update README

app.py

@@ -194,10 +194,10 @@ def run(cfg: DictConfig):
     #     return new_frame
 
     def set_denoising_steps(denoising_steps, sampling_timesteps_state):
-        algo.sampling_timesteps = denoising_steps
-        algo.diffusion_model.sampling_timesteps = denoising_steps
+        runner.algo.sampling_timesteps = denoising_steps
+        runner.algo.diffusion_model.sampling_timesteps = denoising_steps
         sampling_timesteps_state = denoising_steps
-        print("set denoising steps to", algo.sampling_timesteps)
+        print("set denoising steps to", runner.algo.sampling_timesteps)
         return sampling_timesteps_state
 
     def update_image_and_log(keys):
@@ -205,7 +205,7 @@ def run(cfg: DictConfig):
         global input_history
         global memory_curr_frame
 
-        print("algo frame:", len(algo.frames))
+        print("algo frame:", len(runner.algo.frames))
         
         for i in range(len(actions)):
             memory_curr_frame += 1
@@ -244,7 +244,9 @@ def run(cfg: DictConfig):
         global input_history
         global memory_frames
 
-        algo.reset()
+        device = next(runner.algo.parameters()).device
+        print(device)
+        runner.algo.reset()
         memory_frames = []
         memory_frames.append(load_image_as_tensor(DEFAULT_IMAGE))
         memory_curr_frame = 0
@@ -328,11 +330,11 @@ def run(cfg: DictConfig):
                 input_box = gr.Textbox(label="Action Sequence", placeholder="Enter action sequence here...", lines=1, max_lines=1)
                 log_output = gr.Textbox(label="History Log", interactive=False)
             with gr.Column(scale=1):
-                slider = gr.Slider(minimum=10, maximum=50, value=algo.sampling_timesteps, step=1, label="Denoising Steps")
+                slider = gr.Slider(minimum=10, maximum=50, value=runner.algo.sampling_timesteps, step=1, label="Denoising Steps")
                 submit_button = gr.Button("Generate")
                 reset_btn = gr.Button("Reset")
         
-        sampling_timesteps_state = gr.State(algo.sampling_timesteps)
+        sampling_timesteps_state = gr.State(runner.algo.sampling_timesteps)
         
         example_actions = ["DDDDDDDDEEEEEEEEEESSSAAAAAAAAWWW", "DDDDDDDDDDDDQQQQQQQQQQQQQQQDDDDDDDDDDDD", 
         "DDDDWWWDDDDDDDDDDDDDDDDDDDDSSSAAAAAAAAAAAAAAAAAAAAAAAA", "SSUNNWWEEEEEEEEEAAA1NNNNNNNNNSSUNNWW"]