mirror of
https://github.com/nod-ai/AMD-SHARK-Studio.git
synced 2026-04-03 03:00:17 -04:00
More fixes for demo.
This commit is contained in:
Ean Garvey
@@ -101,7 +101,7 @@ class StableDiffusion:
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external_weights: str = "safetensors",
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progress=gr.Progress(),
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):
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progress(0, desc="Initializing pipeline...")
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progress(None, desc="Initializing pipeline...")
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self.ui_device = device
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self.precision = precision
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self.compiled_pipeline = False
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@@ -181,7 +181,7 @@ class StableDiffusion:
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external_weights=external_weights,
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custom_vae=custom_vae,
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)
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progress(1, desc="Pipeline initialized!...")
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progress(None, desc="Pipeline initialized!...")
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gc.collect()
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def prepare_pipe(
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@@ -245,18 +245,18 @@ class StableDiffusion:
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"diffusion_pytorch_model.safetensors",
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)
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weights[key] = save_irpa(vae_weights_path, "vae.")
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progress(0, desc=f"Preparing pipeline for {self.ui_device}...")
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progress(None, desc=f"Preparing pipeline for {self.ui_device}...")
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vmfbs, weights = self.sd_pipe.check_prepared(
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mlirs, vmfbs, weights, interactive=False
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)
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progress(1, desc=f"Artifacts ready!")
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progress(0, desc=f"Loading pipeline on device {self.ui_device}...")
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progress(None, desc=f"Artifacts ready!")
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progress(None, desc=f"Loading pipeline on device {self.ui_device}...")
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self.sd_pipe.load_pipeline(
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vmfbs, weights, self.rt_device, self.compiled_pipeline
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)
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progress(1, desc="Pipeline loaded!")
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progress(None, desc="Pipeline loaded! Generating images...")
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return
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def generate_images(
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@@ -271,9 +271,9 @@ class StableDiffusion:
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resample_type,
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control_mode,
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hints,
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progress=gr.Progress(track_tqdm=True),
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progress=gr.Progress()
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):
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progress(0, desc="Generating images...")
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img = self.sd_pipe.generate_images(
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prompt,
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negative_prompt,
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@@ -282,7 +282,6 @@ class StableDiffusion:
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seed,
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return_imgs=True,
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)
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progress(1, desc="Image generation complete!")
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return img
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@@ -453,6 +452,8 @@ def shark_sd_fn(
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generated_imgs = []
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if seed == -1:
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seed = randint(0, sys.maxsize)
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progress(None, desc=f"Generating...")
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for current_batch in range(batch_count):
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start_time = time.time()
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out_imgs = global_obj.get_sd_obj().generate_images(**submit_run_kwargs)
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@@ -35,10 +35,7 @@ p.add_argument(
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"--prompt",
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nargs="+",
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default=[
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"a photo taken of the front of a super-car drifting on a road near "
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"mountains at high speeds with smoke coming off the tires, front "
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"angle, front point of view, trees in the mountains of the "
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"background, ((sharp focus))"
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"A hi-res photo of a red street racer drifting around a curve on a mountain, high altitude, at night, tokyo in the background, 8k"
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],
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help="Text of which images to be generated.",
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)
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@@ -62,7 +59,7 @@ p.add_argument(
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p.add_argument(
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"--steps",
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type=int,
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default=50,
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default=2,
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help="The number of steps to do the sampling.",
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)
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@@ -100,7 +97,7 @@ p.add_argument(
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p.add_argument(
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"--guidance_scale",
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type=float,
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default=7.5,
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default=0,
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help="The value to be used for guidance scaling.",
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)
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@@ -346,7 +343,7 @@ p.add_argument(
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p.add_argument(
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"--batch_count",
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type=int,
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default=1,
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default=4,
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help="Number of batches to be generated with random seeds in " "single execution.",
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)
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@@ -51,6 +51,7 @@ sd_default_models = [
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"stabilityai/stable-diffusion-xl-base-1.0",
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"stabilityai/sdxl-turbo",
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]
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sd_default_models.extend(get_checkpoints(model_type="scripts"))
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def view_json_file(file_path):
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@@ -200,7 +201,7 @@ def save_sd_cfg(config: dict, save_name: str):
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filepath += ".json"
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with open(filepath, mode="w") as f:
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f.write(json.dumps(config))
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return "..."
