xpm-torch
PyTorch training framework built on experimaestro and Lightning Fabric.
Features
- Module system:
Modulebase class combining experimaestroConfigwithtorch.nn.Module, with safetensors serialization - Training:
Learnertask 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
1 maintainer
Metadata
1 maintainer
Release files for xpm-torch 0.2.0
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