More fixes

apps/stable_diffusion/src/models/model_wrappers.py

@@ -109,7 +109,7 @@ def process_vmfb_ir_sdxl(extended_model_name, model_name, device, precision):
     if "vulkan" in device:
         _device = args.iree_vulkan_target_triple
         _device = _device.replace("-", "_")
-        vmfb_path = Path(extended_model_name_for_vmfb + f"_{_device}.vmfb")
+        vmfb_path = Path(extended_model_name_for_vmfb + f"_vulkan.vmfb")
     if vmfb_path.exists():
         shark_module = SharkInference(
             None,

apps/stable_diffusion/src/models/opt_params.py

@@ -123,7 +123,10 @@ def get_clip():
     return get_shark_model(bucket, model_name, iree_flags)
 
 
-def get_tokenizer(subfolder="tokenizer"):
+def get_tokenizer(subfolder="tokenizer", hf_model_id=None):
+    if hf_model_id is not None:
+        args.hf_model_id = hf_model_id
+
     tokenizer = CLIPTokenizer.from_pretrained(
         args.hf_model_id, subfolder=subfolder
     )

apps/stable_diffusion/src/pipelines/pipeline_shark_stable_diffusion_utils.py

@@ -208,6 +208,9 @@ def encode_prompt_sdxl(
         negative_prompt_embeds: Optional[torch.FloatTensor] = None,
         pooled_prompt_embeds: Optional[torch.FloatTensor] = None,
         negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None,
+        hf_model_id: Optional[
+            str
+        ] = "stabilityai/stable-diffusion-xl-base-1.0",
     ):
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -217,7 +220,7 @@ def encode_prompt_sdxl(
             batch_size = prompt_embeds.shape[0]
 
         # Define tokenizers and text encoders
-        self.tokenizer_2 = get_tokenizer("tokenizer_2")
+        self.tokenizer_2 = get_tokenizer("tokenizer_2", hf_model_id)
         self.load_clip_sdxl()
         tokenizers = (
             [self.tokenizer, self.tokenizer_2]

apps/stable_diffusion/src/schedulers/shark_eulerancestraldiscrete.py

@@ -215,7 +215,6 @@ def step(
             device="cpu",
             generator=generator,
         )
-        self._step_index += 1
         step_inputs = [
             noise_pred,
             latent,
@@ -224,9 +223,10 @@ def step(
             sigma_to,
             noise,
         ]
-        print(step_inputs)
-        # TODO: Might not be proper behavior here... deal with dynamic inputs.
+        # TODO: deal with dynamic inputs in turbine flow.
         # update step index since we're done with the variable and will return with compiled module output.
+        self._step_index += 1
+
         if noise_pred.shape[0] < self.batch_size:
             for i in [0, 1, 5]:
                 try:

