Add Experiment Running Code

README.md

@@ -1,5 +1,5 @@
 # Pseudo-Labeller
-Pseudo Irradience Labeller for generating training labels for other PV generation forecasting, and hindcasts. 
+Pseudo Irradience Labeller for generating training labels for other PV generation forecasting, and hindcasts.
 
 ## Install
 

environment.yml

@@ -14,7 +14,7 @@ dependencies:
   - torchdata
   - cartopy
   - rioxarray
-  - pytorch-cuda==11.6
+  - pytorch-cuda
 pip:
   - huggingface_hub
   - einops

pseudo_labeller/model/idam.py

@@ -21,7 +21,7 @@ def __init__(
         num_layers: int = 1,
         output_steps: int = 1,
         pv_meta_input_channels: int = 2,
-        **kwargs
+        **kwargs,
     ):
         """
         Pseudo-Irradience Forecastor/Labeller
@@ -130,8 +130,9 @@ def forward(self, x: torch.Tensor, pv_meta: torch.Tensor = None, output_latents:
             # Rearrange back to timeseries of latent variables
             x = einops.rearrange(x, "b (c t) h w -> b c t h w", c=self.output_channels)
             return x
+        if pv_meta is None:
+            raise ValueError(f"'pv_meta' cannot be none if {output_latents=}")
         pv_meta = self.pv_meta_input(pv_meta)
-        # Reshape to fit into 3DCNN
         x = torch.cat([x, pv_meta], dim=1)
         # Get pv_meta_output
         x = F.relu(self.pv_meta_output(x))  # Generation can only be positive or 0, so ReLU