Merge pull request #12526 from brkirch/mps-adjust-sub-quad

Fixes for `git checkout`, MPS/macOS fixes and optimizations

6 files changed, 17 insertions, 12 deletions

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 94b2322a..449a8755 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -173,6 +173,9 @@ def git_clone(url, dir, name, commithash=None):
         if current_hash == commithash:

             return

 

+        if run_git(dir, name, 'config --get remote.origin.url', None, f"Couldn't determine {name}'s origin URL", live=False).strip() != url:

+            run_git(dir, name, f'remote set-url origin "{url}"', None, f"Failed to set {name}'s origin URL", live=False)

+

         run_git(dir, name, 'fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)

 

         run_git(dir, name, f'checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)

diff --git a/modules/mac_specific.py b/modules/mac_specific.py
index bce527cc..89256c5b 100644
--- a/modules/mac_specific.py
+++ b/modules/mac_specific.py
@@ -52,9 +52,6 @@ def cumsum_fix(input, cumsum_func, *args, **kwargs):
 
 
 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)
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 0e810eec..7f9e328d 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,6 +1,7 @@
 from __future__ import annotations

 import math

 import psutil

+import platform

 

 import torch

 from torch import einsum

@@ -94,7 +95,10 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem):
 class SdOptimizationSubQuad(SdOptimization):

     name = "sub-quadratic"

     cmd_opt = "opt_sub_quad_attention"

-    priority = 10

+

+    @property

+    def priority(self):

+        return 1000 if shared.device.type == 'mps' else 10

 

     def apply(self):

         ldm.modules.attention.CrossAttention.forward = sub_quad_attention_forward

@@ -120,7 +124,7 @@ class SdOptimizationInvokeAI(SdOptimization):
 

     @property

     def priority(self):

-        return 1000 if not torch.cuda.is_available() else 10

+        return 1000 if shared.device.type != 'mps' and not torch.cuda.is_available() else 10

 

     def apply(self):

         ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_invokeAI

@@ -427,7 +431,10 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_
     qk_matmul_size_bytes = batch_x_heads * bytes_per_token * q_tokens * k_tokens

 

     if chunk_threshold is None:

-        chunk_threshold_bytes = int(get_available_vram() * 0.9) if q.device.type == 'mps' else int(get_available_vram() * 0.7)

+        if q.device.type == 'mps':

+            chunk_threshold_bytes = 268435456 * (2 if platform.processor() == 'i386' else bytes_per_token)

+        else:

+            chunk_threshold_bytes = int(get_available_vram() * 0.7)

     elif chunk_threshold == 0:

         chunk_threshold_bytes = None

     else:

diff --git a/modules/sd_samplers_timesteps_impl.py b/modules/sd_samplers_timesteps_impl.py
index 48d7e649..d32e3521 100644
--- a/modules/sd_samplers_timesteps_impl.py
+++ b/modules/sd_samplers_timesteps_impl.py
@@ -11,7 +11,7 @@ from modules.models.diffusion.uni_pc import uni_pc
 def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta=0.0):

     alphas_cumprod = model.inner_model.inner_model.alphas_cumprod

     alphas = alphas_cumprod[timesteps]

-    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64)

+    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)

     sqrt_one_minus_alphas = torch.sqrt(1 - alphas)

     sigmas = eta * np.sqrt((1 - alphas_prev.cpu().numpy()) / (1 - alphas.cpu()) * (1 - alphas.cpu() / alphas_prev.cpu().numpy()))

 

@@ -42,7 +42,7 @@ def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta=
 def plms(model, x, timesteps, extra_args=None, callback=None, disable=None):

     alphas_cumprod = model.inner_model.inner_model.alphas_cumprod

     alphas = alphas_cumprod[timesteps]

-    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64)

+    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)

     sqrt_one_minus_alphas = torch.sqrt(1 - alphas)

 

     extra_args = {} if extra_args is None else extra_args

diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py
index 497568eb..ae4ee4bb 100644
--- a/modules/sub_quadratic_attention.py
+++ b/modules/sub_quadratic_attention.py
@@ -58,7 +58,7 @@ def _summarize_chunk(
     scale: float,
 ) -> AttnChunk:
     attn_weights = torch.baddbmm(
-        torch.empty(1, 1, 1, device=query.device, dtype=query.dtype),
+        torch.zeros(1, 1, 1, device=query.device, dtype=query.dtype),
         query,
         key.transpose(1,2),
         alpha=scale,
@@ -121,7 +121,7 @@ def _get_attention_scores_no_kv_chunking(
     scale: float,
 ) -> Tensor:
     attn_scores = torch.baddbmm(
-        torch.empty(1, 1, 1, device=query.device, dtype=query.dtype),
+        torch.zeros(1, 1, 1, device=query.device, dtype=query.dtype),
         query,
         key.transpose(1,2),
         alpha=scale,
diff --git a/webui-macos-env.sh b/webui-macos-env.sh
index 6354e73b..24bc5c42 100644
--- a/webui-macos-env.sh
+++ b/webui-macos-env.sh
@@ -12,8 +12,6 @@ fi
 export install_dir="$HOME"
 export COMMANDLINE_ARGS="--skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate"
 export TORCH_COMMAND="pip install torch==2.0.1 torchvision==0.15.2"
-export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git"
-export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71"
 export PYTORCH_ENABLE_MPS_FALLBACK=1
 
 ####################################################################