install: tighten comments
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Daniel Han
parent
8997bf020a
commit
8a2389c5dc
3 changed files with 38 additions and 53 deletions
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@ -326,11 +326,8 @@ cu130onlytorch291 = [
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"xformers @ https://download.pytorch.org/whl/cu130/xformers-0.0.33.post2-cp39-abi3-win_amd64.whl ; (sys_platform == 'win32')",
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]
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cu126onlytorch2100 = [
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# The explicit torch pin replicates the xformers 0.0.34 wheel's transitive
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# torch==2.10.0 pin on machines where the x86-64-only wheel is skipped
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# (Linux aarch64 has real 2.10.0 wheels; Windows ARM64 fails loudly).
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# Without it an ARM64 install of the cu126-torch2100 wrapper would proceed
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# unpinned and resolve a newer torch.
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# Pin torch so ARM64 installs (x86-64-only xformers wheel and its transitive
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# torch pin skipped) stay on 2.10 instead of resolving newer.
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"torch==2.10.0",
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"xformers @ https://download.pytorch.org/whl/cu126/xformers-0.0.34-cp39-abi3-manylinux_2_28_x86_64.whl ; ('linux' in sys_platform) and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
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"xformers @ https://download.pytorch.org/whl/cu126/xformers-0.0.34-cp39-abi3-win_amd64.whl ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
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@ -348,14 +345,9 @@ cu130onlytorch2100 = [
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"xformers @ https://download.pytorch.org/whl/cu130/xformers-0.0.34-cp39-abi3-win_amd64.whl ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
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]
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cu126onlytorch2110 = [
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# xformers 0.0.35 does not hard-pin torch the way 0.0.34 pinned torch==2.10.0,
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# so the torch 2.11 trio is pinned explicitly. Use the +cu126 LOCAL build, not
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# a bare torch>=2.11: torch 2.11's default PyPI wheel is CUDA 13.0 (2.10 was
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# CUDA 12.x), so a bare resolve would pair a cu130 torch with the cu126
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# xformers below and fail at import. The +cu126 label only resolves from the
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# matching download.pytorch.org/whl/cu126 index the installer configures, so
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# torch stays on the same CUDA as xformers (or fails loudly if that index is
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# absent) instead of silently mismatching.
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# xformers 0.0.35 does not pin torch, so pin the trio to the +cu126 local
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# build: torch 2.11 defaults to a CUDA-13 PyPI wheel, and only the +cu126 tag
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# resolves from the cu126 index alongside the cu126 xformers below.
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"torch==2.11.0+cu126",
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"torchvision==0.26.0+cu126",
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"torchaudio==2.11.0+cu126",
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@ -363,9 +355,8 @@ cu126onlytorch2110 = [
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"xformers @ https://download.pytorch.org/whl/cu126/xformers-0.0.35-py39-none-win_amd64.whl ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
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]
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cu128onlytorch2110 = [
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# +cu128 local build for the same reason as cu126onlytorch2110 above: torch
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# 2.11's default PyPI wheel is CUDA 13.0, so pin to the cu128 index to keep the
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# torch trio on the same CUDA as the cu128 xformers wheel.
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# Same +cuNNN pin as cu126onlytorch2110: keeps the trio on the cu128 index
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# instead of torch 2.11's CUDA-13 PyPI default.
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"torch==2.11.0+cu128",
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"torchvision==0.26.0+cu128",
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"torchaudio==2.11.0+cu128",
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@ -373,13 +364,9 @@ cu128onlytorch2110 = [
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"xformers @ https://download.pytorch.org/whl/cu128/xformers-0.0.35-py39-none-win_amd64.whl ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
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]
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cu130onlytorch2110 = [
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# Pinned to the +cu130 local build like the cu126/cu128 extras: a bare range
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# lets a configured CUDA-12 extra index win (PEP 440 ranks 2.11.0+cu126 above
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# the unlabelled 2.11.0), and a ===2.11.0 pin would force-replace the trio on
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# machines installed from the official cu130 index (whose wheels carry the
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# +cu130 local tag). The exact +cu130 pins accept the official cu130-index
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# install as-is and fail loudly anywhere the cu130 index is missing;
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# _auto_install.py appends the matching index for every torch2110 CUDA extra.
