From a4cb96d4ae82741be9f0d072a37af3ae39521379 Mon Sep 17 00:00:00 2001 From: brkirch Date: Sat, 11 Mar 2023 17:35:17 -0500 Subject: Remove test, use bool tensor fix by default The test isn't working correctly on macOS 13.3 and the bool tensor fix for cumsum is currently always needed anyway, so enable the fix by default. --- modules/mac_specific.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) (limited to 'modules/mac_specific.py') diff --git a/modules/mac_specific.py b/modules/mac_specific.py index ddcea53b..18e6ff72 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -23,7 +23,7 @@ def cumsum_fix(input, cumsum_func, *args, **kwargs): output_dtype = kwargs.get('dtype', input.dtype) if output_dtype == torch.int64: return cumsum_func(input.cpu(), *args, **kwargs).to(input.device) - elif cumsum_needs_bool_fix and output_dtype == torch.bool or cumsum_needs_int_fix and (output_dtype == torch.int8 or output_dtype == torch.int16): + elif output_dtype == torch.bool or cumsum_needs_int_fix and (output_dtype == torch.int8 or output_dtype == torch.int16): return cumsum_func(input.to(torch.int32), *args, **kwargs).to(torch.int64) return cumsum_func(input, *args, **kwargs) @@ -45,7 +45,6 @@ if has_mps: CondFunc('torch.Tensor.numpy', lambda orig_func, self, *args, **kwargs: orig_func(self.detach(), *args, **kwargs), lambda _, self, *args, **kwargs: self.requires_grad) elif version.parse(torch.__version__) > version.parse("1.13.1"): cumsum_needs_int_fix = not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.ShortTensor([1,1]).to(torch.device("mps")).cumsum(0)) - cumsum_needs_bool_fix = not torch.BoolTensor([True,True]).to(device=torch.device("mps"), dtype=torch.int64).equal(torch.BoolTensor([True,False]).to(torch.device("mps")).cumsum(0)) cumsum_fix_func = lambda orig_func, input, *args, **kwargs: cumsum_fix(input, orig_func, *args, **kwargs) CondFunc('torch.cumsum', cumsum_fix_func, None) CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None) -- cgit v1.2.3 From c5142e2fbecb50531a55aa804ea132c5d870858c Mon Sep 17 00:00:00 2001 From: brkirch Date: Fri, 24 Mar 2023 02:58:18 -0400 Subject: Add workaround for broken nn.Linear on macOS 13.2 Credit to danieldk (https://github.com/explosion/curated-transformers/pull/124) for the workaround this is based on. --- html/licenses.html | 26 ++++++++++++++++++++++++++ modules/mac_specific.py | 5 +++++ 2 files changed, 31 insertions(+) (limited to 'modules/mac_specific.py') diff --git a/html/licenses.html b/html/licenses.html index bddbf466..bc995aa0 100644 --- a/html/licenses.html +++ b/html/licenses.html @@ -635,4 +635,30 @@ SOFTWARE. WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. + + +

Curated transformers

+The MPS workaround for nn.Linear on macOS 13.2.X is based on the MPS workaround for nn.Linear created by danieldk for Curated transformers +
+The MIT License (MIT)
+
+Copyright (C) 2021 ExplosionAI GmbH
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
\ No newline at end of file diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 18e6ff72..3a170f60 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -1,4 +1,5 @@ import torch +import platform from modules import paths from modules.sd_hijack_utils import CondFunc from packaging import version @@ -32,6 +33,10 @@ if has_mps: # MPS fix for randn in torchsde CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'mps') + if platform.mac_ver()[0].startswith("13.2."): + # MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124) + CondFunc('torch.nn.functional.linear', lambda _, input, weight, bias: (torch.matmul(input, weight.t()) + bias) if bias is not None else torch.matmul(input, weight.t()), lambda _, input, weight, bias: input.numel() > 10485760) + if version.parse(torch.__version__) < version.parse("1.13"): # PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working -- cgit v1.2.3 From 27fe3eb6a9d8f866af8b90dff18f4445124702da Mon Sep 17 00:00:00 2001 From: brkirch Date: Fri, 24 Mar 2023 03:04:47 -0400 Subject: Add workaround for MPS layer_norm on PyTorch 2.0 On PyTorch 2.0, with MPS layer_norm only accepts float32 inputs. This was fixed shortly after 2.0 was finalized so the workaround can be applied with an exact version match. --- modules/mac_specific.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/mac_specific.py') diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 3a170f60..6fe8dea0 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -54,4 +54,6 @@ if has_mps: CondFunc('torch.cumsum', cumsum_fix_func, None) CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None) CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None) - + if version.parse(torch.__version__) == version.parse("2.0"): + # MPS workaround for https://github.com/pytorch/pytorch/issues/96113 + CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda *args, **kwargs: len(args) == 6) -- cgit v1.2.3