831521756947
         direct_shortwave_radiation_flux_gl:
-          mean: 11458988.0
-          std: 13025427.0
-        downward_longwave_radiation_flux_gl:
-          mean: 27187026.0
-          std: 15855867.0
-        downward_shortwave_radiation_flux_gl:
-          mean: 11458988.0
-          std: 13025427.0
+          mean: 12905302.0
+          std: 16294988.0
         downward_ultraviolet_radiation_flux_gl:
           mean: 1305651.25
           std: 1445635.25
-        snow_depth_gl:
-          mean: 8.107526082312688e-05
-          std: 0.000913831521756947
-        temperature_sl:
-          mean: 283.48333740234375
-          std: 3.692270040512085
         total_precipitation_rate_gl:
           mean: 3.108070450252853e-05
           std: 9.81039775069803e-05
-        visibility_sl:
-          mean: 12905302.0
-          std: 16294988.0
-        wind_u_component_100m:
-          mean: 2.393547296524048
-          std: 7.2320556640625
         wind_u_component_10m:
           mean: 1.7677178382873535
           std: 5.531515598297119
+        wind_u_component_100m:
+          mean: 2.393547296524048
+          std: 7.2320556640625
         wind_u_component_200m:
           mean: 2.7963004112243652
           std: 8.049470901489258
-        wind_v_component_100m:
-          mean: 1.4244288206100464
-          std: 6.944501876831055
         wind_v_component_10m:
           mean: 0.985887885093689
           std: 5.411230564117432
+        wind_v_component_100m:
+          mean: 1.4244288206100464
+          std: 6.944501876831055
         wind_v_component_200m:
           mean: 1.6010299921035767
           std: 7.561611652374268
-      provider: ecmwf
-      time_resolution_minutes: 60
-      zarr_path: PLACEHOLDER.zarr
+        diff_downward_longwave_radiation_flux_gl:
+          mean: 1136464.0
+          std: 131942.03125
+        diff_downward_shortwave_radiation_flux_gl:
+          mean: 420584.6875
+          std: 715366.3125
+        diff_downward_ultraviolet_radiation_flux_gl:
+          mean: 48265.4765625
+          std: 81605.25
+        diff_direct_shortwave_radiation_flux_gl:
+          mean: 469169.5
+          std: 818950.6875
   satellite:
+    zarr_path: PLACEHOLDER.zarr
+    interval_start_minutes: -60
+    interval_end_minutes: 0
+    time_resolution_minutes: 5
     channels:
     - IR_016
     - IR_039
@@ -115,22 +118,12 @@ input_data:
     - VIS008
     - WV_062
     - WV_073
-    dropout_fraction: 0.8
+    image_size_pixels_height: 50
+    image_size_pixels_width: 50
     dropout_timedeltas_minutes:
     - -5
-    - -10
-    - -15
-    - -20
-    - -25
-    - -30
-    image_size_pixels_height: 100
-    image_size_pixels_width: 100
-    interval_end_minutes: -60
-    interval_start_minutes: -90
+    dropout_fraction: 1.0
     normalisation_constants:
-      HRV:
-        mean: 0.09298719
-        std: 0.11405209
       IR_016:
         mean: 0.17594202
         std: 0.21462157
@@ -164,15 +157,16 @@ input_data:
       WV_073:
         mean: 0.62479186
         std: 0.12924142
-    time_resolution_minutes: 5
-    zarr_path: PLACEHOLDER.zarr
   solar_position:
-    interval_end_minutes: 2160
     interval_start_minutes: -2880
+    interval_end_minutes: 2160
     time_resolution_minutes: 15
   generation:
-    capacity_mode: variable
-    interval_end_minutes: 2160
-    interval_start_minutes: -2880
     time_resolution_minutes: 15
-    zarr_path: /home/zak/projects/PVNet/nl_solar/pv_data/netherlands_pv_data_v2.nc
+    interval_start_minutes: -2880
+    interval_end_minutes: 2160
+    dropout_timedeltas_minutes:
+    - -15
+    dropout_fraction: 1.0
+    dropout_value: -1
+    zarr_path: /home/alex/NL/PV_ned_nl_netherlands_pv_data.nc

model_config.yaml

@@ -11,41 +11,49 @@ nwp_encoders_dict:
   ecmwf:
     _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
     _partial_: true
-    in_channels: 14
+    in_channels: 13
     out_features: 64
+    fc_features: 32
+    stride:
+    - 1
+    - 2
+    - 2
     number_of_conv3d_layers: 4
     conv3d_channels: 32
-    image_size_pixels: 30
+    image_size_pixels: 32
 sat_encoder:
   _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
   _partial_: true
   in_channels: 11
-  out_features: 256
-  number_of_conv3d_layers: 6
+  out_features: 128
+  fc_features: 32
+  stride:
+  - 1
+  - 2
+  - 2
+  number_of_conv3d_layers: 4
   conv3d_channels: 32
-  image_size_pixels: 100
-add_image_embedding_channel: false
+  image_size_pixels: 50
 output_network:
   _target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
   _partial_: true
   fc_hidden_features: 128
   n_res_blocks: 6
   res_block_layers: 2
-  dropout_frac: 0.0
-embedding_dim: 16
+  dropout_frac: 0.2
 include_sun: true
-include_time: true
+interval_minutes: 15
+location_id_mapping:
+  0: 0
 forecast_minutes: 2160
 history_minutes: 2880
-interval_minutes: 15
-min_sat_delay_minutes: 60
-sat_history_minutes: 90
+min_sat_delay_minutes: 5
+sat_history_minutes: 65
 pv_history_minutes: 2880
-pv_interval_minutes: 15
 nwp_history_minutes:
   ecmwf: 120
 nwp_forecast_minutes:
-  ecmwf: 2160
+  ecmwf: 2220
 nwp_interval_minutes:
   ecmwf: 60
 include_generation_history: true

model_weights.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:49ff8659676eb4759756c6d1f1c65bc4c4b9815ef91bcbf541bc2f0c706d2ccb
-size 1200429264
+oid sha256:f963d24d947f0d745403c2f67770e56604e062c8020cea3e55caa9b2c015887f
+size 2756464