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# Same +cuNNN pin as the cu126/cu128 extras: a bare range lets a CUDA-12 index
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# win (PEP 440 ranks +cu126 above unlabelled 2.11.0) and ===2.11.0 would
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# force-replace official cu130-index installs. _auto_install.py adds the index.
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"torch==2.11.0+cu130",
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"torchvision==0.26.0+cu130",
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"torchaudio==2.11.0+cu130",
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@ -1,13 +1,24 @@
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# Unsloth Zoo - Utilities for Unsloth
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# Copyright 2023-present Daniel Han-Chen, Michael Han-Chen & the Unsloth team. All rights reserved.
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published
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# by the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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#
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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"""Regression guard for the CUDA torch2110 optional-dependency extras.
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torch 2.11's DEFAULT PyPI wheel is CUDA 13.0 (torch 2.10 defaulted to CUDA 12.x).
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So the CUDA-12 `cuXXXonlytorch2110` extras must pin the torch trio to the matching
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`+cuXXX` local build; a bare `torch>=2.11` there would resolve a cu130 torch from
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PyPI alongside the cu126/cu128 xformers wheel and fail at import. The cu130 extra is
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pinned to +cu130 too: a bare or ===-pinned spec either lets a foreign CUDA index
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outrank the intended wheel or force-replaces official cu130-index installs.
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Hermetic: only parses pyproject.toml, no network or install.
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The cuXXXonlytorch2110 extras must pin the torch trio to the matching +cuXXX local
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build (torch 2.11 defaults to a CUDA-13 PyPI wheel), or resolution mismatches the
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xformers wheel. Hermetic: only parses pyproject.toml, no network or install.
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"""
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from __future__ import annotations
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@ -17,7 +28,7 @@ from pathlib import Path
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import pytest
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from packaging.requirements import Requirement
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try: # tomllib is stdlib on Python 3.11+; older interpreters need the tomli backport.
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try: # tomllib is stdlib on 3.11+; older interpreters need the tomli backport.
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import tomllib
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except ModuleNotFoundError: # pragma: no cover - Python 3.9 / 3.10
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tomllib = pytest.importorskip("tomli")
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@ -33,9 +44,7 @@ def _extra(name: str) -> list[str]:
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def _reqs(specs: list[str]) -> dict[str, list[Requirement]]:
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# Keyed by name -> list: each extra carries one Linux and one Windows
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# xformers requirement, so a plain name -> Requirement dict would silently
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# drop the Linux entry.
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# name -> list: each extra has one Linux and one Windows xformers requirement.
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out: dict[str, list[Requirement]] = {}
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for spec in specs:
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r = Requirement(spec)
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@ -45,9 +54,7 @@ def _reqs(specs: list[str]) -> dict[str, list[Requirement]]:
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@pytest.mark.parametrize("cuda", ["cu126", "cu128", "cu130"])
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def test_cuda12_torch2110_pins_matching_local_build(cuda: str):
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# Each of torch/torchvision/torchaudio must pin the exact +cuXXX local build
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# so it can only resolve from the matching PyTorch CUDA index, never the
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# CUDA-13 default on PyPI.
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# Each trio member must pin the exact +cuXXX local build.
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reqs = _reqs(_extra(f"{cuda}onlytorch2110"))
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for pkg in _TORCH_TRIO:
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(req,) = reqs[pkg]
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@ -65,9 +72,7 @@ def test_cuda12_torch2110_pins_matching_local_build(cuda: str):
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assert (
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f"/whl/{cuda}/xformers-0.0.35-" in r.url
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), f"xformers not on the {cuda} index: {r.url}"
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# The wheels are x86-64 only, so the markers must exclude other machines
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# (e.g. Linux aarch64 such as GB200/DGX Spark, Windows ARM64) where the
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# torch trio resolves fine but these wheels would abort the install.
