From 028d3f6425d85f122027c127fba8bcbf4f66ee75 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:05:02 +0300 Subject: ruff auto fixes --- modules/devices.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/devices.py') diff --git a/modules/devices.py b/modules/devices.py index c705a3cb..d8a34a0f 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -65,7 +65,7 @@ def enable_tf32(): # enabling benchmark option seems to enable a range of cards to do fp16 when they otherwise can't # see https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/4407 - if any([torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())]): + if any(torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())): torch.backends.cudnn.benchmark = True torch.backends.cuda.matmul.allow_tf32 = True -- cgit v1.2.1 From 8faac8b96313c6c4bf0a81bddecff4d6ba22ac25 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 21 May 2023 21:55:14 +0300 Subject: run basic torch calculation at startup in parallel to reduce the performance impact of first generation --- modules/devices.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) (limited to 'modules/devices.py') diff --git a/modules/devices.py b/modules/devices.py index d8a34a0f..1ed6ffdc 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -1,5 +1,7 @@ import sys import contextlib +from functools import lru_cache + import torch from modules import errors @@ -154,3 +156,19 @@ def test_for_nans(x, where): message += " Use --disable-nan-check commandline argument to disable this check." raise NansException(message) + + +@lru_cache +def first_time_calculation(): + """ + just do any calculation with pytorch layers - the first time this is done it allocaltes about 700MB of memory and + spends about 2.7 seconds doing that, at least wih NVidia. + """ + + x = torch.zeros((1, 1)).to(device, dtype) + linear = torch.nn.Linear(1, 1).to(device, dtype) + linear(x) + + x = torch.zeros((1, 1, 3, 3)).to(device, dtype) + conv2d = torch.nn.Conv2d(1, 1, (3, 3)).to(device, dtype) + conv2d(x) -- cgit v1.2.1 From ba70a220e3176153ba2a559acb9e5aa692dce7ca Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 5 Jun 2023 22:20:29 +0300 Subject: Remove a bunch of unused/vestigial code As found by Vulture and some eyes --- modules/devices.py | 7 ------- 1 file changed, 7 deletions(-) (limited to 'modules/devices.py') diff --git a/modules/devices.py b/modules/devices.py index 1ed6ffdc..620ed1a6 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -15,13 +15,6 @@ def has_mps() -> bool: else: return mac_specific.has_mps -def extract_device_id(args, name): - for x in range(len(args)): - if name in args[x]: - return args[x + 1] - - return None - def get_cuda_device_string(): from modules import shared -- cgit v1.2.1