How do I replace the evaclip?

[zxqing01]

If I want to use your model to replace evaclip, how should the following code be modified?

`
elif clip_pretrained=="EVA02-CLIP-B-16" or clip_pretrained=="EVA02-CLIP-L-14-336":
clip_model = eva_clip.create_model(model_name=clip_pretrained,
pretrained=cache_dir,
force_custom_clip=True,
precision="amp",
device=device)
self.tokenizer = open_clip.get_tokenizer(clip_pretrained)
clip_preprocess=None

def get_text_embeds(self, classnames, templates, clip_model, prompt=None):
if self.cache is not None and not self.training:
return self.cache

    if self.tokens is None or prompt is not None:
        tokens = []
        for classname in classnames:
            if ', ' in classname:
                classname_splits = classname.split(', ')
                texts = [template.format(classname_splits[0]) for template in templates]
            else:
                texts = [template.format(classname) for template in templates]  # format with class
            if self.tokenizer is not None:
                texts = self.tokenizer(texts).cuda()
            else: 
                texts = clip.tokenize(texts).cuda()
            tokens.append(texts)
        tokens = torch.stack(tokens, dim=0).squeeze(1)
        if prompt is None:
            self.tokens = tokens
    elif self.tokens is not None and prompt is None:
        tokens = self.tokens

    class_embeddings = clip_model.encode_text(tokens, prompt)
    class_embeddings = class_embeddings / class_embeddings.norm(dim=-1, keepdim=True)
    
    
    class_embeddings = class_embeddings.unsqueeze(1)
    
    if not self.training:
        self.cache = class_embeddings
        
    return class_embeddings`

[raytrun]

Thank you for your interest in our model. You can refer to this for detailed usage instructions.