expansionnet-v2
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56 lines
2.5 KiB
56 lines
2.5 KiB
2 years ago
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# Copyright 2021 Zilliz. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import sys
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import os
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from pathlib import Path
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import torch
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from torchvision import transforms
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from transformers import GPT2Tokenizer
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from towhee.types.arg import arg, to_image_color
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from towhee.types.image_utils import to_pil
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from towhee.operator.base import NNOperator, OperatorFlag
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from towhee import register
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from towhee.models import clip
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class ExpansionNetV2(NNOperator):
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"""
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ExpansionNet V2 image captioning operator
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"""
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def __init__(self, model_name: str):
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super().__init__()
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sys.path.append(str(Path(__file__).parent))
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from models.End_ExpansionNet_v2 import End_ExpansionNet_v2
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sys.path.pop()
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with open('demo_coco_tokens.pickle') as fw:
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self.model = End_ExpansionNet_v2(swin_img_size=img_size, swin_patch_size=4, swin_in_chans=3,
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swin_embed_dim=192, swin_depths=[2, 2, 18, 2], swin_num_heads=[6, 12, 24, 48],
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swin_window_size=12, swin_mlp_ratio=4., swin_qkv_bias=True, swin_qk_scale=None,
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swin_drop_rate=0.0, swin_attn_drop_rate=0.0, swin_drop_path_rate=0.0,
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swin_norm_layer=torch.nn.LayerNorm, swin_ape=False, swin_patch_norm=True,
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swin_use_checkpoint=False,
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final_swin_dim=1536,
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d_model=model_args.model_dim, N_enc=model_args.N_enc,
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N_dec=model_args.N_dec, num_heads=8, ff=2048,
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num_exp_enc_list=[32, 64, 128, 256, 512],
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num_exp_dec=16,
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output_word2idx=coco_tokens['word2idx_dict'],
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output_idx2word=coco_tokens['idx2word_list'],
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max_seq_len=args.max_seq_len, drop_args=model_args.drop_args,
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rank='cpu')
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