[Bug-Fix] fix attention head intervention for multiple models

Bakser commented 1 month ago

Description

Fix the bug reported in #158 by modifying the modeling scripts of gemma, gpt_neo, gpt_neox, llama, llava, mistral, mainly involving three points:

add the missed split_head_and_permute operation to split the hidden representations by attention heads
fix the support of models with LM head (_lm_type_to_module_mapping), which missed elements in v[1:]
add the support of grouped query attention modules used by Llama-like models

Testing Done

All tests passed.

'pyvene' is not installed.
PASS: pyvene is not installed. Testing local dev code.
=== Test Suite: VanillaInterventionWithTransformerTestCase ===
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./shared/nas2/wangxz/pyvene/pyvene/models/intervenable_base.py:55: DeprecationWarning: The 'warn' function is deprecated, use 'warning' instead
  logging.warn(
WARNING:root:Detected use_fast=True means the intervention location will be static within a batch.

In case multiple location tags are passed only the first one will be considered
.WARNING:root:Detected use_fast=True means the intervention location will be static within a batch.

In case multiple location tags are passed only the first one will be considered
.WARNING:root:Detected use_fast=True means the intervention location will be static within a batch.

In case multiple location tags are passed only the first one will be considered
./shared/nas2/wangxz/miniconda3/envs/llm/lib/python3.11/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
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model.safetensors: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 548M/548M [00:02<00:00, 241MB/s]
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IntervenableConfig
{
    "model_type": "None",
    "representations": [
        {
            "layer": 0,
            "component": "mlp_output",
            "unit": "pos",
            "max_number_of_units": 1,
            "low_rank_dimension": null,
            "intervention_type": null,
            "intervention": null,
            "subspace_partition": null,
            "group_key": null,
            "intervention_link_key": null,
            "moe_key": null,
            "source_representation": "PLACEHOLDER",
            "hidden_source_representation": null
        },
        {
            "layer": 1,
            "component": "mlp_output",
            "unit": "pos",
            "max_number_of_units": 1,
            "low_rank_dimension": null,
            "intervention_type": null,
            "intervention": null,
            "subspace_partition": null,
            "group_key": null,
            "intervention_link_key": null,
            "moe_key": null,
            "source_representation": "PLACEHOLDER",
            "hidden_source_representation": null
        },
        {
            "layer": 2,
            "component": "mlp_output",
            "unit": "pos",
            "max_number_of_units": 1,
            "low_rank_dimension": null,
            "intervention_type": null,
            "intervention": null,
            "subspace_partition": null,
            "group_key": null,
            "intervention_link_key": null,
            "moe_key": null,
            "source_representation": "PLACEHOLDER",
            "hidden_source_representation": null
        },
        {
            "layer": 3,
            "component": "mlp_output",
            "unit": "pos",
            "max_number_of_units": 1,
            "low_rank_dimension": null,
            "intervention_type": null,
            "intervention": null,
            "subspace_partition": null,
            "group_key": null,
            "intervention_link_key": null,
            "moe_key": null,
            "source_representation": "PLACEHOLDER",
            "hidden_source_representation": null
        }
    ],
    "intervention_types": "<class 'pyvene.models.interventions.VanillaIntervention'>",
    "mode": "parallel",
    "sorted_keys": "None",
    "intervention_dimensions": "None"
}
.loaded model
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Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.
Once upon a time there was a little girl named Lucy. She was three years old and loved to explore. One day, Lucy was walking in the park when
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.sentencepiece is not installed. skipping
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Directory './tmp/' already exists.
/shared/nas2/wangxz/pyvene/pyvene/models/intervenable_base.py:165: DeprecationWarning: The 'warn' function is deprecated, use 'warning' instead
  logging.warn(
WARNING:root:The key is provided in the config. Assuming this is loaded from a pretrained module.
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Directory './test_output_dir_prefix-542c1b' already exists.
WARNING:root:The key is provided in the config. Assuming this is loaded from a pretrained module.
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.Removing testing dir ./test_output_dir_prefix-542c1b
=== Test Suite: InterventionWithGPT2TestCase ===
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testing stream: head_attention_value_output with multiple heads positions
testing stream: head_query_output with multiple heads positions
testing stream: head_key_output with multiple heads positions
testing stream: head_value_output with multiple heads positions
.=== Test Suite: InterventionWithMLPTestCase ===
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......=== Test Suite: CausalModelTestCase ===
......=== Test Suite: IntervenableConfigUnitTestCase ===
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.=== Test Suite: InterventionUtilsTestCase ===
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.....Directory './test_output_dir_prefix-dbeab8' created successfully.
WARNING:root:The key is provided in the config. Assuming this is loaded from a pretrained module.
Directory './test_output_dir_prefix-5f226d' created successfully.
WARNING:root:The key is provided in the config. Assuming this is loaded from a pretrained module.
Directory './test_output_dir_prefix-da0f35' created successfully.
WARNING:root:The key is provided in the config. Assuming this is loaded from a pretrained module.
.Directory './test_output_dir_prefix-3a4b1e' created successfully.
.Directory './test_output_dir_prefix-23496a' created successfully.
.tensor([[1.9266e-05, 1.0024e+00, 1.4001e+01, 1.5001e+01, 1.6000e+01, 1.7000e+01],
        [6.0000e+00, 7.0024e+00, 2.0001e+01, 2.1001e+01, 2.2000e+01, 2.3000e+01]],
       grad_fn=<AddBackward0>)
./shared/nas2/wangxz/pyvene/pyvene/models/interventions.py:422: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  mask_sigmoid = torch.sigmoid(self.mask / torch.tensor(self.temperature))
.........Removing testing dir ./test_output_dir_prefix-dbeab8
Removing testing dir ./test_output_dir_prefix-5f226d
Removing testing dir ./test_output_dir_prefix-da0f35
Removing testing dir ./test_output_dir_prefix-3a4b1e
Removing testing dir ./test_output_dir_prefix-23496a
.............
----------------------------------------------------------------------
Ran 71 tests in 33.548s

