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https://github.com/nod-ai/SHARK-Studio.git
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3 Commits
20240602.1
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debug
| Author | SHA1 | Date | |
|---|---|---|---|
|
4529fd0461 | ||
|
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4c2bb4b7b4 | ||
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d5013fd13e |
@@ -25,14 +25,6 @@ def imports():
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)
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torch")
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warnings.filterwarnings(action="ignore", category=UserWarning, module="diffusers")
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warnings.filterwarnings(action="ignore", category=FutureWarning, module="diffusers")
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warnings.filterwarnings(
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action="ignore", category=FutureWarning, module="huggingface-hub"
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)
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warnings.filterwarnings(
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action="ignore", category=UserWarning, module="huggingface-hub"
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)
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import gradio # noqa: F401
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@@ -99,10 +99,7 @@ class StableDiffusion:
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import_ir: bool = True,
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is_controlled: bool = False,
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external_weights: str = "safetensors",
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progress=gr.Progress(),
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):
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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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self.base_model_id = base_model_id
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@@ -115,15 +112,12 @@ class StableDiffusion:
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"custom_pipeline",
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)
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self.turbine_pipe = custom_module.StudioPipeline
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self.dynamic_steps = custom_module.dynamic_steps
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self.model_map = custom_module.MODEL_MAP
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elif self.is_sdxl:
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self.turbine_pipe = SharkSDXLPipeline
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self.dynamic_steps = False
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self.model_map = EMPTY_SDXL_MAP
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else:
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self.turbine_pipe = SharkSDPipeline
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self.dynamic_steps = True
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self.model_map = EMPTY_SD_MAP
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max_length = 64
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target_backend, self.rt_device, triple = parse_device(device, target_triple)
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@@ -184,19 +178,13 @@ 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(None, desc="Pipeline initialized!...")
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print(f"\n[LOG] Pipeline initialized with pipe_id: {self.pipe_id}.")
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gc.collect()
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def prepare_pipe(
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self,
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custom_weights,
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adapters,
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embeddings,
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is_img2img,
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compiled_pipeline,
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progress=gr.Progress(),
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self, custom_weights, adapters, embeddings, is_img2img, compiled_pipeline
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):
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print(f"\n[LOG] Preparing pipeline...")
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self.is_img2img = False
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mlirs = copy.deepcopy(self.model_map)
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vmfbs = copy.deepcopy(self.model_map)
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@@ -248,18 +236,17 @@ 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(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(None, desc=f"Artifacts ready!")
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progress(None, desc=f"Loading pipeline on device {self.ui_device}...")
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print(f"\n[LOG] Loading pipeline to device {self.rt_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(None, desc="Pipeline loaded! Generating images...")
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print(
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"\n[LOG] Pipeline successfully prepared for runtime. Generating images..."
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)
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return
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def generate_images(
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@@ -274,9 +261,7 @@ 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(),
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):
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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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@@ -288,7 +273,9 @@ class StableDiffusion:
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return img
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def shark_sd_fn_dict_input(sd_kwargs: dict, *, progress=gr.Progress()):
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def shark_sd_fn_dict_input(
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sd_kwargs: dict,
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):
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print("\n[LOG] Submitting Request...")
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for key in sd_kwargs:
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@@ -319,7 +306,7 @@ def shark_sd_fn_dict_input(sd_kwargs: dict, *, progress=gr.Progress()):
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)
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return None, ""
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if sd_kwargs["target_triple"] == "":
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if not parse_device(sd_kwargs["device"], sd_kwargs["target_triple"])[2]:
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if parse_device(sd_kwargs["device"], sd_kwargs["target_triple"])[2] == "":
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gr.Warning(
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"Target device architecture could not be inferred. Please specify a target triple, e.g. 'gfx1100' for a Radeon 7900xtx."
