From 06dd5a54b3517dd6cb026668d454ce95c92bea5a Mon Sep 17 00:00:00 2001
From: Mayur Kawale <122032765+Mefisto04@users.noreply.github.com>
Date: Sat, 12 Oct 2024 00:18:27 +0530
Subject: [PATCH 1/2] Update depth_pro.py

---
 src/depth_pro/depth_pro.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/src/depth_pro/depth_pro.py b/src/depth_pro/depth_pro.py
index f31b4e1..0a2dd91 100644
--- a/src/depth_pro/depth_pro.py
+++ b/src/depth_pro/depth_pro.py
@@ -71,8 +71,8 @@ def create_backbone_model(
 
 def create_model_and_transforms(
     config: DepthProConfig = DEFAULT_MONODEPTH_CONFIG_DICT,
-    device: torch.device = torch.device("cpu"),
-    precision: torch.dtype = torch.float32,
+    device: torch.device = torch.device("cuda" if torch.cuda.is_available() else "cpu"),
+    precision: torch.dtype = torch.float16 if device.type == 'cuda' else torch.float32,
 ) -> Tuple[DepthPro, Compose]:
     """Create a DepthPro model and load weights from `config.checkpoint_uri`.
 
@@ -146,7 +146,8 @@ def create_model_and_transforms(
         # which we would not use. We only use the encoding.
         missing_keys = [key for key in missing_keys if "fc_norm" not in key]
         if len(missing_keys) != 0:
-            raise KeyError(f"Keys are missing when loading monodepth: {missing_keys}")
+            raise KeyError(f"Keys are missing when loading monodepth: {missing_keys}. "
+                   f"Ensure the model checkpoint is compatible with the architecture or update the state dict.")
 
     return model, transform
 

From 641e46daf10eaa0459f0632ef413ecb7ebec7694 Mon Sep 17 00:00:00 2001
From: Mayur Kawale <122032765+Mefisto04@users.noreply.github.com>
Date: Fri, 25 Oct 2024 00:14:23 +0530
Subject: [PATCH 2/2] Update depth_pro.py

---
 src/depth_pro/depth_pro.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/depth_pro/depth_pro.py b/src/depth_pro/depth_pro.py
index 0a2dd91..36fe5a0 100644
--- a/src/depth_pro/depth_pro.py
+++ b/src/depth_pro/depth_pro.py
@@ -72,8 +72,10 @@ def create_backbone_model(
 def create_model_and_transforms(
     config: DepthProConfig = DEFAULT_MONODEPTH_CONFIG_DICT,
     device: torch.device = torch.device("cuda" if torch.cuda.is_available() else "cpu"),
-    precision: torch.dtype = torch.float16 if device.type == 'cuda' else torch.float32,
 ) -> Tuple[DepthPro, Compose]:
+    # Determine the precision based on the device here
+    precision = torch.float16 if device.type == 'cuda' else torch.float32
+
     """Create a DepthPro model and load weights from `config.checkpoint_uri`.
 
     Args: