File size: 1,317 Bytes
c94c8c9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 |
from contextlib import nullcontext
import torch
import torch.nn as nn
from transformers import CLIPTextModelWithProjection
from modules.build import LANGUAGE_REGISTRY
from modules.utils import get_mlp_head
@LANGUAGE_REGISTRY.register()
class CLIPLanguageEncoder(nn.Module):
def __init__(self, cfg, weights="openai/clip-vit-large-patch14", output_dim=768, freeze_backbone=True, use_projection=False, dropout=0.1):
super().__init__()
self.context = torch.no_grad if freeze_backbone else nullcontext
self.model = CLIPTextModelWithProjection.from_pretrained(weights)
self.use_projection = use_projection
if use_projection:
self.projection = get_mlp_head(self.model.config.hidden_size, output_dim, output_dim, dropout=dropout)
#self.attention = nn.MultiheadAttention(embed_dim=768, num_heads=12, batch_first=True)
def forward(self, txt_ids, txt_masks):
with self.context():
txt = self.model(txt_ids, txt_masks).last_hidden_state
txt = self.model.text_projection(txt)
txt = torch.nn.functional.normalize(txt, p=2, dim=2)
#txt = self.attention(txt, txt, txt, key_padding_mask=txt_masks.logical_not())[0]
if self.use_projection:
txt = self.projection(txt)
return txt |