Commit
•
3bd45f6
1
Parent(s):
3649225
added files
Browse files- README.md +3 -0
- handler.py +53 -0
- requirements.txt +5 -0
- sharded/config.json +256 -0
- sharded/pytorch_model-00001-of-00004.bin +3 -0
- sharded/pytorch_model-00002-of-00004.bin +3 -0
- sharded/pytorch_model-00003-of-00004.bin +3 -0
- sharded/pytorch_model-00004-of-00004.bin +3 -0
- sharded/pytorch_model.bin.index.json +0 -0
README.md
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---
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license: mit
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---
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handler.py
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# handler.py
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import torch
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from transformers import pipeline, AutoProcessor, Blip2ForConditionalGeneration
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import os
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"""import base64
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from io import BytesIO
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from PIL import Image"""
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# check for GPU
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device = 0 if torch.cuda.is_available() else -1
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class EndpointHandler():
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def __init__(self, path=""):
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blip2_proc = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b")
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#blip2 = Blip2ForConditionalGeneration.from_pretrained("sharded", device_map="auto", load_in_8bit=True)
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blip2 = Blip2ForConditionalGeneration.from_pretrained(os.path.join(path, "sharded"), device_map="auto", load_in_8bit=True)
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#translator = pipeline("translation",model="Helsinki-NLP/opus-mt-en-de",device=device)
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def __call__(self, data):
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# deserialize incomin request
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"""b64_img = data.pop("b64", data)
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lang = data.pop("lang", None)
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decode = data.pop("decode", None)
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#prepare image
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im_bytes = base64.b64decode(b64_img) # im_bytes is a binary image
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im_file = BytesIO(im_bytes) # convert image to file-like object
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image = Image.open(im_file).convert("RGB")
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output = {}
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inputs = self.blip2_proc(image, return_tensors="pt").to(device, torch.float16)
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#nucleus vs beam sampling
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if decode == None or decode == "beam":
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generated_ids = self.blip2.generate(**inputs, max_new_tokens=20)
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prediction = self.blip2_proc.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
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#english vs german caption
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if lang != None or lang == "de":
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translation = self.translator(prediction)
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output["beam"] = translation[0]
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else:
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output["beam"] = prediction
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if decode != None or decode == "nucleus":
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generated_ids = self.blip2.generate(**inputs, max_new_tokens=20)
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prediction = self.blip2_proc.batch_decode(generated_ids, skip_special_tokens=True,do_sample=True)[0].strip()
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#english vs german caption
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if lang != None or lang == "de":
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translation = self.translator(prediction)
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output["nucleus"] = translation[0]
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else:
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output["nucleus"] = prediction
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# postprocess the prediction
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return output"""
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return 73
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requirements.txt
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git+https://github.com/huggingface/transformers.git
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accelerate
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bitsandbytes
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Pillow
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torch
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sharded/config.json
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{
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"_commit_hash": "ca9e6c21b0ae56818ab19c8c873eb1bb5cfae2f8",
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"_name_or_path": "Salesforce/blip2-opt-2.7b",
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"architectures": [
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"Blip2ForConditionalGeneration"
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],
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"model_type": "blip-2",
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"num_query_tokens": 32,
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"qformer_config": {
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},
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