Migrate model to pvnet version 5.0.3.post0+git.c5a17176.dirty

README.md

@@ -9,12 +9,12 @@ license: mit
 
 
 
-# PVNet_summation
+# PVNet2
 
 ## Model Description
 
 <!-- Provide a longer summary of what this model is/does. -->
-This model class sums the output of the PVNet model's GSP level predictions to make a national forecast of UK PV output. More information can be found in the model repo [1], the PVNet model repo [2], and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
+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).
 
 - **Developed by:** openclimatefix
 - **Model type:** Fusion model
@@ -28,23 +28,21 @@ This model class sums the output of the PVNet model's GSP level predictions to m
 
 <!-- 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 the output predictions of our PVNet model which gives GSP (i.e. UK regional) level predictions
-of solar power across Great Britain. This model is trained to take those predictions and use them to estimate
-the national total with uncertainty estimates.
+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.
 
 
 ### Preprocessing
 
-The input data is prepared with the `ocf_data_sampler` [3].
+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/pvnet_summation/runs/50rkn19f](https://wandb.ai/openclimatefix/pvnet_summation/runs/50rkn19f)
+ - [https://wandb.ai/openclimatefix/pvnet2.1/runs/r2txd12n](https://wandb.ai/openclimatefix/pvnet2.1/runs/r2txd12n)
 
 
-The training logs for all model runs of PVNet_summation can be found [here](https://wandb.ai/openclimatefix/pvnet_summation).
+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)
 
@@ -55,6 +53,15 @@ Trained on a single NVIDIA Tesla T4
 
 ### Software
 
-- [1] https://github.com/openclimatefix/PVNet_summation
-- [2] https://github.com/openclimatefix/PVNet
-- [3] https://github.com/openclimatefix/ocf-data-sampler
+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
+
+The versions of these packages can be found below:
+ - pvnet==4.1.6
+ - ocf-data-sampler==0.2.17.post0+git.563e6370.dirty
+
+
+---
+**Migration Note**: This model was migrated on 2025-08-08 to pvnet version 5.0.3.post0+git.c5a17176.dirty

model_config.yaml

@@ -1,4 +1,4 @@
-_target_: pvnet_summation.models.flat_model.FlatModel
+_target_: pvnet.models.LateFusionModel
 output_quantiles:
 - 0.02
 - 0.1
@@ -7,23 +7,377 @@ output_quantiles:
 - 0.75
 - 0.9
 - 0.98
-model_name: openclimatefix/pvnet_uk_region
-model_version: 6feaa986a6bed3cc6c7961c6bf9e92fb15acca6a
+nwp_encoders_dict:
+  ukv:
+    _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
+    _partial_: true
+    in_channels: 11
+    out_features: 256
+    number_of_conv3d_layers: 6
+    conv3d_channels: 32
+    image_size_pixels: 24
+  ecmwf:
+    _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
+    _partial_: true
+    in_channels: 12
+    out_features: 256
+    number_of_conv3d_layers: 4
+    conv3d_channels: 32
+    image_size_pixels: 12
+sat_encoder: null
+add_image_embedding_channel: false
+pv_encoder: null
 output_network:
-  _target_: pvnet.models.multimodal.linear_networks.networks.ResFCNet2
+  _target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
   _partial_: true
   fc_hidden_features: 128
-  n_res_blocks: 2
+  n_res_blocks: 6
   res_block_layers: 2
-  dropout_frac: 0.1
-relative_scale_pvnet_outputs: false
-predict_difference_from_sum: true
-optimizer:
-  _target_: pvnet.optimizers.AdamWReduceLROnPlateau
-  lr: 0.0001
-  weight_decay: 0.25
-  amsgrad: true
-  patience: 10
-  factor: 0.1
-  threshold: 0.0
-num_locations: 331
+  dropout_frac: 0.0
+embedding_dim: 16
+include_sun: true
+include_gsp_yield_history: false
+forecast_minutes: 2160
+history_minutes: 120
+min_sat_delay_minutes: 0
+sat_history_minutes: 60
+pv_history_minutes: 180
+nwp_history_minutes:
+  ukv: 120
+  ecmwf: 120
+nwp_forecast_minutes:
+  ukv: 1800
+  ecmwf: 2220
+location_id_mapping:
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+  2: 2
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+adapt_batches: true

pytorch_model.bin → model_weights.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 47138430
+oid sha256:0c354e0bf5795e58202225a2819a81b7984204dc4a7151640100a26500fc0117
+size 90973456