Debugging

openclimatefix · Dec 5, 2023 · fe2e2e5 · fe2e2e5
1 parent 2d11c8b
commit fe2e2e5
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Showing 2 changed files with 5 additions and 6 deletions.
diff --git a/pvnet/models/base_model.py b/pvnet/models/base_model.py
@@ -450,9 +450,9 @@ def validation_step(self, batch: dict, batch_idx):
         """Run validation step"""
         y_hat = self(batch)
         print(f"y_hat.shape: {y_hat.shape}")
-        print(f"{batch[self._target_key].shape}")
-        print(f"{batch[self._target_key][:, -self.forecast_len_30 :, 0].shape}")
-        print(f"{self.forecast_len_30}")
+        print(f"{batch[self._target_key].shape=}")
+        print(f"{batch[self._target_key][:, -self.forecast_len_30 :, 0].shape=}")
+        print(f"{self.forecast_len_30=}")
         y = batch[self._target_key][:, -self.forecast_len_30 :, 0]
 
         losses = self._calculate_common_losses(y, y_hat)

diff --git a/pvnet/models/multimodal/site_encoders/encoders.py b/pvnet/models/multimodal/site_encoders/encoders.py
@@ -335,7 +335,7 @@ def _encode_query(self, x):
 
     def _encode_key(self, x):
         # Shape: [batch size, sequence length, PV site]
-        sensor_site_seqs = x[BatchKey.sensor].float()
+        sensor_site_seqs = x[BatchKey.sensor][:, : self.sequence_length].float()
         batch_size = sensor_site_seqs.shape[0]
         print(f"{sensor_site_seqs.shape=}")
 
@@ -355,7 +355,7 @@ def _encode_key(self, x):
 
     def _encode_value(self, x):
         # Shape: [batch size, sequence length, PV site]
-        sensor_site_seqs = x[BatchKey.sensor].float()
+        sensor_site_seqs = x[BatchKey.sensor][:, : self.sequence_length].float()
         batch_size = sensor_site_seqs.shape[0]
 
         if self.use_sensor_id_in_value:
@@ -394,7 +394,6 @@ def _attention_forward(self, x, average_attn_weights=True):
     def forward(self, x):
         """Run model forward"""
         # Do slicing here to only get history
-        x[BatchKey.sensor] = x[BatchKey.sensor][:, : self.sequence_length].float()
         attn_output, attn_output_weights = self._attention_forward(x)
 
         # Reshape from [batch_size, 1, vdim] to [batch_size, vdim]