apps/stable_diffusion/web/index.py

@@ -110,11 +110,15 @@ def resource_path(relative_path):
         txt2img_sendto_outpaint,
         txt2img_sendto_upscaler,
         # SDXL
-        txt2img_sdxl_inf,
         txt2img_sdxl_web,
         txt2img_sdxl_custom_model,
         txt2img_sdxl_gallery,
+        txt2img_sdxl_png_info_img,
         txt2img_sdxl_status,
+        txt2img_sdxl_sendto_img2img,
+        txt2img_sdxl_sendto_inpaint,
+        txt2img_sdxl_sendto_outpaint,
+        txt2img_sdxl_sendto_upscaler,
         # h2ogpt_upload,
         # h2ogpt_web,
         img2img_web,
@@ -151,7 +155,7 @@ def resource_path(relative_path):
         upscaler_sendto_outpaint,
         #  lora_train_web,
         #  model_web,
-        #  model_config_web,
+        model_config_web,
         hf_models,
         modelmanager_sendto_txt2img,
         modelmanager_sendto_img2img,
@@ -165,6 +169,7 @@ def resource_path(relative_path):
         outputgallery_watch,
         outputgallery_filename,
         outputgallery_sendto_txt2img,
+        outputgallery_sendto_txt2img_sdxl,
         outputgallery_sendto_img2img,
         outputgallery_sendto_inpaint,
         outputgallery_sendto_outpaint,
@@ -241,6 +246,7 @@ def register_outputgallery_button(button, selectedid, inputs, outputs):
                         inpaint_status,
                         outpaint_status,
                         upscaler_status,
+                        txt2img_sdxl_status,
                     ]
                 )
             #  with gr.TabItem(label="Model Manager", id=6):
@@ -249,17 +255,17 @@ def register_outputgallery_button(button, selectedid, inputs, outputs):
             #      lora_train_web.render()
             with gr.TabItem(label="Chat Bot", id=8):
                 stablelm_chat.render()
-            #  with gr.TabItem(
-            #      label="Generate Sharding Config (Experimental)", id=9
-            #  ):
-            #      model_config_web.render()
-            with gr.TabItem(label="MultiModal (Experimental)", id=10):
-                minigpt4_web.render()
+            with gr.TabItem(
+                label="Generate Sharding Config (Experimental)", id=9
+            ):
+                model_config_web.render()
+            # with gr.TabItem(label="MultiModal (Experimental)", id=10):
+            #     minigpt4_web.render()
             # with gr.TabItem(label="DocuChat Upload", id=11):
             #     h2ogpt_upload.render()
             # with gr.TabItem(label="DocuChat(Experimental)", id=12):
             #     h2ogpt_web.render()
-            with gr.TabItem(label="Text-to-Image-SDXL (Experimental)", id=13):
+            with gr.TabItem(label="Text-to-Image (SDXL)", id=13):
                 txt2img_sdxl_web.render()
 
             actual_port = app.usable_port()

apps/stable_diffusion/web/ui/__init__.py

@@ -16,6 +16,11 @@
     txt2img_sdxl_custom_model,
     txt2img_sdxl_gallery,
     txt2img_sdxl_status,
+    txt2img_sdxl_png_info_img,
+    txt2img_sdxl_sendto_img2img,
+    txt2img_sdxl_sendto_inpaint,
+    txt2img_sdxl_sendto_outpaint,
+    txt2img_sdxl_sendto_upscaler,
 )
 from apps.stable_diffusion.web.ui.img2img_ui import (
     img2img_inf,
@@ -83,6 +88,7 @@
     outputgallery_watch,
     outputgallery_filename,
     outputgallery_sendto_txt2img,
+    outputgallery_sendto_txt2img_sdxl,
     outputgallery_sendto_img2img,
     outputgallery_sendto_inpaint,
     outputgallery_sendto_outpaint,

apps/stable_diffusion/web/ui/img2img_ui.py

@@ -426,19 +426,14 @@ def cnet_preview(
                                 return (None, stencils, images)
 
                     def create_canvas(width, height):
-                        return {
-                            "background": None,
-                            "layers": [
-                                Image.fromarray(
-                                    np.zeros(
-                                        shape=(height, width, 3),
-                                        dtype=np.uint8,
-                                    )
-                                    + 255
-                                )
-                            ],
-                            "composite": None,
-                        }
+                        data = (
+                            np.zeros(
+                                shape=(height, width, 3),
+                                dtype=np.uint8,
+                            )
+                            + 255
+                        )
+                        return data
 
                     def update_cn_input(model, width, height):
                         if model == "scribble":

apps/stable_diffusion/web/ui/outputgallery_ui.py

@@ -152,6 +152,7 @@ def output_subdirs() -> list[str]:
                     wrap=True,
                     elem_classes="output_parameters_dataframe",
                     value=[["Status", "No image selected"]],
+                    interactive=True,
                 )
 
             with gr.Accordion(label="Send To", open=True):
@@ -162,6 +163,12 @@ def output_subdirs() -> list[str]:
                         elem_classes="outputgallery_sendto",
                         size="sm",
                     )
+                    outputgallery_sendto_txt2img_sdxl = gr.Button(
+                        value="Txt2Img XL",
+                        interactive=False,
+                        elem_classes="outputgallery_sendto",
+                        size="sm",
+                    )
 
