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refs/deplo
| Author | SHA1 | Date | |
|---|---|---|---|
| 766fca2517 | |||
| 5b9d078db3 | |||
| 98684d5814 |
19
1/model.py
19
1/model.py
@ -2,7 +2,6 @@ import triton_python_backend_utils as pb_utils
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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import numpy as np
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import json
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import os
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class TritonPythonModel:
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def initialize(self, args):
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@ -13,27 +12,9 @@ class TritonPythonModel:
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"""
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self.logger = pb_utils.Logger
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current_file_path = os.path.abspath(__file__)
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self.logger.log_info(f"current_file_path: {current_file_path}")
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self.model_name = args["model_name"]
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model_repository = args["model_repository"]
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model_path = f"{model_repository}/{self.model_name}"
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#model_path = "/cheetah/input/model/gemma-3-1b-it/gemma-3-1b-it"
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input_model_path = model_path
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if os.path.exists(input_model_path):
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file_list = os.listdir(input_model_path)
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self.logger.log_info(f"'{input_model_path}' 디렉토리의 파일 목록:")
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for file_name in file_list:
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self.logger.log_info(file_name)
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else:
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self.logger.log_info(f"'{input_model_path}' 디렉토리가 존재하지 않습니다.")
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self.logger.log_info(f"model_repository: {model_repository}")
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self.logger.log_info(f"model_path: {model_path}")
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self.model_config = json.loads(args["model_config"])
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@ -1,6 +1,3 @@
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test.txt
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test.txt
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test.txt
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test.txt
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test.txt
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@ -1,7 +1,6 @@
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# Triton backend to use
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name: "gemma-3-1b-it"
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backend: "python"
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max_batch_size: 0
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backend: "python"
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# Triton should expect as input a single string
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# input of variable length named 'text_input'
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@ -72,7 +71,6 @@ output [
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}
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]
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parameters: [
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{
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key: "enable_inference_trace",
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@ -86,4 +84,3 @@ instance_group [
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count: 1
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}
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]
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