# PiT

**Category:** ViT · **Code:**
[`timm/models/pit.py`](https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/pit.py) ·
**Architectures:** 8 · **Pretrained weights:** 8 (8 with ImageNet-1k results)

Pooling-based Vision Transformers (PiT) reduce the spatial size and increase the channels of the tokens between stages
with a depthwise convolution pooling layer, as in CNNs.

## Papers

* [Rethinking Spatial Dimensions of Vision Transformers](https://arxiv.org/abs/2103.16302)

## Usage

See the [Quickstart](../quickstart) for loading pretrained weights, image preprocessing and fine-tuning, and [Feature
Extraction](../feature_extraction) for using the models as backbones.

```py
>>> import timm
>>> model = timm.create_model('pit_s_distilled_224.in1k', pretrained=True)
>>> data_config = timm.data.resolve_model_data_config(model)
```

## Model API support

| Feature | `PoolingVisionTransformer` |
|---|---|
| [`features_only=True` feature maps](../model_api#intermediate-features) | ✓ (strides 7, 14, 28) |
| [`forward_intermediates()`](../model_api#intermediate-features) | ✓ |
| [`prune_intermediate_layers()`](../model_api#intermediate-features) | ✓ |
| [Any input size, no changes needed](../model_api#input-size) | ✗ |
| [`set_input_size()`](../model_api#input-size) | ✗ |
| [`dynamic_img_size=True`](../model_api#input-size) | ✗ |
| [`set_grad_checkpointing()`](../model_api#training-hooks) | ✗ |
| [Layer-wise LR decay (`group_matcher()`)](../model_api#training-hooks) | ✗ |
| [`reset_classifier()`](../model_api#classifier) | ✓ |

✓ supported, ✓ (square) works for square sizes only, ✗ not supported, – not needed (the model already accepts any input
size). Checked by running each feature on a randomly initialized model (`PoolingVisionTransformer` with `pit_ti_224` at
224), other architectures of the same class are expected to behave the same. See the [Model API](../model_api) page for
details.

## Architectures

| Architecture | Params (M) | GMACs | Input size | Pretrained weights |
|---|---:|---:|---:|---:|
| `pit_b_224` | 73.76 | 12.42 | 224 | 1 |
| `pit_b_distilled_224` | 74.79 | 12.50 | 224 | 1 |
| `pit_s_224` | 23.46 | 2.88 | 224 | 1 |
| `pit_s_distilled_224` | 24.04 | 2.90 | 224 | 1 |
| `pit_ti_224` | 4.85 | 0.70 | 224 | 1 |
| `pit_ti_distilled_224` | 5.10 | 0.71 | 224 | 1 |
| `pit_xs_224` | 10.62 | 1.40 | 224 | 1 |
| `pit_xs_distilled_224` | 11.00 | 1.41 | 224 | 1 |

GMACs and parameter counts are for the default input size and classifier of each architecture, from the [benchmark
results](https://github.com/huggingface/pytorch-image-models/tree/main/results).

## Pretrained weights

Top-1 is ImageNet-1k validation accuracy from
[`results-imagenet.csv`](https://github.com/huggingface/pytorch-image-models/blob/main/results/results-imagenet.csv) at
the listed eval size, - if the weight has no ImageNet-1k result (e.g. pretraining or image-text weights). Classes is the
size of the pretrained classifier, none for weights without one.

| Weight | Input size | Top-1 (%) | Eval size | Classes | License | Hub |
|---|---:|---:|---:|---:|---|---|
| `pit_b_224.in1k` | 224 | 82.458 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_b_224.in1k) |
| `pit_b_distilled_224.in1k` | 224 | 83.774 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_b_distilled_224.in1k) |
| `pit_s_224.in1k` | 224 | 81.114 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_s_224.in1k) |
| `pit_s_distilled_224.in1k` | 224 | 81.826 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_s_distilled_224.in1k) |
| `pit_ti_224.in1k` | 224 | 72.926 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_ti_224.in1k) |
| `pit_ti_distilled_224.in1k` | 224 | 74.276 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_ti_distilled_224.in1k) |
| `pit_xs_224.in1k` | 224 | 78.196 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_xs_224.in1k) |
| `pit_xs_distilled_224.in1k` | 224 | 79.172 | 224 | 1000 | apache-2.0 | [timm](https://huggingface.co/timm/pit_xs_distilled_224.in1k) |