Update app.py

app.py

@@ -484,7 +484,7 @@ def text_to_image(prompt,slider_step,slider_guidance,slider_batch, version):
         text_encoder = text_encoder21
         tokenizer = tokenizer21
         scheduler = scheduler21
-        slider_batch = min(slider_batch, 2)
+        slider_batch = min(slider_batch, 1)
         size = 768
     elif version == 'Stable Diffusion v1.5':
         vae = vae15
@@ -612,7 +612,7 @@ def text_to_image_with_template(prompt,template_image,slider_step,slider_guidanc
         text_encoder = text_encoder21
         tokenizer = tokenizer21
         scheduler = scheduler21
-        slider_batch = min(slider_batch, 2)
+        slider_batch = min(slider_batch, 1)
         size = 768
     elif version == 'Stable Diffusion v1.5':
         vae = vae15
@@ -736,7 +736,7 @@ def text_inpainting(prompt,orig_image,mask_image,slider_step,slider_guidance,sli
         text_encoder = text_encoder21
         tokenizer = tokenizer21
         scheduler = scheduler21
-        slider_batch = min(slider_batch, 2)
+        slider_batch = min(slider_batch, 1)
         size = 768
     elif version == 'Stable Diffusion v1.5':
         vae = vae15
@@ -906,7 +906,7 @@ with gr.Blocks() as demo:
                 radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
-                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 【2】 for SD v2.1 to avoid OOM.")
+                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")
                 # slider_seed = gr.Slider(minimum=1, maximum=10000, label="Seed", randomize=True)
                 button = gr.Button("Generate")
                             
@@ -957,7 +957,7 @@ with gr.Blocks() as demo:
                 radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
-                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 【2】 for SD v2.1 to avoid OOM.")
+                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")
                 # binary = gr.Radio(["park", "zoo", "road"], label="Location", info="Where did they go?")
                 binary = gr.Checkbox(label="Binarization", bool=True, info="Whether to binarize the template image? You may need it when using handwritten images as templates.")
                 button = gr.Button("Generate")
@@ -1007,7 +1007,7 @@ with gr.Blocks() as demo:
                 radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
-                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 【2】 for SD v2.1 to avoid OOM.")
+                slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")
                 button = gr.Button("Generate")
             with gr.Column(scale=1):
                 output = gr.Image(label='Generated image')