mirror of
https://github.com/nod-ai/AMD-SHARK-Studio.git
synced 2026-04-25 03:00:12 -04:00
[Shard] Add sharding generation in shark studio
Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
This commit is contained in:
@@ -154,6 +154,7 @@ if __name__ == "__main__":
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upscaler_sendto_outpaint,
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lora_train_web,
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model_web,
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model_config_web,
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hf_models,
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modelmanager_sendto_txt2img,
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modelmanager_sendto_img2img,
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@@ -221,6 +222,16 @@ if __name__ == "__main__":
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outpaint_web.render()
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with gr.TabItem(label="Upscaler", id=4):
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upscaler_web.render()
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with gr.TabItem(label="Model Manager", id=6):
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model_web.render()
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with gr.TabItem(label="Chat Bot(Experimental)", id=7):
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stablelm_chat.render()
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with gr.TabItem(label="Generate Sharding Config", id=8):
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model_config_web.render()
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with gr.TabItem(label="LoRA Training(Experimental)", id=9):
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lora_train_web.render()
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with gr.TabItem(label="MultiModal (Experimental)", id=10):
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minigpt4_web.render()
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if args.output_gallery:
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with gr.TabItem(label="Output Gallery", id=5) as og_tab:
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outputgallery_web.render()
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@@ -236,15 +247,7 @@ if __name__ == "__main__":
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upscaler_status,
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]
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)
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with gr.TabItem(label="Model Manager", id=6):
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model_web.render()
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with gr.TabItem(label="LoRA Training (Experimental)", id=8):
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lora_train_web.render()
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with gr.TabItem(label="Chat Bot (Experimental)", id=7):
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stablelm_chat.render()
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with gr.TabItem(label="MultiModal (Experimental)", id=9):
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minigpt4_web.render()
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with gr.TabItem(label="DocuChat(Experimental)", id=10):
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with gr.TabItem(label="DocuChat(Experimental)", id=11):
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h2ogpt_web.render()
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# send to buttons
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@@ -78,6 +78,7 @@ from apps.stable_diffusion.web.ui.stablelm_ui import (
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stablelm_chat,
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llm_chat_api,
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)
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from apps.stable_diffusion.web.ui.generate_config import model_config_web
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from apps.stable_diffusion.web.ui.h2ogpt import h2ogpt_web
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from apps.stable_diffusion.web.ui.minigpt4_ui import minigpt4_web
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from apps.stable_diffusion.web.ui.outputgallery_ui import (
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41
apps/stable_diffusion/web/ui/generate_config.py
Normal file
41
apps/stable_diffusion/web/ui/generate_config.py
Normal file
@@ -0,0 +1,41 @@
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import gradio as gr
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import torch
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from transformers import AutoTokenizer
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from apps.language_models.src.model_wrappers.vicuna_model import CombinedModel
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from shark.shark_generate_model_config import GenerateConfigFile
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def get_model_config():
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hf_model_path = "TheBloke/vicuna-7B-1.1-HF"
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tokenizer = AutoTokenizer.from_pretrained(hf_model_path, use_fast=False)
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compilation_prompt = "".join(["0" for _ in range(17)])
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compilation_input_ids = tokenizer(
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compilation_prompt,
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return_tensors="pt",
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).input_ids
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compilation_input_ids = torch.tensor(compilation_input_ids).reshape(
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[1, 19]
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)
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firstVicunaCompileInput = (compilation_input_ids,)
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model = CombinedModel()
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c = GenerateConfigFile(model, 1, ["gpu_id"], firstVicunaCompileInput)
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return c.split_into_layers()
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with gr.Blocks() as model_config_web:
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with gr.Row():
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hf_models = gr.Dropdown(
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label="Model List",
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choices=["Vicuna"],
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value="Vicuna",
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visible=True,
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)
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get_model_config_btn = gr.Button(value="Get Model Config")
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json_view = gr.JSON()
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get_model_config_btn.click(
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fn=get_model_config,
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inputs=[],
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outputs=[json_view],
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)
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