                     outputgallery_sendto_img2img = gr.Button(
                         value="Img2Img",
@@ -414,6 +421,7 @@ def on_select_tab(subdir_paths, request: gr.Request):
         [outputgallery_filename],
         [
             outputgallery_sendto_txt2img,
+            outputgallery_sendto_txt2img_sdxl,
             outputgallery_sendto_img2img,
             outputgallery_sendto_inpaint,
             outputgallery_sendto_outpaint,

apps/stable_diffusion/web/ui/txt2img_sdxl_ui.py

@@ -461,7 +461,7 @@ def txt2img_sdxl_inf(
                         show_label=False,
                         elem_id="gallery",
                         columns=[2],
-                        object_fit="contain",
+                        object_fit="scale_down",
                     )
                     std_output = gr.Textbox(
                         value=f"{t2i_sdxl_model_info}\n"
@@ -483,7 +483,18 @@ def txt2img_sdxl_inf(
                     )
                     stop_batch = gr.Button("Stop Batch")
                 with gr.Row():
-                    blank_thing_for_row = None
+                    txt2img_sdxl_sendto_img2img = gr.Button(
+                        value="Send To Img2Img"
+                    )
+                    txt2img_sdxl_sendto_inpaint = gr.Button(
+                        value="Send To Inpaint"
+                    )
+                    txt2img_sdxl_sendto_outpaint = gr.Button(
+                        value="Send To Outpaint"
+                    )
+                    txt2img_sdxl_sendto_upscaler = gr.Button(
+                        value="Send To Upscaler"
+                    )
 
         kwargs = dict(
             fn=txt2img_sdxl_inf,

apps/stable_diffusion/web/ui/utils.py

@@ -263,18 +263,19 @@ def cancel_sd():
 def set_model_default_configs(model_ckpt_or_id, jsonconfig=None):
     import gradio as gr
 
+    config_modelname = default_config_exists(model_ckpt_or_id)
     if jsonconfig:
         return get_config_from_json(jsonconfig)
-    elif default_config_exists(model_ckpt_or_id):
-        return default_configs[model_ckpt_or_id]
+    elif config_modelname:
+        return default_configs[config_modelname]
     # TODO: Use HF metadata to setup pipeline if available
     # elif is_valid_hf_id(model_ckpt_or_id):
     #     return get_HF_default_configs(model_ckpt_or_id)
     else:
         # We don't have default metadata to setup a good config. Do not change configs.
         return [
             gr.Textbox(label="Prompt", interactive=True, visible=True),
-            gr.update(),
+            gr.Textbox(label="Negative Prompt", interactive=True),
             gr.update(),
             gr.update(),
             gr.update(),
@@ -304,19 +305,21 @@ def default_config_exists(model_ckpt_or_id):
         "stabilityai/sdxl-turbo",
         "stabilityai/stable_diffusion-xl-base-1.0",
     ]:
-        return True
+        return model_ckpt_or_id
+    elif "turbo" in model_ckpt_or_id.lower():
+        return "stabilityai/sdxl-turbo"
     else:
-        return False
+        return None
 
 
 default_configs = {
     "stabilityai/sdxl-turbo": [
         gr.Textbox(label="", interactive=False, value=None, visible=False),
         gr.Textbox(
             label="Prompt",
-            value="An anthropomorphic shark writing code on an old tube monitor, macro shot, in an office filled with water, stop-animation style, claymation",
+            value="role-playing game (RPG) style fantasy, An enchanting image featuring an adorable kitten mage wearing intricate ancient robes, holding an ancient staff, hard at work in her fantastical workshop, magic runes floating in the air",
         ),
-        gr.Slider(0, 5, value=2),
+        gr.Slider(0, 10, value=2),
         gr.Dropdown(value="EulerAncestralDiscrete"),
         gr.Slider(0, value=0),
         512,

shark/parser.py

@@ -155,7 +155,7 @@ def __call__(self, parser, namespace, values, option_string=None):
 
 parser.add_argument(
     "--vulkan_debug_utils",
-    default=True,
+    default=False,
     action=argparse.BooleanOptionalAction,
     help="Profiles vulkan device and collects the .rdc info.",
 )