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)
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@@ -353,8 +340,6 @@ def shark_sd_fn(
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resample_type: str,
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controlnets: dict,
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embeddings: dict,
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seed_increment: str | int = 1,
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progress=gr.Progress(),
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):
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sd_kwargs = locals()
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if not isinstance(sd_init_image, list):
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@@ -428,9 +413,6 @@ def shark_sd_fn(
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"control_mode": control_mode,
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"hints": hints,
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}
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if global_obj.get_sd_obj() and global_obj.get_sd_obj().dynamic_steps:
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submit_run_kwargs["steps"] = submit_pipe_kwargs["steps"]
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submit_pipe_kwargs.pop("steps")
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if (
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not global_obj.get_sd_obj()
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or global_obj.get_pipe_kwargs() != submit_pipe_kwargs
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@@ -456,11 +438,6 @@ def shark_sd_fn(
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global_obj.get_sd_obj().prepare_pipe(**submit_prep_kwargs)
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generated_imgs = []
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if seed in [-1, "-1"]:
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seed = randint(0, 4294967295)
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print(f"\n[LOG] Random seed: {seed}")
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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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@@ -479,20 +456,14 @@ def shark_sd_fn(
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sd_kwargs,
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)
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generated_imgs.extend(out_imgs)
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seed = get_next_seed(seed, seed_increment)
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# TODO: make seed changes over batch counts more configurable.
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submit_run_kwargs["seed"] = submit_run_kwargs["seed"] + 1
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yield generated_imgs, status_label(
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"Stable Diffusion", current_batch + 1, batch_count, batch_size
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)
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return (generated_imgs, "")
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def get_next_seed(seed, seed_increment):
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if isinstance(seed_increment, int):
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return int(seed + seed_increment)
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elif seed_increment == "random":
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return randint(0, sys.maxsize)
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def unload_sd():
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print("Unloading models.")
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import apps.shark_studio.web.utils.globals as global_obj
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@@ -54,31 +54,31 @@ def get_available_devices():
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available_devices = []
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rocm_devices = get_devices_by_name("rocm")
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available_devices.extend(rocm_devices)
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# cpu_device = get_devices_by_name("cpu-sync")
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# available_devices.extend(cpu_device)
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cpu_device = get_devices_by_name("cpu-sync")
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available_devices.extend(cpu_device)
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cpu_device = get_devices_by_name("cpu-task")
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available_devices.extend(cpu_device)
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# from shark.iree_utils.vulkan_utils import (
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# get_all_vulkan_devices,
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# )
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from shark.iree_utils.vulkan_utils import (
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get_all_vulkan_devices,
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)
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# vulkaninfo_list = get_all_vulkan_devices()
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# vulkan_devices = []
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# id = 0
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# for device in vulkaninfo_list:
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# vulkan_devices.append(f"{device.strip()} => vulkan://{id}")
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# id += 1
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# if id != 0:
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# print(f"vulkan devices are available.")
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vulkaninfo_list = get_all_vulkan_devices()
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vulkan_devices = []
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id = 0
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for device in vulkaninfo_list:
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vulkan_devices.append(f"{device.strip()} => vulkan://{id}")
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id += 1
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if id != 0:
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print(f"vulkan devices are available.")
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# available_devices.extend(vulkan_devices)
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# metal_devices = get_devices_by_name("metal")
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# available_devices.extend(metal_devices)
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# cuda_devices = get_devices_by_name("cuda")
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# available_devices.extend(cuda_devices)
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# hip_devices = get_devices_by_name("hip")
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# available_devices.extend(hip_devices)
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available_devices.extend(vulkan_devices)
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metal_devices = get_devices_by_name("metal")
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available_devices.extend(metal_devices)
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cuda_devices = get_devices_by_name("cuda")
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available_devices.extend(cuda_devices)
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hip_devices = get_devices_by_name("hip")
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available_devices.extend(hip_devices)
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for idx, device_str in enumerate(available_devices):
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if "AMD Radeon(TM) Graphics =>" in device_str:
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@@ -160,8 +160,6 @@ def parse_device(device_str, target_override=""):
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rt_device = rt_driver
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if target_override:
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if "cpu" in device_str:
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rt_device = "local-task"
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return target_backend, rt_device, target_override
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match target_backend:
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case "vulkan-spirv":
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@@ -171,10 +169,7 @@ def parse_device(device_str, target_override=""):
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triple = get_rocm_target_chip(device_str)
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return target_backend, rt_device, triple
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case "llvm-cpu":
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if "Ryzen 9" in device_str:
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return target_backend, "local-task", "znver4"
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else:
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return "llvm-cpu", "local-task", "x86_64-linux-gnu"
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return "llvm-cpu", "local-task", "x86_64-linux-gnu"
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def get_rocm_target_chip(device_str):
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@@ -71,14 +71,7 @@ def save_irpa(weights_path, prepend_str):
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new_key = prepend_str + key
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archive.add_tensor(new_key, weights[key])
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if "safetensors" in weights_path:
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irpa_file = weights_path.replace(".safetensors", ".irpa")
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elif "irpa" in weights_path:
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irpa_file = weights_path
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else:
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return Exception(
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"Invalid file format. Please provide a .safetensors or .irpa file."
