refactor: Update ConchModel and Phikon to use logging

The ConchModel and Phikon classes in the conch.py and phikon.py files respectively have been updated to use log for indicating that weights are not used for these models.

src/prismtoolbox/wsiemb/models/conch_model/conch.py

@@ -1,3 +1,4 @@
+import logging
 import json
 import torch
 import torch.nn as nn
@@ -6,6 +7,7 @@
 from huggingface_hub import hf_hub_download
 from .coca_model import CoCa, resize_pos_embed
 
+log = logging.getLogger(__name__)
 CFG_FILE = Path(__file__).parent / "config.json"
 
 
@@ -37,6 +39,8 @@ def forward(self, x):
 
 
 def create_conch_embedder(weights=None):
+    if weights is not None:
+        log.warning("Weights are not used in this model, they will be ignored.")
     checkpoint_path = "hf_hub:MahmoodLab/conch"
     with open(CFG_FILE, "r") as f:
         model_cfg = json.load(f)

src/prismtoolbox/wsiemb/models/phikon.py

@@ -1,7 +1,9 @@
+import logging
 import torch.nn as nn
 from functools import partial
 from transformers import AutoImageProcessor, ViTModel
 
+log = logging.getLogger(__name__)
 
 class Phikon(nn.Module):
     def __init__(self) -> None:
@@ -15,6 +17,8 @@ def forward(self, x):
 
 
 def create_phikon_embedder(weights=None):
+    if weights is not None:
+        log.warning("Weights are not used in this model, they will be ignored.")
     model = Phikon()
     pretrained_transforms = partial(
         AutoImageProcessor.from_pretrained("owkin/phikon"), return_tensors="pt"