Use Zero Spaces (#2)

- Update app.py (4991b244b5fa5ad2bc2da3ae398d3b53269df5c7)
- Update requirements.txt (7e13740cf2673a8fab6d0f5b4baef752b86c7b9d)
- Update requirements.txt (e095422a7dca7248cbb17d9df26e88f97b8dd2a3)
- Update README.md (9b6cd9151c82ec5d8fdb028c597ca2d725daf387)
- updates on change (3ceb728d939da3d6443d825c09ac2e06571644e5)
- no need for xformers on Spaces Zero (b7758dc0fb7aac6390e644ce988b5a60c7e65257)


Co-authored-by: Radamés Ajna <[email protected]>

README.md

@@ -4,7 +4,7 @@ emoji: ⚡
 colorFrom: purple
 colorTo: red
 sdk: gradio
-sdk_version: 4.26.0
+sdk_version: 4.36.0
 app_file: app.py
 pinned: false
 license: cc-by-nc-4.0

app.py

@@ -1,12 +1,15 @@
 import random
+import spaces
 
 import gradio as gr
 import numpy as np
 import torch
 from diffusers import LCMScheduler, PixArtAlphaPipeline, Transformer2DModel
 from peft import PeftModel
+import os
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
+IS_SPACE = os.environ.get("SPACE_ID", None) is not None
 
 transformer = Transformer2DModel.from_pretrained(
     "PixArt-alpha/PixArt-XL-2-1024-MS",
@@ -23,7 +26,8 @@ if torch.cuda.is_available():
         transformer=transformer,
         torch_dtype=torch.float16,
     )
-    pipe.enable_xformers_memory_efficient_attention()
+    if not IS_SPACE:
+        pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
 else:
     pipe = PixArtAlphaPipeline.from_pretrained(
@@ -46,8 +50,8 @@ MAX_IMAGE_SIZE = 1024
 NUM_INFERENCE_STEPS = 4
 
 
+@spaces.GPU
 def infer(prompt, seed, randomize_seed):
-
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
@@ -88,7 +92,6 @@ else:
     power_device = "CPU"
 
 with gr.Blocks(css=css) as demo:
-
     with gr.Column(elem_id="col-container"):
         gr.Markdown(
             f"""
@@ -107,7 +110,6 @@ with gr.Blocks(css=css) as demo:
         )
 
         with gr.Row():
-
             prompt = gr.Text(
                 label="Prompt",
                 show_label=False,
@@ -121,7 +123,6 @@ with gr.Blocks(css=css) as demo:
         result = gr.Image(label="Result", show_label=False)
 
         with gr.Accordion("Advanced Settings", open=False):
-
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,
@@ -134,14 +135,18 @@ with gr.Blocks(css=css) as demo:
 
         examples = gr.Examples(examples=examples, inputs=[prompt])
 
-        gr.Markdown(
-            "**Disclaimer:**"
-        )
+        gr.Markdown("**Disclaimer:**")
         gr.Markdown(
             "This demo is only for research purpose. Jasper cannot be held responsible for the generation of NSFW (Not Safe For Work) content through the use of this demo. Users are solely responsible for any content they create, and it is their obligation to ensure that it adheres to appropriate and ethical standards. Jasper provides the tools, but the responsibility for their use lies with the individual user."
         )
-
-    run_button.click(fn=infer, inputs=[prompt, seed, randomize_seed], outputs=[result])
-    seed.change(fn=infer, inputs=[prompt, seed, randomize_seed], outputs=[result])
+    gr.on(
+        [run_button.click, seed.change, prompt.change, randomize_seed.change],
+        fn=infer,
+        inputs=[prompt, seed, randomize_seed],
+        outputs=[result],
+        show_progress="minimal",
+        show_api=False,
+        trigger_mode="always_last",
+    )
 
 demo.queue().launch(show_api=False)

requirements.txt

@@ -1,5 +1,5 @@
 accelerate
-diffusers
+git+https://github.com/huggingface/diffusers/
 invisible_watermark
 --extra-index-url https://download.pytorch.org/whl/cu118
 torch==2.0.1
@@ -9,4 +9,5 @@ optimum
 beautifulsoup4
 transformers >= 4.34.0
 xformers
-ftfy
+ftfy
+spaces