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)
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irpa_file = weights_path.replace(".safetensors", ".irpa")
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archive.save(irpa_file)
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return irpa_file
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@@ -33,8 +33,6 @@ def save_output_img(output_img, img_seed, extra_info=None):
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if extra_info is None:
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extra_info = {}
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elif "progress" in extra_info.keys():
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extra_info.pop("progress")
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generated_imgs_path = Path(
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get_generated_imgs_path(), get_generated_imgs_todays_subdir()
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)
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@@ -35,7 +35,10 @@ p.add_argument(
|
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"--prompt",
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nargs="+",
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default=[
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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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"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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],
|
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help="Text of which images to be generated.",
|
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)
|
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@@ -59,7 +62,7 @@ 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=2,
|
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default=50,
|
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help="The number of steps to do the sampling.",
|
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)
|
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|
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@@ -97,7 +100,7 @@ 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=0,
|
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default=7.5,
|
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help="The value to be used for guidance scaling.",
|
||||
)
|
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|
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@@ -343,7 +346,7 @@ p.add_argument(
|
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p.add_argument(
|
||||
"--batch_count",
|
||||
type=int,
|
||||
default=4,
|
||||
default=1,
|
||||
help="Number of batches to be generated with random seeds in " "single execution.",
|
||||
)
|
||||
|
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|
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@@ -1,20 +0,0 @@
|
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from apps.shark_studio.modules.ckpt_processing import save_irpa
|
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import argparse
|
||||
import safetensors
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument(
|
||||
"--input",
|
||||
type=str,
|
||||
default="",
|
||||
help="input safetensors/irpa",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--prefix",
|
||||
type=str,
|
||||
default="",
|
||||
help="prefix to add to all the keys in the irpa",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
output_file = save_irpa(args.input, args.prefix)
|
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print("saved irpa to", output_file, "with prefix", args.prefix)
|
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@@ -194,7 +194,7 @@ def webui():
|
||||
sd_element.render()
|
||||
with gr.TabItem(label="Output Gallery", id=1):
|
||||
outputgallery_element.render()
|
||||
with gr.TabItem(label="Chat Bot", id=2, visible=False):
|
||||
with gr.TabItem(label="Chat Bot", id=2):
|
||||
chat_element.render()
|
||||
|
||||
studio_web.queue()
|
||||
|
||||
@@ -45,13 +45,12 @@ from apps.shark_studio.modules import logger
|
||||
import apps.shark_studio.web.utils.globals as global_obj
|
||||
|
||||
sd_default_models = [
|
||||
# "runwayml/stable-diffusion-v1-5",
|
||||
# "stabilityai/stable-diffusion-2-1-base",
|
||||
# "stabilityai/stable-diffusion-2-1",
|
||||
"runwayml/stable-diffusion-v1-5",
|
||||
"stabilityai/stable-diffusion-2-1-base",
|
||||
"stabilityai/stable-diffusion-2-1",
|
||||
"stabilityai/stable-diffusion-xl-base-1.0",
|
||||
"stabilityai/sdxl-turbo",
|
||||
]
|
||||
sd_default_models.extend(get_checkpoints(model_type="scripts"))
|
||||
|
||||
|
||||
def view_json_file(file_path):
|
||||
@@ -159,8 +158,6 @@ def load_sd_cfg(sd_json: dict, load_sd_config: str):
|
||||
sd_image = [Image.open(i, mode="r")]
|
||||
else:
|
||||
sd_image = None
|
||||
if not sd_json["device"]:
|
||||
sd_json["device"] = gr.update()
|
||||
|
||||
return [
|
||||
sd_json["prompt"][0],
|
||||
@@ -168,7 +165,7 @@ def load_sd_cfg(sd_json: dict, load_sd_config: str):
|
||||
sd_image,
|
||||
sd_json["height"],
|
||||
sd_json["width"],
|
||||
gr.update(),
|
||||
sd_json["steps"],
|
||||
sd_json["strength"],
|
||||
sd_json["guidance_scale"],
|
||||
sd_json["seed"],
|
||||
@@ -201,7 +198,7 @@ def save_sd_cfg(config: dict, save_name: str):
|
||||
filepath += ".json"
|
||||
with open(filepath, mode="w") as f:
|
||||
f.write(json.dumps(config))
|
||||
return save_name
|
||||
return "..."
