adding zero gpu tags

app.py

@@ -1,5 +1,6 @@
 # imports from gradio_demo.py
 import gradio as gr 
+import spaces
 import numpy as np
 from PIL import Image
 import torch 
@@ -24,12 +25,16 @@ from tqdm import trange, tqdm
 from torchvision import transforms
 import k_diffusion as K
 
+zero = torch.Tensor([0]).cuda()
+print("Zero Device = ",zero.device," <-- this probably says cpu") # <-- 'cpu' 🤔
+
 
 from pom.pianoroll import regroup_lines, img_file_2_midi_file, square_to_rect, rect_to_square
 from pom.square_to_rect import square_to_rect
 
 CT_HOME = '.'
 
+@spaces.GPU
 def infer_mask_from_init_img(img, mask_with='grey'):
     "note, this works whether image is normalized on 0..1 or -1..1, but not 0..255"
     assert mask_with in ['blue','white','grey']
@@ -52,6 +57,7 @@ def infer_mask_from_init_img(img, mask_with='grey'):
     return mask*1.0
 
 
+@spaces.GPU
 def count_notes_in_mask(img, mask):
     "counts the number of new notes in the mask"
     img_t = ToTensor()(img)
@@ -59,6 +65,7 @@ def count_notes_in_mask(img, mask):
     return new_notes.item()
 
 
+@spaces.GPU
 def grab_dense_gen(init_img, 
                 PREFIX, 
                 num_to_gen=64, 
@@ -85,8 +92,9 @@ def grab_dense_gen(init_img,
     return dense_filename
 
 
-
+@spaces.GPU
 def process_image(image, repaint, busyness):
+    print("Process Image: Zero Device = ",zero.device)
     # get image ready and execute sampler
     print("image = ",image)
     image = image['composite']
@@ -136,11 +144,6 @@ def process_image(image, repaint, busyness):
 
     return gen_image, html, audio_file
 
-# def greet(name):
-#     return "Hello " + name + "!!"
-
-# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-# demo.launch()
 
 
 make_dict = lambda x: {'background':x, 'composite':x, 'layers':[x]}