Fix _init_max_length in base_model.py

[gucci-j]

What does this PR do?

This PR just fixes an error caused in self._init_max_length(config.max_length). I added try-except to avoid the error.

Error

AttributeError occurred while processing load_model() for bigscience/bloom-7b1 because self._tokenizer was not defined at this stage.

WARNING:lighteval.logging.hierarchical_logger:  Test all gather {
WARNING:lighteval.logging.hierarchical_logger:    Test gather tensor
WARNING:lighteval.logging.hierarchical_logger:    gathered_tensor tensor([0], device='cuda:0'), should be [0]
WARNING:lighteval.logging.hierarchical_logger:  } [0:00:00.000649]
WARNING:lighteval.logging.hierarchical_logger:  Creating model configuration {
WARNING:lighteval.logging.hierarchical_logger:  } [0:00:00.000012]
WARNING:lighteval.logging.hierarchical_logger:  Model loading {
loading configuration file config.json from cache at /mnt/parscratch/users/acp23ay/private/hub/models--bigscience--bloom-7b1/snapshots/6232703e399354503377bf59dfbb8397fd569e4a/config.json
Model config BloomConfig {
  "_name_or_path": "bigscience/bloom-7b1",
  "apply_residual_connection_post_layernorm": false,
  "architectures": [
    "BloomForCausalLM"
  ],
  "attention_dropout": 0.0,
  "attention_softmax_in_fp32": true,
  "bias_dropout_fusion": true,
  "bos_token_id": 1,
  "eos_token_id": 2,
  "hidden_dropout": 0.0,
  "hidden_size": 4096,
  "initializer_range": 0.02,
  "layer_norm_epsilon": 1e-05,
  "masked_softmax_fusion": true,
  "model_type": "bloom",
  "n_head": 32,
  "n_inner": null,
  "n_layer": 30,
  "offset_alibi": 100,
  "pad_token_id": 3,
  "pretraining_tp": 1,
  "skip_bias_add": true,
  "skip_bias_add_qkv": false,
  "slow_but_exact": false,
  "torch_dtype": "float16",
  "transformers_version": "4.39.0.dev0",
  "unk_token_id": 0,
  "use_cache": true,
  "vocab_size": 250880
}

WARNING:lighteval.logging.hierarchical_logger:  } [0:00:00.123938]
WARNING:lighteval.logging.hierarchical_logger:} [0:00:00.435923]
Traceback (most recent call last):
  File "/users/acp23ay/src/lighteval/run_evals_accelerate.py", line 82, in <module>
    main(args)
  File "/users/acp23ay/src/lighteval/src/lighteval/logging/hierarchical_logger.py", line 166, in wrapper
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/main_accelerate.py", line 77, in main
    model, model_info = load_model(config=model_config, env_config=env_config)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/models/model_loader.py", line 83, in load_model
    return load_model_with_accelerate_or_default(config=config, env_config=env_config)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/models/model_loader.py", line 125, in load_model_with_accelerate_or_default
    model = BaseModel(config=config, env_config=env_config)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/models/base_model.py", line 76, in __init__
    self._max_length = self._init_max_length(config.max_length)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/models/base_model.py", line 269, in _init_max_length
    if hasattr(self.tokenizer, "model_max_length"):
               ^^^^^^^^^^^^^^
  File "/users/acp23ay/src/lighteval/src/lighteval/models/base_model.py", line 103, in tokenizer
    return self._tokenizer
           ^^^^^^^^^^^^^^^
AttributeError: 'BaseModel' object has no attribute '_tokenizer'. Did you mean: 'tokenizer'?