### Install NeuralPlexer via pip

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Standard installation command for the library.

```bash
pip install neural-plexer-pytorch
```

--------------------------------

### Install NeuralPlexer from source

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Commands to clone the repository and install in editable mode.

```bash
git clone https://github.com/lucidrains/neural-plexer-pytorch
cd neural-plexer-pytorch
pip install -e .
```

--------------------------------

### View project directory structure

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Overview of the repository file layout.

```text
neural-plexer-pytorch/
├── neural_plexer_pytorch/
│   ├── __init__.py
│   └── neural_plexer_pytorch.py    # Main implementation (in development)
├── setup.py
├── README.md
└── LICENSE
```

--------------------------------

### Initialize and use NeuralPlexer

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Expected usage pattern for model initialization and performing a forward pass.

```python
# Once implemented, the expected usage pattern will be:
from neural_plexer_pytorch import NeuralPlexer

# Initialize model
model = NeuralPlexer(
    dim=256,
    depth=12,
    heads=8,
    # Additional configuration parameters
)

# Forward pass with protein and ligand data
output = model(
    protein_sequence,
    ligand_atoms,
    # Additional inputs
)
```

--------------------------------

### Import required dependencies

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Essential imports for the library, requiring torch 2.0+ and einops 0.7.0+.

```python
# Required dependencies (automatically installed)
# torch>=2.0
# einops>=0.7.0

import torch
from einops import rearrange, repeat
```

--------------------------------

### Reference paper BibTeX

Source: https://context7.com/lucidrains/neural-plexer-pytorch/llms.txt

Citation for the underlying research paper.

```bibtex
@article{Qiao2022DynamicBackbonePS,
    title   = {Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models},
    author  = {Zhuoran Qiao and Weili Nie and Arash Vahdat and Thomas F. Miller and Anima Anandkumar},
    journal = {ArXiv},
    year    = {2022},
    volume  = {abs/2209.15171}
}
```

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