Update app.py

app.py

@@ -25,13 +25,9 @@ from diffusers.models.modeling_utils import ModelMixin
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file, save_file
 from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler, DDIMScheduler, StableDiffusionXLPipeline, UNet2DConditionModel, AutoencoderKL, UNet3DConditionModel
-#import jax
-#import jax.numpy as jnp
-from numba import cuda, njit as cpu, void, int64 as int, float64 as float, boolean as bool, uint8 as rgb
-from numba.cuda import jit as gpu, grid, as_cuda_array as tensor2array
-from numba.types import unicode_type as string
-from PIL.Image import fromarray as array2image
-import numpy as np
+from numba import jit, void as vid, int64 as int, float64 as flt, boolean as bol, uint8 as rgb
+from numba.types import unicode_type as str
+from functools import partial
 
 # logging
 
@@ -49,10 +45,14 @@ formatter = logging.Formatter('\n >>> [%(levelname)s] %(asctime)s %(name)s: %(me
 handler2.setFormatter(formatter)
 root.addHandler(handler2)
 
-# output data
+# jit decorator shortcuts
 
-out_pipe=array([""])
-last_motion=array([""])
+math = partial(jit, cache=True, parallel=True)
+loop = partial(jit, cache=True, forceobj=True)
+
+# storage data
+
+last_motion=""
 
 # constant data
 
@@ -69,8 +69,8 @@ adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-
 # precision data
 
 fast=True
-fps=10
-time=1
+fps=15
+time=3
 width=384
 height=768
 step=40
@@ -135,7 +135,6 @@ pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapt
 pipe.enable_vae_slicing()
 pipe.enable_free_init(method="butterworth", use_fast_sampling=fast)
 
-
 # functionality
 
 def run(cmd):
@@ -187,26 +186,22 @@ def generate_random_string(length):
     characters = str(ascii_letters + digits)
     return ''.join(random.choice(characters) for _ in range(length))
     
-@gpu(void( rgb[:], string[:], string[:], string[:] ))
 def calc(img,p1,p2,motion):
-    global out_pipe
     global last_motion
     global pipe
 
-    x = grid(1)
-
-    if last_motion[0] != motion:
+    if last_motion != motion:
         pipe.unload_lora_weights()
         if inp[3] != "":
             pipe.load_lora_weights(motion, adapter_name="motion")
             pipe.fuse_lora()
             pipe.set_adapters("motion", [0.7])
-        last_motion[0] = motion
+        last_motion = motion
 
     pipe.to(device,dtype)
 
     if p2=="":
-        out_pipe[x] = pipe(
+        return pipe(
             prompt=p1,
             height=height,
             width=width,
@@ -216,7 +211,7 @@ def calc(img,p1,p2,motion):
             num_frames=(fps*time)
         )
     
-    out_pipe[x] = pipe(
+    return pipe(
         prompt=p1,
         negative_prompt=p2,
         height=height,
@@ -227,6 +222,7 @@ def calc(img,p1,p2,motion):
         num_frames=(fps*time)
     )
 
+@loop
 def handle(*inp):
     
     inp[1] = translate(inp[1],"english")
@@ -249,9 +245,10 @@ def handle(*inp):
     inp[1] = array(inp[1])
     inp[2] = array(inp[2])
     inp[3] = array(inp[3])
-    calc[ln,32](*inp)
-
+    
+    out_pipe = []
     for i in range(ln):
+        out_pipe = calc(*inp)
         name = generate_random_string(12)+".png"
         export_to_gif(out_pipe[i].frames[0],name,fps=fps)
         out_pipe[i] = name
@@ -329,7 +326,7 @@ def entry():
     os.chdir(os.path.abspath(os.path.dirname(__file__)))
     
     ui()
-    events[1,32]()
+    events()
 
 # entry