|
||||
|
||||
|
||||
def create_canvas(width, height):
|
||||
@@ -238,42 +235,11 @@ def base_model_changed(base_model_id):
|
||||
new_choices = get_checkpoints(
|
||||
os.path.join("checkpoints", os.path.basename(str(base_model_id)))
|
||||
) + get_checkpoints(model_type="checkpoints")
|
||||
if "turbo" in base_model_id:
|
||||
new_steps = gr.Dropdown(
|
||||
value=cmd_opts.steps,
|
||||
choices=[1, 2, 3, 4],
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=False,
|
||||
)
|
||||
if "stable-diffusion-xl-base-1.0" in base_model_id:
|
||||
new_steps = gr.Dropdown(
|
||||
value=40,
|
||||
choices=[20, 25, 30, 35, 40, 45, 50],
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=False,
|
||||
)
|
||||
elif ".py" in base_model_id:
|
||||
new_steps = gr.Dropdown(
|
||||
value=20,
|
||||
choices=[10, 15, 20, 28],
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=True,
|
||||
)
|
||||
else:
|
||||
new_steps = gr.Dropdown(
|
||||
value=cmd_opts.steps,
|
||||
choices=[10, 20, 30, 40, 50],
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=True,
|
||||
)
|
||||
|
||||
return [
|
||||
gr.Dropdown(
|
||||
value=new_choices[0] if len(new_choices) > 0 else "None",
|
||||
choices=["None"] + new_choices,
|
||||
),
|
||||
new_steps,
|
||||
]
|
||||
return gr.Dropdown(
|
||||
value=new_choices[0] if len(new_choices) > 0 else "None",
|
||||
choices=["None"] + new_choices,
|
||||
)
|
||||
|
||||
|
||||
with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
@@ -290,17 +256,16 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
choices=global_obj.get_device_list(),
|
||||
allow_custom_value=False,
|
||||
)
|
||||
target_triple = gr.Textbox(
|
||||
elem_id="target_triple",
|
||||
label="Architecture",
|
||||
value="",
|
||||
)
|
||||
with gr.Row():
|
||||
ondemand = gr.Checkbox(
|
||||
value=cmd_opts.lowvram,
|
||||
label="Low VRAM",
|
||||
interactive=True,
|
||||
visible=False,
|
||||
)
|
||||
target_triple = gr.Textbox(
|
||||
elem_id="target_triple",
|
||||
label="Architecture",
|
||||
value="",
|
||||
)
|
||||
precision = gr.Radio(
|
||||
label="Precision",
|
||||
@@ -316,29 +281,27 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
label="\U000026F0\U0000FE0F Base Model",
|
||||
info="Select or enter HF model ID",
|
||||
elem_id="custom_model",
|
||||
value="stabilityai/sdxl-turbo",
|
||||
value="stabilityai/stable-diffusion-2-1-base",
|
||||
choices=sd_default_models,
|
||||
allow_custom_value=True,
|
||||
) # base_model_id
|
||||
with gr.Row():
|
||||
height = gr.Slider(
|
||||
512,
|
||||
384,
|
||||
1024,
|
||||
value=512,
|
||||
step=512,
|
||||
value=cmd_opts.height,
|
||||
step=8,
|
||||
label="\U00002195\U0000FE0F Height",
|
||||
)
|
||||
width = gr.Slider(
|
||||
512,
|
||||
384,
|
||||
1024,
|
||||
value=512,
|
||||
step=512,
|
||||
value=cmd_opts.width,
|
||||
step=8,
|
||||
label="\U00002194\U0000FE0F Width",
|
||||
)
|
||||
with gr.Accordion(
|
||||
label="\U00002696\U0000FE0F Model Weights",
|
||||
open=False,
|
||||
visible=False, # DEMO
|
||||
label="\U00002696\U0000FE0F Model Weights", open=False
|
||||
):
|
||||
with gr.Column():
|
||||
custom_weights = gr.Dropdown(
|
||||
@@ -350,6 +313,11 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
choices=["None"]
|
||||
+ get_checkpoints(os.path.basename(str(base_model_id))),
|
||||
) # custom_weights
|
||||
base_model_id.change(
|
||||
fn=base_model_changed,
|
||||
inputs=[base_model_id],
|
||||
outputs=[custom_weights],
|
||||
)
|
||||
sd_vae_info = (str(get_checkpoints_path("vae"))).replace(
|
||||
"\\", "\n\\"
|
||||
)
|
||||
