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Author SHA1 Message Date
a91c637c60 Update model.py 2025-05-13 08:40:07 +00:00
a3dab09801 Create New File 2025-04-30 07:31:55 +00:00
203891813b modify model path 2025-04-29 13:59:26 +09:00
ddb8145bd1 print file list at input model directory 2025-04-29 13:46:56 +09:00
941523384f modify model path 2025-04-29 13:29:04 +09:00
6f5c252f55 add log 2025-04-29 13:00:21 +09:00
b19c4d2940 restructurized 2025-04-29 10:47:51 +09:00
12 changed files with 38 additions and 13 deletions

@ -2,6 +2,7 @@ import triton_python_backend_utils as pb_utils
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
import numpy as np
import json
import os
class TritonPythonModel:
def initialize(self, args):
@ -12,9 +13,27 @@ class TritonPythonModel:
"""
self.logger = pb_utils.Logger
current_file_path = os.path.abspath(__file__)
self.logger.log_info(f"current_file_path: {current_file_path}")
self.model_name = args["model_name"]
model_repository = args["model_repository"]
model_path = f"{model_repository}/{self.model_name}"
#model_path = "/cheetah/input/model/gemma-3-1b-it/gemma-3-1b-it"
input_model_path = model_path
if os.path.exists(input_model_path):
file_list = os.listdir(input_model_path)
self.logger.log_info(f"'{input_model_path}' 디렉토리의 파일 목록:")
for file_name in file_list:
self.logger.log_info(file_name)
else:
self.logger.log_info(f"'{input_model_path}' 디렉토리가 존재하지 않습니다.")
self.logger.log_info(f"model_repository: {model_repository}")
self.logger.log_info(f"model_path: {model_path}")
self.model_config = json.loads(args["model_config"])

@ -1,6 +1,7 @@
# Triton backend to use
name: "gemma-3-1b-it"
max_batch_size: 0
backend: "python"
max_batch_size: 0
# Triton should expect as input a single string
# input of variable length named 'text_input'
@ -71,6 +72,7 @@ output [
}
]
parameters: [
{
key: "enable_inference_trace",
@ -84,3 +86,4 @@ instance_group [
count: 1
}
]

@ -1,3 +1,6 @@
test.txt
test.txt
test.txt
test.txt
test.txt