🚨Fix floating-point precision in JanusImageProcessor resize
Author: raimbekovm
Pull request: yes

Fixes #43186

## What does this PR do?

Fixes floating-point precision issue in `JanusImageProcessor.resize()` where `int()` truncation caused incorrect output dimensions.

**Problem:**
```python
height = 2522, size = 384
delta = 384 / 2522 = 0.15225218081681999...
height * delta = 383.9999999999...
int(height * delta) = 383  # Wrong!
round(height * delta) = 384  # Correct!
```

**Solution:**
Replace `int()` with `round()` for proper rounding of scaled dimensions.

## Why edit `modular_janus.py`?

The file `image_processing_deepseek_vl.py` (mentioned in the issue) is auto-generated from `modular_janus.py`. The header states:
```
🚨 This file was automatically generated from src/transformers/models/janus/modular_janus.py.
   Do NOT edit this file manually...
```

DeepseekVL imports `JanusImageProcessor`, so fixing the source fixes all dependent models:
- Janus
- DeepseekVL
- DeepseekVL Hybrid

Comments:
Bug seems legit but I'd like someone with more image processor experience to check that we're still matching the behaviour that these models expect, because sometimes models are trained with slightly buggy preprocessing code and it becomes important to match that behaviour later. cc @molbap @yonigozlan @zucchini-nlp

Done. Ran the modular converter and pushed the regenerated file.

Note: The same int() truncation issue exists in two other places:
- `image_processing_deepseek_vl.py` (generated from modular_deepseek_vl.py which inherits from JanusImageProcessor)
- `image_processing_janus_fast.py` (not a modular file)

Should I include these in this PR or handle them separately?

> Should I include these in this PR or handle them separately?

Running `make fix-repo` should have auto-fixed those, no? I see the CI is still complaining about these models

Fixed. Added the missing changes for deepseek_vl and janus_fast.

@bot /repo

Repo. Consistency fix runs successfully without any file modified.

run-slow: deepseek_vl, janus, deepseek_vl_hybrid

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_43187). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.


run-slow: deepseek_vl, janus, deepseek_vl_hybrid



slow tests cannot be triggered 😢 

run-slow: deepseek_vl, deepseek_vl_hybrid, janus

This comment contains `run-slow`, running the specified jobs: 

models: ["models/deepseek_vl", "models/deepseek_vl_hybrid", "models/janus"]
quantizations: []

## CI Results
[Workflow Run ⚙️](https://github.com/huggingface/transformers/actions/runs/21471503710)

### Model CI Report

#### ❌ Failed tests

- [deepseek_vl_hybrid](https://github.com/huggingface/transformers/actions/runs/21471503710/job/61845515283):
    tests/models/deepseek_vl_hybrid/test_modeling_deepseek_vl_hybrid.py::DeepseekVLHybridIntegrationTest::test_model_text_generation

- [janus](https://github.com/huggingface/transformers/actions/runs/21471503710/job/61845515268):
    tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation



I got similar results locally with slow tests now failing due to this changes. However it seems to me that the processing now works as it's supposed to , so ok to change the expected values (and add a 🚨 as it breaks BC a bit)? @molbap @zucchini-nlp  

Yeah, sounds good to me. Let's just update test values with the new ones and merge as breaking

run-slow: deepseek_vl, deepseek_vl_hybrid, janus

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: deepseek_vl, deepseek_vl_hybrid, janus