DPOTrainer: AttributeError: 'list' object has no attribute 'numel'

[tahirahmad2030]

Transformers: 4.41.2
trl: 0.9.4
torch: Version: 2.3.0+cu121

I am training a simple translation model using DPO Trainer and the code is below:

from datasets import Dataset
from transformers import Trainer, TrainingArguments, AutoTokenizer, AutoModelForSeq2SeqLM
from torch.nn.functional import cross_entropy
import torch

# Load pre-trained T5 tokenizer and model
model_name = "t5-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
tokenizer.pad_token = tokenizer.eos_token
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

from trl import DPOConfig, DPOTrainer
# Example tokenized dataset (replace with your actual dataset)
tokenized_dataset = Dataset.from_dict({
    'prompt': ["Translate to French: The house is beautiful.", "Translate to French: The cat sat on the mat."],
    'chosen': ["La maison est belle.", "Le chat était sur le tapis."],
    'rejected': ["La maison est laide.", "Le chat a mangé le tapis."],
})

# Preprocess function
def preprocess_function(examples):
    inputs = examples['prompt']
    chosen_targets = examples['chosen']
    rejected_targets = examples['rejected']

    model_inputs = tokenizer(inputs, max_length=512, truncation=True, padding="max_length")
    model_inputs["labels"] = tokenizer(chosen_targets, max_length=512, truncation=True, padding="max_length").input_ids
    model_inputs["chosen_labels"] = tokenizer(chosen_targets, max_length=512, truncation=True, padding="max_length").input_ids
    model_inputs["rejected_labels"] = tokenizer(rejected_targets, max_length=512, truncation=True, padding="max_length").input_ids

    return model_inputs

# Tokenize the dataset
tokenized_dataset = tokenized_dataset.map(preprocess_function, batched=False)

# Training arguments
training_args = DPOConfig(
    output_dir="./results",
    evaluation_strategy="epoch",
    learning_rate=2e-5,
    per_device_train_batch_size=4,
    num_train_epochs=3,
    logging_dir="./logs",
)

# Initialize Trainer
trainer = DPOTrainer(
    model=model,
    args=training_args,
    train_dataset=tokenized_dataset,
    tokenizer=tokenizer,
)

# Train the model
trainer.train()

The error:

AttributeError                            Traceback (most recent call last)
<ipython-input-24-a566970b894e> in <cell line: 64>()
     62 
     63 # Train the model
---> 64 trainer.train()

4 frames
/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py in estimate_tokens(self, input_dict)
   1186             self.warnings_issued = {}
   1187         if self.main_input_name in input_dict:
-> 1188             return input_dict[self.main_input_name].numel()
   1189         elif "estimate_tokens" not in self.warnings_issued:
   1190             logger.warning(

AttributeError: 'list' object has no attribute 'numel'

I tried different envs like sagemaker and google colab but the error persists.

[b11z]

I don't know the fix, but I have worked around by doing:

model.floating_point_ops = lambda s: 0

More detail: I was passing data to DPO as plain Python objects, not tensors, since that's what DPO expects. But the floating_point_ops method of some models expects tensors. Since this method was only used for monitoring, I just replaced it with a noop.

[tahirahmad2030]

Thanks for the work around @b11z .

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