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# SPDX-License-Identifier: Apache-2.0

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# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

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# http://www.apache.org/licenses/LICENSE-2.0

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# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

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# limitations under the License.

# Public training requirements (Torch-only pipeline).

# Install a PyTorch build compatible with your Python/CUDA stack.

# Target Python versions: 3.11, 3.12, 3.13

-r requirements_public_inference.txt

cuquantum-python-cu12>=26.03.0

tensorboard

torchinfo

# decoder_ablation workflow

scipy

ldpc

beliefmatching

# ONNX quantization (INT8/FP8 via QUANT_FORMAT).

# nvidia-modelopt[onnx] officially caps at Python <3.13 but works on 3.13 in practice.

# check_python_compat.sh installs it with --ignore-requires-python on Python 3.13+.

# For manual installs on Python 3.13+: pip install nvidia-modelopt[onnx] --ignore-requires-python

# onnxruntime is the INT8-only fallback when modelopt is not importable.

nvidia-modelopt[onnx]; python_version < "3.13"

onnxruntime; python_version >= "3.13"