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import sys, os |
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current_path = os.path.dirname(os.path.abspath(__file__)) |
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sys.path.append(current_path) |
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import jax |
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from vit_gpt2.modeling_flax_vit_gpt2_lm import FlaxViTGPT2LMForConditionalGeneration |
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from transformers import ViTFeatureExtractor |
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from PIL import Image |
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import requests |
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import numpy as np |
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from transformers import ViTFeatureExtractor, GPT2Tokenizer |
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model_name_or_path = './outputs/ckpt_2/' |
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flax_vit_gpt2_lm = FlaxViTGPT2LMForConditionalGeneration.from_pretrained(model_name_or_path) |
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vit_model_name = 'google/vit-base-patch16-224-in21k' |
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feature_extractor = ViTFeatureExtractor.from_pretrained(vit_model_name) |
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gpt2_model_name = 'asi/gpt-fr-cased-small' |
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tokenizer = GPT2Tokenizer.from_pretrained(gpt2_model_name) |
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max_length = 64 |
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num_beams = 16 |
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gen_kwargs = {"max_length": max_length, "num_beams": num_beams} |
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@jax.jit |
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def predict_fn(pixel_values): |
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return flax_vit_gpt2_lm.generate(pixel_values, **gen_kwargs) |
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def predict(image, pxs=None): |
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encoder_inputs = feature_extractor(images=image, return_tensors="jax") |
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pixel_values = encoder_inputs.pixel_values |
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if pxs is not None: |
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pixel_values = pxs |
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generation = predict_fn(pixel_values) |
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token_ids = np.array(generation.sequences)[0] |
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caption = tokenizer.decode(token_ids) |
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return caption, token_ids |
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if __name__ == '__main__': |
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from datetime import datetime |
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idx = 11 |
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url = f'./wit_data_dir/train/images/{idx}.jpg' |
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image = Image.open(url) |
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encoder_inputs = feature_extractor(images=image, return_tensors="np") |
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pv1 = encoder_inputs.pixel_values |
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pv2 = np.load(f'./wit_data_dir/train/numpy/{idx}.npy') |
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print(np.sum(np.abs(pv1 - pv2))) |
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s = datetime.now() |
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caption, token_ids = predict(image, pxs=pv2) |
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e = datetime.now() |
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e = (e - s).total_seconds() |
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print(e) |
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print(f'token_ids: {token_ids}') |
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print(f'caption: {caption}') |
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for _ in range(1): |
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s = datetime.now() |
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caption, token_ids = predict(image, pxs=None) |
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e = datetime.now() |
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e = (e - s).total_seconds() |
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print(e) |
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print('-' * 20) |
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print(f'token_ids: {token_ids}') |
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print(f'caption: {caption}') |
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