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---
dataset_info:
features:
- name: prompt_text
dtype: string
- name: prompt_ids
sequence: int64
- name: decode_ids
sequence: int64
- name: prompt_pattern
sequence:
sequence: int64
- name: decode_pattern
sequence:
sequence: int64
- name: predictor_pattern
sequence:
sequence:
sequence: int64
splits:
- name: train
num_bytes: 297949158
num_examples: 30000
download_size: 30294841
dataset_size: 297949158
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
`decode_pattern.shape`: (num_layers, num_decoding_steps)
`predictor_pattern.shape`: (num_decoding_steps, num_layers, top3_indices)
We need to permute `predictor_pattern` via:
```python
predictor_pattern = predictor_pattern.permute(1,0,2) # (num_layers, num_decoding_steps, top3_indices)
``` |