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# x86-64-only wheels: markers must exclude aarch64 / ARM64.
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assert r.marker is not None
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assert not r.marker.evaluate({"sys_platform": "linux", "platform_machine": "aarch64"})
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assert not r.marker.evaluate({"sys_platform": "win32", "platform_machine": "ARM64"})
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@ -78,8 +83,7 @@ def test_cuda12_torch2110_pins_matching_local_build(cuda: str):
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@pytest.mark.parametrize("cuda", ["cu126", "cu128", "cu130"])
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@pytest.mark.parametrize("variant", ["", "ampere-"])
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def test_torch2110_wrapper_references_matching_leaf(cuda: str, variant: str):
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# The six public wrappers must pull in the usual huggingface + bitsandbytes
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# pair and reference the internal leaf of the SAME CUDA version.
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# Wrappers pull huggingface + bitsandbytes and the leaf of the same CUDA version.
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specs = _extra(f"{cuda}-{variant}torch2110")
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assert specs == [
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"unsloth[huggingface]",
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@ -90,11 +94,8 @@ def test_torch2110_wrapper_references_matching_leaf(cuda: str, variant: str):
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@pytest.mark.parametrize("cuda", ["cu126", "cu128", "cu130"])
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def test_cuda12_torch2100_keeps_torch_pinned_off_x86(cuda: str):
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# The torch2100 leaves used to rely on the xformers 0.0.34 wheel's transitive
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# torch==2.10.0 pin. Now that the x86-64-only wheels carry platform_machine
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# markers, the leaf must pin torch explicitly so an ARM64 install stays on
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# torch 2.10 (Linux aarch64 wheels exist) or fails loudly (Windows ARM64)
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# instead of resolving an unpinned newer torch.
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# Now the xformers wheels carry x86-64 markers, the leaf must pin torch
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# explicitly so ARM64 installs stay on 2.10 instead of resolving newer.
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reqs = _reqs(_extra(f"{cuda}onlytorch2100"))
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(torch_req,) = reqs["torch"]
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assert str(torch_req.specifier) == "==2.10.0", (
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@ -42,10 +42,7 @@ else: raise RuntimeError(f"Torch = {v} too new!")
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if v > V('2.6.9') and cuda not in ("11.8", "12.6", "12.8", "13.0"): raise RuntimeError(f"CUDA = {cuda} not supported!")
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if v >= V('2.10.0') and cuda not in ("12.6", "12.8", "13.0"): raise RuntimeError(f"Torch = {v} requires CUDA 12.6, 12.8, or 13.0! Got CUDA = {cuda}")
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x = x.format(cuda.replace(".", ""), "-ampere" if False else "") # is_ampere is broken due to flash-attn
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# The CUDA torch2110 extras pin the torch trio to the exact +cuNNN local build,
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# which only resolves from the matching PyTorch CUDA index (a bare spec would let
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# a configured foreign CUDA index outrank the intended wheel, since PEP 440 ranks
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# any local build above the unlabelled release), so add that index for every
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# CUDA torch 2.11 environment.
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# The torch2110 extras pin the trio to +cuNNN local builds, which only resolve
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# from the matching PyTorch CUDA index, so add that index for torch 2.11.
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extra_index = f' --extra-index-url https://download.pytorch.org/whl/cu{cuda.replace(".", "")}' if (x.endswith('-torch2110') and cuda in ("12.6", "12.8", "13.0")) else ''
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print(f'pip install --upgrade pip setuptools wheel && pip install --no-deps git+https://github.com/unslothai/unsloth-zoo.git && pip install "unsloth[{x}] @ git+https://github.com/unslothai/unsloth.git" --no-build-isolation{extra_index}')
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