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fix templating webui bug

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51616 2025-05-14 07:59:32 +00:00
parent 52e36fccef
commit e6294f08da
2 changed files with 19 additions and 16 deletions
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7
README.md
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@ -50,6 +50,13 @@ run python intx_sft.py configs/...yaml ... --from_pretrained_checkpoint=train_ou
### Evaluation
LongBench
```bash
# generative
run python src/ctx_to_lora/eval.py --checkpoint_path train_outputs/runs/May08_13-56-31_slurm0-a3nodeset-5_59383_906acb28/checkpoint-105000/pytorch_model.bin
# benchmark
cd LongBench/LongBench
run python pred_ctx_to_lora.py --checkpoint_path ../../train_outputs/runs/Mar16_12-38-01_slurm0-a3nodeset-12_54818_32426662/checkpoint-136782/pytorch_model.bin
run python eval_ctx_to_lora.py --model_name Mar16_12-38-01_slurm0-a3nodeset-12_54818_32426662/checkpoint-136782 --checkpoint_path ../../train_outputs/runs/Mar16_12-38-01_slurm0-a3nodeset-12_54818_32426662/checkpoint-136782/pytorch_model.bin
```

28
webui/app.py
View file

@ -8,6 +8,7 @@ import yaml
from flask import Flask, abort, jsonify, render_template, request
from transformers import pipeline, AutoTokenizer
from ctx_to_lora.data_utils import tokenize_ctx_text
from ctx_to_lora.model_loading import get_tokenizer
app = Flask(__name__)
@ -354,7 +355,7 @@ def load_checkpoint():
train=False,
use_flash_attn=True,
)
modulated_model = modulated_model.to(device)
modulated_model = modulated_model.to(device).to(torch.bfloat16)
modulated_model.eval()
result = {
@ -393,23 +394,18 @@ def process_multiple_contexts(contexts, ctx_tokenizer):
print(f"Processing {len(contexts)} non-empty contexts")
# Tokenize each context
all_ctx_ids = []
all_ctx_attn_mask = []
for context in contexts:
# Tokenize the single context
inputs = ctx_tokenizer(context, return_tensors="pt")
all_ctx_ids.append(inputs["input_ids"][0])
all_ctx_attn_mask.append(inputs["attention_mask"][0])
# Pad to the same length
tokenized_contexts = tokenize_ctx_text({"context": contexts}, ctx_tokenizer)
ctx_ids = tokenized_contexts["ctx_ids"]
ctx_attn_mask = tokenized_contexts["ctx_attn_mask"]
ctx_ids = torch.nn.utils.rnn.pad_sequence(
all_ctx_ids, batch_first=True, padding_value=ctx_tokenizer.pad_token_id
torch.tensor(ctx_ids, dtype=torch.long, device=device),
batch_first=True,
padding_value=0,
)
ctx_attn_mask = torch.nn.utils.rnn.pad_sequence(
all_ctx_attn_mask, batch_first=True, padding_value=0
torch.tensor(ctx_attn_mask, dtype=torch.long, device=device),
batch_first=True,
padding_value=0,
)
return {"ctx_ids": ctx_ids, "ctx_attn_mask": ctx_attn_mask}
@ -483,7 +479,7 @@ def chat():
# Tokenize the chat history
model_inputs = base_tokenizer.apply_chat_template(
chat_history, return_tensors="pt"
chat_history, return_tensors="pt", add_generation_prompt=True
).to(device)
# Generate response with context-modulated model