@@ -401,9 +369,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
show_progress=False,
|
||||
)
|
||||
with gr.Accordion(
|
||||
label="\U0001F9EA\U0000FE0F Input Image Processing",
|
||||
open=False,
|
||||
visible=False,
|
||||
label="\U0001F9EA\U0000FE0F Input Image Processing", open=False
|
||||
):
|
||||
strength = gr.Slider(
|
||||
0,
|
||||
@@ -437,23 +403,24 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
seed = gr.Textbox(
|
||||
value=cmd_opts.seed,
|
||||
label="\U0001F331\U0000FE0F Seed",
|
||||
info="An integer, -1 for random",
|
||||
info="An integer or a JSON list of integers, -1 for random",
|
||||
show_copy_button=True,
|
||||
)
|
||||
scheduler = gr.Dropdown(
|
||||
elem_id="scheduler",
|
||||
label="\U0001F4C5\U0000FE0F Scheduler",
|
||||
info="\U000E0020", # forces same height as seed
|
||||
value="EulerAncestralDiscrete",
|
||||
value="EulerDiscrete",
|
||||
choices=scheduler_model_map.keys(),
|
||||
allow_custom_value=False,
|
||||
)
|
||||
with gr.Row():
|
||||
steps = gr.Dropdown(
|
||||
steps = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.steps,
|
||||
choices=[1, 2, 3, 4],
|
||||
step=1,
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=True,
|
||||
)
|
||||
guidance_scale = gr.Slider(
|
||||
0,
|
||||
@@ -511,17 +478,17 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
with gr.Row():
|
||||
canvas_width = gr.Slider(
|
||||
label="Canvas Width",
|
||||
minimum=512,
|
||||
minimum=256,
|
||||
maximum=1024,
|
||||
value=512,
|
||||
step=512,
|
||||
step=8,
|
||||
)
|
||||
canvas_height = gr.Slider(
|
||||
label="Canvas Height",
|
||||
minimum=512,
|
||||
minimum=256,
|
||||
maximum=1024,
|
||||
value=512,
|
||||
step=512,
|
||||
step=8,
|
||||
)
|
||||
make_canvas = gr.Button(
|
||||
value="Make Canvas!",
|
||||
@@ -591,9 +558,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
lambda: gr.Tabs(selected=101),
|
||||
outputs=[sd_tabs],
|
||||
)
|
||||
with gr.Tab(
|
||||
label="Input Image", id=100, visible=False
|
||||
) as sd_tab_init_image: # DEMO
|
||||
with gr.Tab(label="Input Image", id=100) as sd_tab_init_image:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
# TODO: make this import image prompt info if it exists
|
||||
@@ -639,10 +604,10 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
step=1,
|
||||
label="Batch Size",
|
||||
interactive=True,
|
||||
visible=False, # DEMO
|
||||
visible=True,
|
||||
)
|
||||
compiled_pipeline = gr.Checkbox(
|
||||
True,
|
||||
False,
|
||||
label="Faster txt2img (SDXL only)",
|
||||
)
|
||||
with gr.Row():
|
||||
@@ -653,18 +618,18 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
queue=False,
|
||||
show_progress=False,
|
||||
)
|
||||
stop_batch = gr.Button("Stop", visible=False)
|
||||
stop_batch = gr.Button("Stop")
|
||||
with gr.Tab(label="Config", id=102) as sd_tab_config:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
Path(get_configs_path()).mkdir(
|
||||
parents=True, exist_ok=True
|
||||
)
|
||||
write_default_sd_configs(get_configs_path())
|
||||
default_config_file = os.path.join(
|
||||
get_configs_path(),
|
||||
"sdxl-turbo.json",
|
||||
"default_sd_config.json",
|
||||
)
|
||||
write_default_sd_configs(get_configs_path())
|
||||
sd_json = gr.JSON(
|
||||
elem_classes=["fill"],
|
||||
value=view_json_file(default_config_file),
|
||||
@@ -679,7 +644,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
if cmd_opts.configs_path
|
||||
else get_configs_path()
|
||||
),
|
||||
height=200,
|
||||
height=75,
|
||||
)
|
||||
with gr.Column(scale=1):
|
||||
save_sd_config = gr.Button(
|
||||
@@ -690,13 +655,13 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
