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"text": [
"number of parameters: 29.94M\n",
"Running on local URL: http://127.0.0.1:7860\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
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"data": {
"text/html": [
""
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"source": [
"import torch\n",
"import gradio as gr\n",
"import random\n",
"from config import device_type, ckpt_path, GPTConfig, GPT, encode, decode, ctx, num_samples, max_new_tokens, temperature, top_k\n",
"\n",
"checkpoint = torch.load(ckpt_path, map_location=device_type)\n",
"gptconf = GPTConfig(**checkpoint['model_args'])\n",
"model = GPT(gptconf)\n",
"state_dict = checkpoint['model']\n",
"unwanted_prefix = '_orig_mod.'\n",
"for k,v in list(state_dict.items()):\n",
" if k.startswith(unwanted_prefix):\n",
" state_dict[k[len(unwanted_prefix):]] = state_dict.pop(k)\n",
"model.load_state_dict(state_dict)\n",
"model.eval()\n",
"model.to(device_type)\n",
"\n",
"button_click = False\n",
"\n",
"def fn_query_on_load():\n",
" return \"in the air and\"\n",
"\n",
"num_samples = 1\n",
"def generate_commentary(start):\n",
" start_ids = encode(start)\n",
" x = (torch.tensor(start_ids, dtype=torch.long, device=device_type)[None, ...])\n",
"\n",
" out_text = ''\n",
" with torch.no_grad():\n",
" with ctx:\n",
" for k in range(num_samples):\n",
" y = model.generate(x, max_new_tokens, temperature=temperature, top_k=top_k)\n",
" out_text += decode(y[0].tolist())\n",
" out_text += '\\n-o-o-o-o-o-o-o-\\n\\n'\n",
"\n",
" return out_text\n",
" \n",
" \n",
"def fn_gen_comm(prompt, st, o1, o2, o3):\n",
" '''global button_click\n",
" if not button_click:\n",
" button_click = True\n",
" elif stat == -1:\n",
" button_click = False\n",
" return {\n",
" output1: output1,\n",
" output2: output2,\n",
" output3: output3,\n",
" stat: stat\n",
" }\n",
" \n",
" \n",
" out = generate_commentary(prompt)\n",
" if stat == -1:\n",
" return {\n",
" output1: out,\n",
" output2: None,\n",
" output3: None,\n",
" stat: 0\n",
" }\n",
" \n",
" elif stat == 0:\n",
" return {\n",
" output1: output1,\n",
" output2: out,\n",
" output3: None,\n",
" stat: 1\n",
" }\n",
" \n",
" elif stat == 2:\n",
" return {\n",
" output1: output1,\n",
" output2: output2,\n",
" output3: out,\n",
" stat: -1\n",
" }'''\n",
" \n",
" global button_click\n",
" if not button_click:\n",
" if st == -1:\n",
" button_click = True\n",
" elif st == -1:\n",
" button_click = False\n",
" return {\n",
" output1: o1,\n",
" output2: o2,\n",
" output3: o3,\n",
" stat: -1\n",
" }\n",
" elif st == 2:\n",
" button_click = False\n",
" return {\n",
" output1: o1,\n",
" output2: o2,\n",
" output3: o3,\n",
" stat: -1\n",
" }\n",
" \n",
" out = generate_commentary(prompt)\n",
" if st == -1:\n",
" return {\n",
" output1: out,\n",
" output2: None,\n",
" output3: None,\n",
" stat: 0\n",
" }\n",
" elif st == 0:\n",
" return {\n",
" output1: o1,\n",
" output2: out,\n",
" output3: None,\n",
" stat: 1\n",
" }\n",
" elif st == 1:\n",
" return {\n",
" output1: o1,\n",
" output2: o2,\n",
" output3: out,\n",
" stat: 2\n",
" }\n",
"\n",
"\n",
"with gr.Blocks() as app:\n",
" with gr.Row():\n",
" gr.Markdown(\n",
" \"\"\"\n",
" # NanoGPT - Cricket Commentary Generative AI\n",
" ### Give a prompt and see how it comes out with cricket commentary :)\n",
" \"\"\")\n",
"\n",
" with gr.Row(visible=True):\n",
" search_text = gr.Textbox(value=fn_query_on_load, placeholder='Enter prompt..', label='Enter Prompt')\n",
"\n",
" with gr.Row():\n",
" submit_btn = gr.Button(\"Submit\", variant='primary')\n",
" clear_btn = gr.ClearButton()\n",
" with gr.Row():\n",
" with gr.Column():\n",
" output1 = gr.Textbox(lines=10, interactive=False, label='Commentary Box')\n",
" output2 = gr.Textbox(lines=10, interactive=False, label='Commentary Box')\n",
" output3 = gr.Textbox(lines=10, interactive=False, label='Commentary Box')\n",
" stat = gr.State(value=-1)\n",
" \n",
"\n",
" def clear_data():\n",
" return {\n",
" output1: None,\n",
" output2: None,\n",
" output3: None,\n",
" search_text: None\n",
" }\n",
"\n",
" clear_btn.click(clear_data, None, [output1, output2, output3, search_text])\n",
"\n",
"\n",
" submit_btn.click(\n",
" fn_gen_comm,\n",
" [search_text, stat, output1, output2, output3],\n",
" [output1, output2, output3, stat]\n",
" )\n",
" \n",
" '''output1.change(\n",
" fn_gen_comm,\n",
" search_text,\n",
" [output1, output2, output3, stat]\n",
" )\n",
" \n",
" output2.change(\n",
" fn_gen_comm,\n",
" search_text,\n",
" [output1, output2, output3, stat]\n",
" )\n",
"\n",
" output3.change(\n",
" fn_gen_comm,\n",
" search_text,\n",
" [output1, output2, output3, stat]\n",
" )'''\n",
"\n",
"'''\n",
"Launch the app\n",
"'''\n",
"app.queue().launch()"
]
},
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