AllenNLP

2.10.1 verified Fri May 01 auth: no python maintenance

An open-source NLP research library built on PyTorch, providing flexible abstractions for building and training deep learning models. Current version is 2.10.1 (stable, maintenance mode). Release cadence: irregular, with minor releases every few months.

pip install allennlp

Common errors

error ModuleNotFoundError: No module named 'allennlp.common' ↓

cause Importing from incorrect package path or missing installation.

fix

Use correct import path: e.g., 'from allennlp.common import JsonDict'. Ensure package installed: pip install allennlp.

error RuntimeError: Expected all tensors to be on the same device, but found at least two devices ↓

cause Moving model/data between CPU and GPU incorrectly.

fix

Use 'model = model.cuda()' or 'model.to(device)' before training, and ensure tensors are moved similarly.

error ImportError: cannot import name 'AllenNlpModel' from 'allennlp.models' ↓

cause Outdated import style from pre-2.0 versions.

fix

Use 'from allennlp.models import Model' instead.

error AttributeError: 'AllennlpDataset' object has no attribute 'to_torch_dataset' ↓

cause Using deprecated dataset API.

fix

Use 'allennlp.data.DataLoader' and 'allennlp.data.Vocabulary' directly (see updated examples).

Warnings

breaking AllenNLP 2.0+ removed the old 'allennlp.commands' and many APIs changed. Projects using AllenNLP <1.x will not work. ↓

fix Migrate to new API (see migration guide: https://github.com/allenai/allennlp/blob/main/CHANGELOG.md)

deprecated The 'allennlp.data.DatasetReader' abstract class is being phased out in favor of 'allennlp.data.dataset_readers' concrete classes. Custom readers may need updates. ↓

fix Inherit from 'allennlp.data.dataset_readers.DatasetReader' instead.

gotcha Installing allennlp from pip may pull incompatible PyTorch versions. Always ensure torch matches your system. ↓

fix Install PyTorch first from pytorch.org, then pip install allennlp (without torch dependency).

Install

pip install allennlp[all]

Imports

AllenNLP
wrong
```
import allennlp
```
correct
```
from allennlp.models import Model
```
Top-level import does not expose common classes directly.

Predictor

wrong

from allennlp import Predictor

correct

from allennlp.predictors import Predictor

Predictor is in the predictors submodule.

DatasetReader
wrong
```
from allennlp.dataset_readers import DatasetReader
```
correct
```
from allennlp.data import DatasetReader
```
DatasetReader is a base class; concrete readers are under allennlp.data.dataset_readers.

Quickstart

Minimal model example demonstrating class structure and forward pass.

import torch
from allennlp.common import JsonDict
from allennlp.data import Instance
from allennlp.data.fields import TextField
from allennlp.data.token_indexers import SingleIdTokenIndexer
from allennlp.data.tokenizers import SpacyTokenizer
from allennlp.models import Model
from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder
from allennlp.modules.token_embedders import Embedding
from allennlp.nn import util

# Example: simple text classifier (not runnable without training data)
class SimpleClassifier(Model):
    def __init__(self, vocab, embed_dim=10):
        super().__init__(vocab)
        self.embedder = BasicTextFieldEmbedder({"tokens": Embedding(embedding_dim=embed_dim, num_embeddings=vocab.get_vocab_size('tokens'))})
        self.linear = torch.nn.Linear(embed_dim, vocab.get_vocab_size('labels'))

    def forward(self, text, label=None):
        embedded = self.embedder(text)
        logits = self.linear(embedded)
        output = {"logits": logits}
        if label is not None:
            output["loss"] = torch.nn.functional.cross_entropy(logits, label)
        return output

print("AllenNLP ready.")