size="sm",
|
||||
components=sd_json,
|
||||
)
|
||||
# with gr.Row():
|
||||
sd_config_name = gr.Textbox(
|
||||
value="Config Name",
|
||||
info="Name of the file this config will be saved to.",
|
||||
interactive=True,
|
||||
show_label=False,
|
||||
)
|
||||
with gr.Row():
|
||||
sd_config_name = gr.Textbox(
|
||||
value="Config Name",
|
||||
info="Name of the file this config will be saved to.",
|
||||
interactive=True,
|
||||
show_label=False,
|
||||
)
|
||||
load_sd_config.change(
|
||||
fn=load_sd_cfg,
|
||||
inputs=[sd_json, load_sd_config],
|
||||
@@ -753,11 +718,6 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
logger.read_sd_logs, None, std_output, every=1
|
||||
)
|
||||
sd_status = gr.Textbox(visible=False)
|
||||
base_model_id.change(
|
||||
fn=base_model_changed,
|
||||
inputs=[base_model_id],
|
||||
outputs=[custom_weights, steps],
|
||||
)
|
||||
|
||||
pull_kwargs = dict(
|
||||
fn=pull_sd_configs,
|
||||
@@ -789,7 +749,6 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
outputs=[
|
||||
sd_json,
|
||||
],
|
||||
show_progress=False,
|
||||
)
|
||||
|
||||
status_kwargs = dict(
|
||||
|
||||
@@ -89,7 +89,7 @@ sdxl_turbo = r"""{
|
||||
}"""
|
||||
|
||||
default_sd_configs = {
|
||||
# "default_sd_config.json": sdxl_turbo,
|
||||
"default_sd_config.json": default_sd_config,
|
||||
"sdxl-30steps.json": sdxl_30steps,
|
||||
"sdxl-turbo.json": sdxl_turbo,
|
||||
}
|
||||
|
||||
@@ -17,9 +17,8 @@ from apps.shark_studio.web.utils.default_configs import default_sd_configs
|
||||
def write_default_sd_configs(path):
|
||||
for key in default_sd_configs.keys():
|
||||
config_fpath = os.path.join(path, key)
|
||||
if not os.path.exists(config_fpath):
|
||||
with open(config_fpath, "w") as f:
|
||||
f.write(default_sd_configs[key])
|
||||
with open(config_fpath, "w") as f:
|
||||
f.write(default_sd_configs[key])
|
||||
|
||||
|
||||
def safe_name(name):
|
||||
@@ -88,8 +87,6 @@ def get_checkpoints_path(model_type=""):
|
||||
def get_checkpoints(model_type="checkpoints"):
|
||||
ckpt_files = []
|
||||
file_types = checkpoints_filetypes
|
||||
if model_type == "scripts":
|
||||
file_types = ["shark_*.py"]
|
||||
if model_type == "lora":
|
||||
file_types = file_types + ("*.pt", "*.bin")
|
||||
for extn in file_types:
|
||||
|
||||
@@ -8,8 +8,8 @@ wheel
|
||||
|
||||
torch==2.3.0
|
||||
shark-turbine @ git+https://github.com/iree-org/iree-turbine.git@main
|
||||
turbine-models @ git+https://github.com/nod-ai/SHARK-Turbine.git@ean-unify-sd#subdirectory=models
|
||||
diffusers @ git+https://github.com/nod-ai/diffusers@v0.24.0-release
|
||||
turbine-models @ git+https://github.com/nod-ai/SHARK-Turbine.git@deprecated-constraints#subdirectory=models
|
||||
diffusers @ git+https://github.com/nod-ai/diffusers@0.29.0.dev0-shark
|
||||
brevitas @ git+https://github.com/Xilinx/brevitas.git@6695e8df7f6a2c7715b9ed69c4b78157376bb60b
|
||||
|
||||
# SHARK Runner
|
||||
|
||||
@@ -89,7 +89,7 @@ else {python -m venv .\shark.venv\}
|
||||
python -m pip install --upgrade pip
|
||||
pip install wheel
|
||||
pip install --pre -r requirements.txt
|
||||
pip install https://github.com/nod-ai/SRT/releases/download/candidate-20240602.283/iree_compiler-20240602.283-cp311-cp311-win_amd64.whl https://github.com/nod-ai/SRT/releases/download/candidate-20240602.283/iree_runtime-20240602.283-cp311-cp311-win_amd64.whl
|
||||
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
|
||||
pip install -e .
|
||||
|
||||
Write-Host "Source your venv with ./shark.venv/Scripts/activate"
|
||||
|
||||
Reference in New Issue
Block a user