Fix editable installation

[tscholak]

✨ Description

The editable installation in the new docker image didn't work. I added a fix for this.

Before:

root@eaa709a280b7:~# fast-llm train gpt --help
2024-11-13 08:05:35,320 Traceback (most recent call last):
  File "/app/fast_llm/tools/cli.py", line 22, in fast_llm
    from fast_llm.tools.train import CliTrainingConfig as Runnable
  File "/app/fast_llm/tools/train.py", line 4, in <module>
    from fast_llm.models.auto import trainer_registry
  File "/app/fast_llm/models/auto.py", line 1, in <module>
    from fast_llm.models.custom.config import CustomModelConfig, CustomTrainerConfig
  File "/app/fast_llm/models/custom/config.py", line 5, in <module>
    from fast_llm.models.gpt.config import (
  File "/app/fast_llm/models/gpt/config.py", line 6, in <module>
    from fast_llm.engine.multi_stage.config import FastLLMModelConfig, PretrainedFastLLMModelConfig
  File "/app/fast_llm/engine/multi_stage/config.py", line 7, in <module>
    from fast_llm import __version__
ImportError: cannot import name '__version__' from 'fast_llm' (unknown location)

After:

root@24efd592c0da:~# fast-llm train gpt --help
usage: fast-llm [-h] [-v] [-c CONFIG] [--verbose VERBOSE] [--config_auth_token_file CONFIG_AUTH_TOKEN_FILE] [--hydra] [--hydra-path HYDRA_PATH] [--hydra-config HYDRA_CONFIG] {gpt,gpt_custom}

positional arguments:
  {gpt,gpt_custom}      The Fast-LLM model type to use. Must be defined in the trainer registry in `fast_llm.models.auto`.

options:
  -h, --help            show this help message and exit
  -v, --validate        Validate the config without running the command.
  -c CONFIG, --config CONFIG
                        The path or url to the base configuration yaml file.
  --verbose VERBOSE     Verbose level for logging the config.
  --config_auth_token_file CONFIG_AUTH_TOKEN_FILE
                        Path to a file containing a (Github) authentication token.
  --hydra               Enable the hydra syntax for configuration updates. Note: this will only enable the update syntax for the command line arguments. See the other Hydra options for enabling more optional
                        features.
  --hydra-path HYDRA_PATH
                        The hydra configuration path in which to loop for updates relative to the current working directory. Setting this will implicitly enable --hydra.
  --hydra-config HYDRA_CONFIG
                        The name of the hydra base configuration as would be provided in a typical Hydra application. Mutually exclusive with `--config`, which it replaces. Requires --hydra-path to be set.

🔍 Type of change

Select all that apply:

• [x] 🐛 Bug fix (non-breaking change that addresses a specific issue)
• [ ] 🚀 New feature (non-breaking change that adds functionality)
• [ ] ⚠️ Breaking change (a change that could affect existing functionality)
• [ ] 📈 Performance improvement/optimization (improves speed, memory usage, or efficiency)
• [ ] 🛠️ Code refactor (non-functional changes that improve code readability, structure, etc.)
• [ ] 📦 Dependency bump (updates dependencies, including Dockerfile or package changes)
• [ ] 📝 Documentation change (updates documentation, including new content or typo fixes)
• [ ] 🔧 Infrastructure/Build change (affects build process, CI/CD, or dependencies)

📝 Changes

1. Add blank __init__.py in /app/fast_llm before running pip install.

✅ Checklist

Make sure the following tasks are completed before submitting the PR:

General:

• [x] 📜 I have read and followed the contributing guidelines.
• [x] 🎉 The functionality is complete, and I have tested the changes.
• [ ] 📝 I have updated the documentation if needed.
• [x] ⚠️ The change does not introduce any new issues (e.g., runtime warnings, type checker errors, linting problems, unhandled edge cases).
• [ ] 🧩 I have commented my code, especially in hard-to-understand areas.

Dependencies and Configuration:

• [x] 🐋 I have updated the Docker configuration or dependencies, if applicable.
• [ ] 🔄 I have ensured compatibility with the existing setup after dependency changes.

Testing:

• [ ] 🧪 I have added or updated tests to cover my changes.
• [ ] ✔️ New and existing tests pass locally with my changes.
• [ ] 🚦 I have tested these changes on GPUs and verified training stability.
• [ ] 🏋️ I have tested the changes on realistic training workloads, if applicable.

Performance Impact:

• [ ] 📊 I have run benchmarks where applicable to evaluate the performance impact.
• [ ] ✅ The benchmarks show no performance regression.
• [ ] 🚀 The benchmarks indicate a potential performance improvement.
• [ ] ⚠️ The benchmarks indicate a potential performance degradation.
• [ ] 📈 I have provided benchmark results and detailed any performance impact below, if applicable.

📊 Performance Impact Details

N/A

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📝 Additional Notes

N/A