RWKV-Runner/backend-python/routes/state_cache.py

267 lines
7.4 KiB
Python

from typing import Any, Dict, List, Union
from utils.log import quick_log
from fastapi import APIRouter, HTTPException, Request, Response, status
from pydantic import BaseModel
import gc
import copy
import global_var
router = APIRouter()
trie = None
dtrie: Dict = {}
max_trie_len = 300
loop_start_id = 1 # to prevent preloaded prompts from being deleted
loop_del_trie_id = loop_start_id
def init():
global trie
try:
import cyac
# import mmap
# import os
#
# if os.path.exists("state_cache.trie"):
# with open("state_cache.trie", "r") as bf:
# buff_object = mmap.mmap(bf.fileno(), 0, access=mmap.ACCESS_READ)
# trie = cyac.Trie.from_buff(buff_object, copy=False)
# else:
trie = cyac.Trie()
except ModuleNotFoundError:
print("cyac not found")
@router.post("/disable-state-cache", tags=["State Cache"])
def disable_state_cache():
global trie, dtrie
if global_var.get(global_var.Deploy_Mode) is True:
raise HTTPException(status.HTTP_403_FORBIDDEN)
trie = None
dtrie = {}
gc.collect()
print("state cache disabled")
return "success"
@router.post("/enable-state-cache", tags=["State Cache"])
def enable_state_cache():
global trie, dtrie
if global_var.get(global_var.Deploy_Mode) is True:
raise HTTPException(status.HTTP_403_FORBIDDEN)
try:
import cyac
trie = cyac.Trie()
dtrie = {}
gc.collect()
print("state cache enabled")
return "success"
except ModuleNotFoundError:
print("state cache disabled")
raise HTTPException(status.HTTP_400_BAD_REQUEST, "cyac not found")
class AddStateBody(BaseModel):
prompt: str
tokens: List[Union[str, int]]
state: Any
logits: Any
def copy_tensor_to_cpu(tensors):
import torch
import numpy as np
devices: List[torch.device] = []
copied: Union[Any, None] = None
tensors_type = type(tensors)
if tensors_type == list:
if hasattr(tensors[0], "device"): # torch state
devices = [tensor.device for tensor in tensors]
copied = [tensor.cpu() for tensor in tensors]
else: # WebGPU logits
copied = tensors
elif tensors_type == torch.Tensor: # torch logits
devices = [tensors.device]
copied = tensors.cpu()
elif tensors_type == np.ndarray: # rwkv.cpp
copied = tensors
else: # WebGPU state
copied = tensors.back()
return copied, devices
# @router.post("/add-state", tags=["State Cache"])
def add_state(body: AddStateBody):
global trie, dtrie, loop_del_trie_id
# if global_var.get(global_var.Deploy_Mode) is True:
# raise HTTPException(status.HTTP_403_FORBIDDEN)
if trie is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
import torch
import numpy as np
try:
devices: List[torch.device] = []
logits_device: Union[torch.device, None] = None
state: Union[Any, None] = None
logits: Union[Any, None] = None
if body.state is not None:
state, devices = copy_tensor_to_cpu(body.state)
if body.logits is not None:
logits, logits_devices = copy_tensor_to_cpu(body.logits)
if len(logits_devices) > 0:
logits_device = logits_devices[0]
id: int = trie.insert(body.prompt)
dtrie[id] = {
"tokens": body.tokens,
"state": state,
"logits": logits,
"devices": devices,
"logits_device": logits_device,
}
if len(trie) >= max_trie_len:
del_prompt = trie[loop_del_trie_id]
trie.remove(del_prompt)
dtrie[loop_del_trie_id] = None
loop_del_trie_id = loop_del_trie_id + 1
if loop_del_trie_id >= max_trie_len:
loop_del_trie_id = loop_start_id
quick_log(
None,
None,
f"New Trie Id: {id}\nTrie Len: {len(trie)}\nTrie Buff Size: {trie.buff_size()}\nDtrie Buff Size Of Id: {__get_a_dtrie_buff_size(dtrie[id])}",
)
return "success"
except Exception as e:
print(e) # should not happen
raise HTTPException(
status.HTTP_400_BAD_REQUEST, f"insert failed, bad prompt.\n{e}"
)
@router.post("/reset-state", tags=["State Cache"])
def reset_state():
global trie, dtrie
if global_var.get(global_var.Deploy_Mode) is True:
raise HTTPException(status.HTTP_403_FORBIDDEN)
if trie is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
import cyac
trie = cyac.Trie()
dtrie = {}
gc.collect()
return "success"
class LongestPrefixStateBody(BaseModel):
prompt: str
def __get_a_dtrie_buff_size(dtrie_v):
# print(sys.getsizeof(dtrie_v["tokens"][0])) # str
# print(sys.getsizeof(dtrie_v["tokens"][0]) * len(dtrie_v["tokens"]))
# print(dtrie_v["state"][0][0].element_size())
# print(dtrie_v["state"][0].nelement())
# print(len(dtrie_v["state"]))
# print(
# len(dtrie_v["state"])
# * dtrie_v["state"][0].nelement()
# * dtrie_v["state"][0][0].element_size()
# )
# print(dtrie_v["logits"][0].element_size())
# print(dtrie_v["logits"].nelement())
# print(dtrie_v["logits"][0].element_size() * dtrie_v["logits"].nelement())
return 54 * len(dtrie_v["tokens"]) + 491520 + 262144 + 28 # TODO
# @router.post("/longest-prefix-state", tags=["State Cache"])
def longest_prefix_state(body: LongestPrefixStateBody, request: Request):
global trie
# if global_var.get(global_var.Deploy_Mode) is True:
# raise HTTPException(status.HTTP_403_FORBIDDEN)
if trie is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
import torch
import numpy as np
id = -1
try:
for id, len in trie.prefix(body.prompt):
pass
except:
pass
if id != -1:
prompt: str = trie[id]
v = dtrie[id]
tokens: List[Union[str, int]] = copy.deepcopy(v["tokens"])
devices: List[torch.device] = v["devices"]
logits_device: Union[torch.device, None] = v["logits_device"]
state: Union[Any, None] = v["state"]
logits: Union[Any, None] = v["logits"]
if type(state) == list and hasattr(state[0], "device"): # torch
state = [
tensor.to(devices[i])
if devices[i] != torch.device("cpu")
else tensor.clone()
for i, tensor in enumerate(state)
]
logits = (
logits.to(logits_device)
if logits_device != torch.device("cpu")
else logits.clone()
)
else: # rwkv.cpp, WebGPU
logits = np.copy(logits)
quick_log(request, body, "Hit:\n" + prompt)
return {
"prompt": prompt,
"tokens": tokens,
"state": state,
"logits": logits,
}
else:
return {"prompt": "", "tokens": [], "state": None, "logits": None}
# @router.post("/save-state", tags=["State Cache"])
def save_state():
global trie
# if global_var.get(global_var.Deploy_Mode) is True:
# raise HTTPException(status.HTTP_403_FORBIDDEN)
if trie is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
# trie.save("state_cache.trie")
return "not implemented"