cpuify

app.py

@@ -5,12 +5,10 @@ import random
 from pipeline import TextToImagePipeline
 import torch
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device ="cpu"
 
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
+
+torch_dtype = torch.float32
 
 pipe = TextToImagePipeline(device=device)
 

bert_vectorize.py

@@ -4,7 +4,7 @@ tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
 model = DistilBertModel.from_pretrained('distilbert-base-uncased', output_hidden_states=True)
 model.eval()
 
-device = "mps" if torch.backends.mps.is_available() else "cpu"
+device ="cpu"
 
 model = model.to(device)
 def vectorize_text_with_bert(text):# from hf docs

factories.py

@@ -172,7 +172,7 @@ class Up(nn.Module):
 
 
 class Dome_UNet(nn.Module):
-    def __init__(self, c_in=3, c_out=3, time_dim=256, device="mps"):
+    def __init__(self, c_in=3, c_out=3, time_dim=256, device="cpu"):
         super().__init__()
         self.device = device
         self.time_dim = time_dim
@@ -233,7 +233,7 @@ class Dome_UNet(nn.Module):
 
 
 class UNet_conditional(nn.Module):
-    def __init__(self, c_in=3, c_out=3, time_dim=256, num_classes=None, context_dim=None, device="cuda"):
+    def __init__(self, c_in=3, c_out=3, time_dim=256, num_classes=None, context_dim=None, device="cpu"):
         super().__init__()
 
         if context_dim is None:

infer.py

@@ -11,7 +11,7 @@ from logger import save_grid_with_label
 
 
 EXPERIMENT_DIRECTORY = "runs/run_3_jxa"
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device ="cpu"
 
 try:
     os.mkdir(os.path.join(EXPERIMENT_DIRECTORY, "inferred"))

pipeline.py

@@ -57,7 +57,7 @@ class TextToImagePipeline():
 
 # Usage example
 if __name__ == "__main__":
-    device = "mps" if torch.backends.mps.is_available() else "cpu"
+    device ="cpu"
     model_dir = "runs/run_3_jxa"  # Path to your model directory
 
     # Create an instance of the pipeline

runner.py

@@ -13,7 +13,7 @@ from torchinfo import summary
 
 
 EXPERIMENT_DIRECTORY = "runs/run_3_jxa_resumed"
-device = "mps" if torch.backends.mps.is_available() else "cpu"
+device ="cpu"
 
 try:
     os.mkdir(os.path.join(EXPERIMENT_DIRECTORY, "inferred"))