Predict
HyenaPredictor
Bases: LightningPassthroughPredictionMixin
, HyenaModel
A predictor for the Hyena model. This adds in the predict step and the passthrough method.
Source code in bionemo/evo2/run/predict.py
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__init__(*args, output_log_prob_seqs=False, log_prob_collapse_option='mean', **kwargs)
Initialize the predictor with our needs around computing log probabilities.
Source code in bionemo/evo2/run/predict.py
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predict_step(batch, batch_idx=None)
Alias for forward_step, also log the pad mask since sequences may not all have the same length.
Source code in bionemo/evo2/run/predict.py
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MambaPredictor
Bases: MambaModel
, LightningPassthroughPredictionMixin
Mamba model for prediction with additional metrics.
Source code in bionemo/evo2/run/predict.py
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__init__(config, tokenizer=None, output_log_prob_seqs=False, log_prob_collapse_option='mean')
Initialize the MambaPredictor, which wraps the mamba model for prediction handling model parallelism.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
config
|
Model Config |
required | |
tokenizer
|
tokenizer for the model. Defaults to None. |
None
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output_log_prob_seqs
|
bool
|
If you want to output the log probabilities of the sequences. Defaults to False. |
False
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log_prob_collapse_option
|
Literal['sum', 'mean']
|
collapse the log probabilities of the sequences with this prior to return. Defaults to "mean". |
'mean'
|
Source code in bionemo/evo2/run/predict.py
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forward(input_ids, position_ids, inference_params=None, attention_mask=None)
Forward pass for prediction. Overrides the base forward method to store predictions.
Source code in bionemo/evo2/run/predict.py
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predict_step(batch, batch_idx, dataloader_idx=0)
Prediction step, saving the results.
Source code in bionemo/evo2/run/predict.py
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PredictDataModule
Bases: LightningDataModule
Create a dataloader for prediction.
Source code in bionemo/evo2/run/predict.py
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__init__(dataset, batch_size=1)
Create a dataloader for prediction.
Source code in bionemo/evo2/run/predict.py
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predict_dataloader()
Create a dataloader for prediction.
Source code in bionemo/evo2/run/predict.py
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setup(stage=None)
Set up the dataloader.
Source code in bionemo/evo2/run/predict.py
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hyena_predict_data_step(dataloader_iter)
Data step for the Hyena model prediction. Modified from the original gpt data step to include the seq_idx.
Source code in bionemo/evo2/run/predict.py
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hyena_predict_forward_step(model, batch)
Performs a forward step for the Hyena model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
The Hyena model |
required | |
batch
|
Dictionary containing input batch data with keys: - tokens: Input token IDs - position_ids: Position IDs - labels: Labels for loss computation - loss_mask: Mask for loss computation |
required |
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: Output from the model forward pass |
Source code in bionemo/evo2/run/predict.py
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main()
Entrypoint for Evo2 prediction (single inference step, no new tokens).
Source code in bionemo/evo2/run/predict.py
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parse_args()
Parse arguments for Evo2 inference.
Source code in bionemo/evo2/run/predict.py
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predict(fasta_path, ckpt_dir, output_dir, tensor_parallel_size, pipeline_model_parallel_size, context_parallel_size, model_size='7b', model_type='hyena', ckpt_format='torch_dist', fp8=False, full_fp8=False, work_dir=None, batch_size=1, output_log_prob_seqs=False, log_prob_collapse_option='mean', prepend_bos=False, no_sequence_parallel=False, hybrid_override_pattern=None, num_layers=None, seq_len_interpolation_factor=None)
Inference workflow for Evo2.
Returns:
Type | Description |
---|---|
None |
Source code in bionemo/evo2/run/predict.py
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