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artist_lib.py

@@ -56,6 +56,7 @@ def imageClassifier(inputImage):
 
 def audioGenerator(inputText):
     device = "cuda" if torch.cuda.is_available() else "cpu"
+    dtype = torch.float16 if torch.cuda.is_available() else torch.float32
     pipe = DiffusionPipeline.from_pretrained("teticio/audio-diffusion-256").to(device)
     output = pipe()
     from IPython.display import display
@@ -88,7 +89,7 @@ def generate_tone(note, octave, duration):
 
 def draw(inp, this_model, force_new):
     device = "cuda" if torch.cuda.is_available() else "cpu"
-    dtype = "torch.float16" if torch.cuda.is_available() else "torch.float32"
+    dtype = torch.float16 if torch.cuda.is_available() else torch.float32
     drawing = inp
     if this_model == "stable-diffusion-2":
         this_model_addr = "stabilityai/stable-diffusion-2"
@@ -141,7 +142,7 @@ def write_blog(inp, this_model, min_length, max_length, force_new):
               return file.read()
     print("generating blog '", blog_post_name, "'", target_filename)
     device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
-    dtype = "torch.float16" if torch.cuda.is_available() else "torch.float32"
+    dtype = torch.float16 if torch.cuda.is_available() else torch.float32
     #generator = pipeline('text-generation', model='EleutherAI/gpt-neo-2.7B', device=device, torch_dtype=dtype)
     #generator = pipeline('text-generation', model=this_model_addr, torch_dtype=dtype)
     #generator = pipeline('text-generation', model=this_model_addr)