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return save_name
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def create_canvas(width, height):
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@@ -284,7 +285,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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label="\U000026F0\U0000FE0F Base Model",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="stabilityai/stable-diffusion-2-1-base",
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value="stabilityai/sdxl-turbo",
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choices=sd_default_models,
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allow_custom_value=True,
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) # base_model_id
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@@ -410,21 +411,21 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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seed = gr.Textbox(
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value=cmd_opts.seed,
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label="\U0001F331\U0000FE0F Seed",
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info="An integer or a JSON list of integers, -1 for random",
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info="An integer, -1 for random",
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show_copy_button=True,
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)
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scheduler = gr.Dropdown(
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elem_id="scheduler",
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label="\U0001F4C5\U0000FE0F Scheduler",
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info="\U000E0020", # forces same height as seed
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value="EulerDiscrete",
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value="EulerAncestralDiscrete",
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choices=scheduler_model_map.keys(),
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allow_custom_value=False,
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)
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with gr.Row():
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steps = gr.Slider(
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1,
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100,
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50,
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value=cmd_opts.steps,
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step=1,
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label="\U0001F3C3\U0000FE0F Steps",
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@@ -485,17 +486,17 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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with gr.Row():
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canvas_width = gr.Slider(
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label="Canvas Width",
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minimum=256,
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minimum=512,
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maximum=1024,
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value=512,
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step=8,
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step=512,
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)
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canvas_height = gr.Slider(
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label="Canvas Height",
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minimum=256,
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minimum=512,
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maximum=1024,
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value=512,
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step=8,
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step=512,
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)
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make_canvas = gr.Button(
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value="Make Canvas!",
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@@ -616,7 +617,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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visible=False, # DEMO
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)
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compiled_pipeline = gr.Checkbox(
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False,
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True,
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label="Faster txt2img (SDXL only)",
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)
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with gr.Row():
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@@ -627,7 +628,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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queue=False,
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show_progress=False,
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)
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stop_batch = gr.Button("Stop")
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stop_batch = gr.Button("Stop", visible=False)
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with gr.Tab(label="Config", id=102) as sd_tab_config:
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with gr.Column(elem_classes=["sd-right-panel"]):
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with gr.Row(elem_classes=["fill"]):
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@@ -653,7 +654,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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if cmd_opts.configs_path
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else get_configs_path()
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),
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height=75,
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height=200,
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)
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with gr.Column(scale=1):
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save_sd_config = gr.Button(
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@@ -664,13 +665,13 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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size="sm",
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components=sd_json,
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)
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with gr.Row():
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sd_config_name = gr.Textbox(
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value="Config Name",
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info="Name of the file this config will be saved to.",
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interactive=True,
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show_label=False,
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)
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#with gr.Row():
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sd_config_name = gr.Textbox(
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value="Config Name",
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info="Name of the file this config will be saved to.",
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interactive=True,
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show_label=False,
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)
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load_sd_config.change(
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fn=load_sd_cfg,
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inputs=[sd_json, load_sd_config],
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@@ -758,6 +759,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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outputs=[
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sd_json,
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],
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show_progress=False,
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)
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status_kwargs = dict(
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@@ -88,6 +88,8 @@ def get_checkpoints_path(model_type=""):
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def get_checkpoints(model_type="checkpoints"):
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ckpt_files = []
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file_types = checkpoints_filetypes
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if model_type == "scripts":
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file_types = ["shark_*.py"]
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if model_type == "lora":
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file_types = file_types + ("*.pt", "*.bin")
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for extn in file_types:
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@@ -89,7 +89,7 @@ else {python -m venv .\shark.venv\}
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python -m pip install --upgrade pip
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pip install wheel
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pip install --pre -r requirements.txt
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pip install --force-reinstall https://github.com/nod-ai/SRT/releases/download/candidate-20240528.279/iree_compiler-20240528.279-cp311-cp311-win_amd64.whl https://github.com/nod-ai/SRT/releases/download/candidate-20240528.279/iree_runtime-20240528.279-cp311-cp311-win_amd64.whl
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pip install --force-reinstall https://github.com/nod-ai/SRT/releases/download/candidate-20240601.282/iree_compiler-20240601.282-cp311-cp311-win_amd64.whl https://github.com/nod-ai/SRT/releases/download/candidate-20240601.282/iree_runtime-20240601.282-cp311-cp311-win_amd64.whl
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pip install -e .
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Write-Host "Source your venv with ./shark.venv/Scripts/activate"
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