chore: 添加虚拟环境到仓库

- 添加 backend_service/venv 虚拟环境
- 包含所有Python依赖包
- 注意：虚拟环境约393MB，包含12655个文件

backend_service/venv/lib/python3.13/site-packages/onnxruntime/quantization/preprocess.py

@@ -0,0 +1,141 @@
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft, Intel Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import logging
+import sys
+
+from .shape_inference import quant_pre_process
+
+logger = logging.getLogger(__name__)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(
+        description="""Model optimizer and shape inferencer, in preparation for quantization,
+Consists of three optional steps:
+1. Symbolic shape inference (best for transformer models).
+2. Model optimization.
+3. ONNX shape inference.
+
+Model quantization with QDQ format, i.e. inserting QuantizeLinear/DeQuantizeLinear on
+the tensor, requires tensor shape information to perform its best. Currently, shape inferencing
+works best with optimized model. As a result, it is highly recommended to run quantization
+on optimized model with shape information. This is the tool for optimization and shape
+inferencing.
+
+Essentially this tool performs the following three (skippable) steps:
+
+1. Symbolic shape inference.
+2. Model optimization
+3. ONNX shape inference"""
+    )
+
+    parser.add_argument("--input", required=True, help="Path to the input model file")
+    parser.add_argument("--output", required=True, help="Path to the output model file")
+    parser.add_argument(
+        "--skip_optimization",
+        type=bool,
+        default=False,
+        help="Skip model optimization step if true. It's a known issue that ORT"
+        " optimization has difficulty with model size greater than 2GB, rerun with"
+        " this option to get around this issue.",
+    )
+    parser.add_argument(
+        "--skip_onnx_shape",
+        type=bool,
+        default=False,
+        help="Skip ONNX shape inference. Symbolic shape inference is most effective"
+        " with transformer based models. Skipping all shape inferences may"
+        " reduce the effectiveness of quantization, as a tensor with unknown"
+        " shape can not be quantized.",
+    )
+    parser.add_argument(
+        "--skip_symbolic_shape",
+        type=bool,
+        default=False,
+        help="Skip symbolic shape inference. Symbolic shape inference is most"
+        " effective with transformer based models. Skipping all shape"
+        " inferences may reduce the effectiveness of quantization, as a tensor"
+        " with unknown shape can not be quantized.",
+    )
+    parser.add_argument(
+        "--auto_merge",
+        help="Automatically merge symbolic dims when confliction happens",
+        action="store_true",
+        default=False,
+    )
+    parser.add_argument(
+        "--int_max",
+        help="maximum value for integer to be treated as boundless for ops like slice",
+        type=int,
+        default=2**31 - 1,
+    )
+    parser.add_argument(
+        "--guess_output_rank",
+        help="guess output rank to be the same as input 0 for unknown ops",
+        action="store_true",
+        default=False,
+    )
+    parser.add_argument(
+        "--verbose",
+        help="Prints detailed logs of inference, 0: turn off, 1: warnings, 3: detailed",
+        type=int,
+        default=0,
+    )
+    parser.add_argument(
+        "--save_as_external_data",
+        help="Saving an ONNX model to external data",
+        action="store_true",
+        default=False,
+    )
+    parser.add_argument(
+        "--all_tensors_to_one_file",
+        help="Saving all the external data to one file",
+        action="store_true",
+        default=False,
+    )
+    parser.add_argument(
+        "--external_data_location",
+        help="The file location to save the external file",
+        default=None,
+    )
+    parser.add_argument(
+        "--external_data_size_threshold",
+        help="The size threshold for external data",
+        type=int,
+        default=1024,
+    )
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    if args.skip_optimization and args.skip_onnx_shape and args.skip_symbolic_shape:
+        logger.error("Skipping all three steps, nothing to be done. Quitting...")
+        sys.exit()
+
+    if (not args.skip_optimization) and args.save_as_external_data:
+        logger.error("ORT model optimization does not support external data yet!")
+        sys.exit()
+
+    logger.info("input model: %s", args.input)
+    logger.info("output model: %s", args.output)
+    quant_pre_process(
+        args.input,
+        args.output,
+        args.skip_optimization,
+        args.skip_onnx_shape,
+        args.skip_symbolic_shape,
+        args.auto_merge,
+        args.int_max,
+        args.guess_output_rank,
+        args.verbose,
+        args.save_as_external_data,
+        args.all_tensors_to_one_file,
+        args.external_data_location,
+        args.external_data_size_threshold,
+    )