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https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-22 08:07:56 +01:00
Move RWKV loader into a separate file
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parent
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commit
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26
modules/RWKV.py
Normal file
26
modules/RWKV.py
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@ -0,0 +1,26 @@
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import os, time, types, torch
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from pathlib import Path
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import numpy as np
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np.set_printoptions(precision=4, suppress=True, linewidth=200)
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os.environ['RWKV_JIT_ON'] = '1'
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os.environ["RWKV_CUDA_ON"] = '0' # '1' : use CUDA kernel for seq mode (much faster)
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import repositories.ChatRWKV.v2.rwkv as rwkv
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from rwkv.model import RWKV
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from rwkv.utils import PIPELINE, PIPELINE_ARGS
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def load_RWKV_model(path):
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os.system("ls")
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model = RWKV(model=path.as_posix(), strategy='cuda fp16')
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out, state = model.forward([187, 510, 1563, 310, 247], None) # use 20B_tokenizer.json
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print(out.detach().cpu().numpy()) # get logits
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out, state = model.forward([187, 510], None)
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out, state = model.forward([1563], state) # RNN has state (use deepcopy if you want to clone it)
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out, state = model.forward([310, 247], state)
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print(out.detach().cpu().numpy()) # same result as above
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pipeline = PIPELINE(model, Path("repositories/ChatRWKV/20B_tokenizer.json").as_posix())
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return pipeline
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@ -79,27 +79,9 @@ def load_model(model_name):
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# RMKV model (not on HuggingFace)
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elif shared.is_RWKV:
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import types
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np.set_printoptions(precision=4, suppress=True, linewidth=200)
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from modules.RWKV import load_RWKV_model
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os.environ['RWKV_JIT_ON'] = '1'
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os.environ["RWKV_CUDA_ON"] = '0' # '1' : use CUDA kernel for seq mode (much faster)
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from rwkv.model import RWKV
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from rwkv.utils import PIPELINE, PIPELINE_ARGS
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model = RWKV(model='models/RWKV-4-Pile-169M-20220807-8023.pth', strategy='cuda fp16')
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out, state = model.forward([187, 510, 1563, 310, 247], None) # use 20B_tokenizer.json
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print(out.detach().cpu().numpy()) # get logits
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out, state = model.forward([187, 510], None)
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out, state = model.forward([1563], state) # RNN has state (use deepcopy if you want to clone it)
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out, state = model.forward([310, 247], state)
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print(out.detach().cpu().numpy()) # same result as above
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pipeline = PIPELINE(model, "20B_tokenizer.json")
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return pipeline, None
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return load_RWKV_model(Path('models/RWKV-4-Pile-169M-20220807-8023.pth')), None
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# Custom
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else:
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@ -82,15 +82,12 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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torch.cuda.empty_cache()
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if shared.is_RWKV:
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def my_print(s):
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print(s, end='', flush=True)
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args = PIPELINE_ARGS(temperature = temperature, top_p = top_p,
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alpha_frequency = 0.25, # Frequency Penalty (as in GPT-3)
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alpha_presence = 0.25, # Presence Penalty (as in GPT-3)
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token_ban = [0], # ban the generation of some tokens
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token_stop = []) # stop generation whenever you see any token here
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reply = question + shared.model.generate(question, token_count=max_new_tokens, args=args, callback=None)
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print(formatted_outputs(reply, None))
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yield formatted_outputs(reply, None)
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return formatted_outputs(reply, None)
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