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# Benchmark ViT

- [Code - ViT Benchmark](https://github.com/legacyai/tf-transformers/tree/main/benchmark/vit)

This is used to benchmark the performance of ViT model on text generation tasks. We evaluate it using 3 frameworks.
Tensorflow-Transformers (default), HuggingFace PyTorch, HuggingFace Tensorflow and HuggingFace JAX (pending).
Executing these scripts are fairly straightfoward and expect users to install the necessary libraries before executing
the benchmark script.

All the configuration are managed using [Hydra](https://github.com/facebookresearch/hydra).

-> Machine - **Tesla V100-SXM2 32GB**

-> Tensorflow-version - **2.4.1**

-> Huggingface-Transformer-Version - **4.12.5**

-> PyTorch-Version - **1.9.0**

## Tensorflow-Transformers. (tft)

The default benchmark mode is ```tft```.
1. To execute ```tft``` (default) :
    ```python run.py benchmark=tft```

2. To execute ```type``` eg ```keras_model``` :
    ```python run.py benchmark=tft benchmark.model.type=keras_model```

        * a. keras_model    -  Uses tf.keras.Model.
        * b. saved_model    -  Uses tf.saved_model
        * c. saved_model_tf-io   -  Uses tf.saved_model, ```model + tf.io ``` is serialized together.


## HuggingFace-Tensorflow. (hf-tf)

1. To execute ```hf-tf``` (default) :
    ```python run.py benchmark=hf benchmark.model.type=tf```


## HuggingFace-PyTorch. (hf-pt)

1. To execute ```hf-pt``` (default) :
    ```python run.py benchmark=hf benchmark.model.type=pt```


## Official Benchmarks on Keras Flowed dataset (5000 samples)

```
Text Classification:
|                            |   batch_size | time (s)      |   samples/second |
|:---------------------------|-------------:|:-------------:|:-----------|------
| tft + saved_model          |           32 |  29.06  sec   |              126 |
| tft + saved_model + tf-io  |           32 |  17.62  sec   |              208 |
| tft + keras_model          |           32 |  29.48  sec   |              124 |
| hf_tf                      |           32 |  95.84  sec   |               38 |
| hf_pt                      |           32 |  24.79  sec   |              148 |
| tft + keras + hf pipeline  |           32 |  94.44 sec    |               39 |
```