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Running
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Zero
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import random
from typing import Tuple
import torch
from wenet.utils.common import pad_list
from gxl_ai_utils.utils import utils_file
def add_sos_eos4speech_llm(ys_pad: torch.Tensor, sos: int, eos: int,
ignore_id: int) -> Tuple[torch.Tensor, torch.Tensor]:
"""Add <sos> and <eos> labels.
为out后接一个eos. in基本保持不变
Args:
ys_pad (torch.Tensor): batch of padded target sequences (B, Lmax)
sos (int): index of <sos>
eos (int): index of <eeos>
ignore_id (int): index of padding
Returns:
ys_in (torch.Tensor) : (B, Lmax)
ys_out (torch.Tensor) : (B, Lmax + 1)
Examples:
>>> sos_id = 10
>>> eos_id = 11
>>> ignore_id = -1
>>> ys_pad
tensor([[ 1, 2, 3, 4, 5],
[ 4, 5, 6, -1, -1],
[ 7, 8, 9, -1, -1]], dtype=torch.int32)
>>> ys_in,ys_out=add_sos_eos(ys_pad, sos_id , eos_id, ignore_id)
>>> ys_in
tensor([[ 1, 2, 3, 4, 5],
[ 4, 5, 6, 11, 11],
[ 7, 8, 9, 11, 11]])
>>> ys_out
tensor([[ 1, 2, 3, 4, 5, 11],
[ 4, 5, 6, 11, -1, -1],
[ 7, 8, 9, 11, -1, -1]])
"""
_sos = torch.tensor([sos],
dtype=torch.long,
requires_grad=False,
device=ys_pad.device)
_eos = torch.tensor([eos],
dtype=torch.long,
requires_grad=False,
device=ys_pad.device)
ys = [y[y != ignore_id] for y in ys_pad] # parse padded ys
# ys_in = [torch.cat([_sos, y], dim=0) for y in ys]
ys_in = [y for y in ys]
ys_out = [torch.cat([y, _eos], dim=0) for y in ys]
return pad_list(ys_in, eos), pad_list(ys_out, ignore_id)
global_prompt_dict = None
def get_prompt_by_task(task_name):
"""
根据task给定指定的prompt, 并实现prompt的多样随意性
Args:
task_name:
Returns:
"""
global global_prompt_dict
if global_prompt_dict is None:
global_prompt_dict = utils_file.load_dict_from_yaml('conf/prompt.yaml')
random_index = random.randint(0, len(global_prompt_dict[task_name])-1)
return global_prompt_dict[task_name][random_index]
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