[BUG: RuntimeError: Boolean value of Tensor with more than one value is ambiguous]

[siwer]

Python -VV

File "/opt/anaconda/envs/transformers/lib/python3.11/site-packages/mistral_inference/transformer.py", line 162, in forward_partial
    if self.vision_encoder is not None and images:
       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Boolean value of Tensor with more than one value is ambiguous

Pip Freeze

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Reproduction Steps

Running forward_partial() with Pixtral led to the above mentioned issue. See the code below for my script

import torch
from pathlib import Path
from mistral_inference.transformer import Transformer
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
from mistral_common.protocol.instruct.messages import UserMessage, TextChunk, ImageURLChunk
from mistral_common.protocol.instruct.request import ChatCompletionRequest

mistral_models_path = Path.home().joinpath('mistral_models', 'Pixtral')
tokenizer = MistralTokenizer.from_file(f"{mistral_models_path}/tekken.json")
model = Transformer.from_folder(mistral_models_path,device="cuda:0")

# Run the model 
url = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
prompt = "Describe the image."

completion_request = ChatCompletionRequest(messages=[UserMessage(content=[ImageURLChunk(image_url=url), TextChunk(text=prompt)])])

encoded = tokenizer.encode_chat_completion(completion_request)

images = encoded.images
tokens = encoded.tokens

tokens = torch.tensor(tokens).to(model.device)
images = torch.cuda.BFloat16Tensor(images).to(model.device)

with torch.no_grad():
    res = model.forward_partial(input_ids=tokens,seqlens=[len(tokens)],images=images)

Expected Behavior

Expected model.forward_partial() to output the vector representations of the input tokens

Additional Context

No response

Suggested Solutions

Change line 162 in mistral-inference/blob/main/src/mistral_inference/transformer.py

current:
if self.vision_encoder is not None and images:

proposed solution:
if self.vision_encoder is not None and images is not None:

This led to the code to functioning properly