b107b432bb* Update llama.py * offload * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * continued pretraining trainer * Update trainer.py * Update trainer.py * Update trainer.py * Update trainer.py * is_bfloat16_supported * Update __init__.py * Update README.md * Update llama.py * is_bfloat16_supported * Update __init__.py
124 lines
4.9 KiB
Python
124 lines
4.9 KiB
Python
# Copyright 2023-present Daniel Han-Chen & the Unsloth team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import warnings
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import importlib
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# Currently only supports 1 GPU, or else seg faults will occur.
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if "CUDA_VISIBLE_DEVICES" in os.environ:
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devices = os.environ["CUDA_VISIBLE_DEVICES"]
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# Check if there are multiple cuda devices set in env
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if not devices.isdigit():
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first_id = devices.split(",")[0]
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warnings.warn(
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f"Unsloth: 'CUDA_VISIBLE_DEVICES' is currently {devices} \n"\
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"Multiple CUDA devices detected but we require a single device.\n"\
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f"We will override CUDA_VISIBLE_DEVICES to first device: {first_id}."
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)
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os.environ["CUDA_VISIBLE_DEVICES"] = str(first_id)
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else:
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# warnings.warn("Unsloth: 'CUDA_VISIBLE_DEVICES' is not set. We shall set it ourselves.")
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os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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pass
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# Reduce VRAM usage by reducing fragmentation
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os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
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try:
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import torch
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except:
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raise ImportError("Pytorch is not installed. Go to https://pytorch.org/.\n"\
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"We have some installation instructions on our Github page.")
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pass
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# Fix up is_bf16_supported https://github.com/unslothai/unsloth/issues/504
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major_version, minor_version = torch.cuda.get_device_capability()
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SUPPORTS_BFLOAT16 = (major_version >= 8)
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def is_bf16_supported(): return SUPPORTS_BFLOAT16
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torch.cuda.is_bf16_supported = is_bf16_supported
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# We support Pytorch 2
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# Fixes https://github.com/unslothai/unsloth/issues/38
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torch_version = torch.__version__.split(".")
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major_torch, minor_torch = torch_version[0], torch_version[1]
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major_torch, minor_torch = int(major_torch), int(minor_torch)
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if (major_torch < 2):
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raise ImportError("Unsloth only supports Pytorch 2 for now. Please update your Pytorch to 2.1.\n"\
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"We have some installation instructions on our Github page.")
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elif (major_torch == 2) and (minor_torch < 2):
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# Disable expandable_segments
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del os.environ["PYTORCH_CUDA_ALLOC_CONF"]
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pass
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# Try loading bitsandbytes and triton
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import bitsandbytes as bnb
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import triton
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from triton.common.build import libcuda_dirs
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import os
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import re
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import numpy as np
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import subprocess
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try:
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cdequantize_blockwise_fp32 = bnb.functional.lib.cdequantize_blockwise_fp32
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libcuda_dirs()
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except:
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warnings.warn(
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"Unsloth: Running `ldconfig /usr/lib64-nvidia` to link CUDA."\
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)
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if os.path.exists("/usr/lib64-nvidia"):
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os.system("ldconfig /usr/lib64-nvidia")
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elif os.path.exists("/usr/local"):
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# Sometimes bitsandbytes cannot be linked properly in Runpod for example
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possible_cudas = subprocess.check_output(["ls", "-al", "/usr/local"]).decode("utf-8").split("\n")
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find_cuda = re.compile(r"[\s](cuda\-[\d\.]{2,})$")
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possible_cudas = [find_cuda.search(x) for x in possible_cudas]
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possible_cudas = [x.group(1) for x in possible_cudas if x is not None]
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# Try linking cuda folder, or everything in local
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if len(possible_cudas) == 0:
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os.system(f"ldconfig /usr/local/")
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else:
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find_number = re.compile(r"([\d\.]{2,})")
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latest_cuda = np.argsort([float(find_number.search(x).group(1)) for x in possible_cudas])[::-1][0]
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latest_cuda = possible_cudas[latest_cuda]
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os.system(f"ldconfig /usr/local/{latest_cuda}")
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pass
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importlib.reload(bnb)
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importlib.reload(triton)
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try:
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import bitsandbytes as bnb
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from triton.common.build import libcuda_dirs
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cdequantize_blockwise_fp32 = bnb.functional.lib.cdequantize_blockwise_fp32
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libcuda_dirs()
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except:
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warnings.warn(
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"Unsloth: CUDA is not linked properly.\n"\
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"Try running `python -m bitsandbytes` then `python -m xformers.info`\n"\
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"We tried running `ldconfig /usr/lib64-nvidia` ourselves, but it didn't work.\n"\
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"You need to run in your terminal `sudo ldconfig /usr/lib64-nvidia` yourself, then import Unsloth.\n"\
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"Also try `sudo ldconfig /usr/local/cuda-xx.x` - find the latest cuda version.\n"\
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"Unsloth will still run for now, but maybe it might crash - let's hope it works!"
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)
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pass
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from .models import *
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from .save import *
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from .chat_templates import *
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from .tokenizer_utils import *
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from .trainer import *
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