OK

Checklist:

[x] My PR title strictly follows the format: [Your Priority] Your Title
[x] I have attached the testing log above
[x] I provide enough comments to my code
[ ] I have changed documentations
[ ] I have added tests for my changes

frankaging commented 1 month ago

@Bakser would you provide an unit test for one of the model type you changed? e.g., llama

thanks. i can add in a new unit test based on your script.

Bakser commented 1 month ago

Sure, I can help with that.

I'm not quite familiar with the unit tests of this repo. Do you mean something like the tests/integration_tests/InterventionWithGPT2TestCase.py but for llama?

frankaging commented 1 month ago

Sure, I can help with that.

I'm not quite familiar with the unit tests of this repo. Do you mean something like the tests/integration_tests/InterventionWithGPT2TestCase.py but for llama?

yes! that would be great! and you can initialize a much smaller llama for test! e.g., just a single layer llama for instance, since we want the unit test to be quick. thanks

frankaging commented 1 month ago

@Bakser hey! any updates on the progress? thanks!

Bakser commented 1 month ago

I didn't work on it on the weekend but I think I can finish it today. sorry for worrying

Bakser commented 1 month ago

I find that I underestimated the workload. I will try to finish it in a couple of days.

Bakser commented 3 weeks ago

@frankaging I've finished the test for Llama. Sorry for the delay since I was on travel.

Basically, I just copied the tests in InterventionWithGPT2TestCase.py into InterventionWithLlamaTestCase.py and added the implementations for Llama forward process into tests/utils.py as like for GPT2 (but I do think if we want to implement tests for more models we need to split this file).

It can be run with python -m unittest tests.integration_tests.InterventionWithLlamaTestCase and the output should be like:

'pyvene' is not installed.
PASS: pyvene is not installed. Testing local dev code.
=== Test Suite: InterventionWithLlamaTestCase ===
You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
loaded model
testing stream: head_attention_value_output with multiple heads positions
testing stream: head_query_output with multiple heads positions
testing stream: head_key_output with multiple heads positions
testing stream: head_value_output with multiple heads positions
.
----------------------------------------------------------------------
Ran 1 test in 37.738s

OK

frankaging commented 3 weeks ago

@frankaging I've finished the test for Llama. Sorry for the delay since I was on travel.

Basically, I just copied the tests in InterventionWithGPT2TestCase.py into InterventionWithLlamaTestCase.py and added the implementations for Llama forward process into tests/utils.py as like for GPT2 (but I do think if we want to implement tests for more models we need to split this file).

It can be run with python -m unittest tests.integration_tests.InterventionWithLlamaTestCase and the output should be like:
'pyvene' is not installed.
PASS: pyvene is not installed. Testing local dev code.
=== Test Suite: InterventionWithLlamaTestCase ===
You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
loaded model
testing stream: head_attention_value_output with multiple heads positions
testing stream: head_query_output with multiple heads positions
testing stream: head_key_output with multiple heads positions
testing stream: head_value_output with multiple heads positions
.
----------------------------------------------------------------------
Ran 1 test in 37.738s

OK

Thanks! @Bakser

stanfordnlp / pyvene