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PyTorchFire: A GPU-Accelerated Wildfire Simulator with Differentiable Cellular Automata

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PyTorchFire: A GPU-Accelerated Wildfire Simulator with Differentiable Cellular Automata

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Installation

Install with minimal dependencies:

pip install pytorchfire

Install with dependencies for examples:

pip install 'pytorchfire[examples]'

Quick Start

pip install 'wildtorch[full]'

Perform wildfire prediction:

from pytorchfire import WildfireModel

model = WildfireModel() # Create a model with default parameters and environment data
model = model.cuda() # Move the model to GPU
# model.reset(seed=seed) # Reset the model with a seed
for _ in range(100): # Run the model for 100 steps
    model.compute() # Compute the next state

Perform parameter calibration:

import torch
from pytorchfire import WildfireModel, BaseTrainer

model = WildfireModel()

trainer = BaseTrainer(model)

trainer.train()
trainer.evaluate()

API Documents

See at Our Read the Docs.

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