xpm-torch 0.1.9

Experimaestro module for Pytorch-based experiments

xpm-torch

PyTorch training framework built on experimaestro and Lightning Fabric.

Features

• Module system: Module base class combining experimaestro Config with torch.nn.Module, with safetensors serialization
• Training: Learner task with checkpointing, validation listeners, and TensorBoard logging
• HuggingFace Hub: Upload/download models via ExperimaestroHFHub (from experimaestro)
• Distributed training: Lightning Fabric integration for multi-GPU/node training

Installation

pip install xpm-torch

Quick Start

from xpm_torch.module import Module
from experimaestro import Param
import torch
import torch.nn as nn

class MyModel(Module):
    input_dim: Param[int]
    hidden_dim: Param[int]

    def __initialize__(self):
        self.fc1 = nn.Linear(self.input_dim, self.hidden_dim)

    def forward(self, x):
        return self.fc1(x)

# Create config, then instance
cfg = MyModel.C(input_dim=50, hidden_dim=100)
model = cfg.instance()
model.initialize()

# Save/load with safetensors
from pathlib import Path
model.save_model(Path("checkpoint/model"))
model.load_model(Path("checkpoint/model"))

License

GPL-3.0