From cc3f604310458eed7d26456c1b3934d582283ffe Mon Sep 17 00:00:00 2001 From: wangshuai09 <391746016@qq.com> Date: Wed, 31 Jan 2024 10:46:53 +0800 Subject: Update --- modules/devices.py | 7 +++++++ modules/initialize.py | 5 +---- modules/launch_utils.py | 8 ++++++++ modules/npu_specific.py | 5 +---- modules/textual_inversion/textual_inversion.py | 5 +---- 5 files changed, 18 insertions(+), 12 deletions(-) (limited to 'modules') diff --git a/modules/devices.py b/modules/devices.py index c737162a..28c0c54d 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -88,9 +88,16 @@ def torch_gc(): xpu_specific.torch_xpu_gc() if npu_specific.has_npu: + torch_npu_set_device() npu_specific.torch_npu_gc() +def torch_npu_set_device(): + # Work around due to bug in torch_npu, revert me after fixed, @see https://gitee.com/ascend/pytorch/issues/I8KECW?from=project-issue + if npu_specific.has_npu: + torch.npu.set_device(0) + + def enable_tf32(): if torch.cuda.is_available(): diff --git a/modules/initialize.py b/modules/initialize.py index cc34fd6f..f7313ff4 100644 --- a/modules/initialize.py +++ b/modules/initialize.py @@ -143,10 +143,7 @@ def initialize_rest(*, reload_script_modules=False): by that time, so we apply optimization again. """ from modules import devices - # Work around due to bug in torch_npu, revert me after fixed, @see https://gitee.com/ascend/pytorch/issues/I8KECW?from=project-issue - if devices.npu_specific.has_npu: - import torch - torch.npu.set_device(0) + devices.torch_npu_set_device() shared.sd_model # noqa: B018 diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 3ff4576a..107c72b0 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -338,6 +338,7 @@ def prepare_environment(): torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://pytorch-extension.intel.com/release-whl/stable/xpu/us/") torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.0.0a0 intel-extension-for-pytorch==2.0.110+gitba7f6c1 --extra-index-url {torch_index_url}") requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt") + requirements_file_for_npu = os.environ.get('REQS_FILE_FOR_NPU', "requirements_npu.txt") xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.23.post1') clip_package = os.environ.get('CLIP_PACKAGE', "https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip") @@ -421,6 +422,13 @@ def prepare_environment(): run_pip(f"install -r \"{requirements_file}\"", "requirements") startup_timer.record("install requirements") + if not os.path.isfile(requirements_file_for_npu): + requirements_file_for_npu = os.path.join(script_path, requirements_file_for_npu) + + if "torch_npu" in torch_command and not requirements_met(requirements_file_for_npu): + run_pip(f"install -r \"{requirements_file_for_npu}\"", "requirements_for_npu") + startup_timer.record("install requirements_for_npu") + if not args.skip_install: run_extensions_installers(settings_file=args.ui_settings_file) diff --git a/modules/npu_specific.py b/modules/npu_specific.py index d8aebf9c..94100691 100644 --- a/modules/npu_specific.py +++ b/modules/npu_specific.py @@ -8,11 +8,10 @@ def check_for_npu(): if importlib.util.find_spec("torch_npu") is None: return False import torch_npu - torch_npu.npu.set_device(0) try: # Will raise a RuntimeError if no NPU is found - _ = torch.npu.device_count() + _ = torch_npu.npu.device_count() return torch.npu.is_available() except RuntimeError: return False @@ -25,8 +24,6 @@ def get_npu_device_string(): def torch_npu_gc(): - # Work around due to bug in torch_npu, revert me after fixed, @see https://gitee.com/ascend/pytorch/issues/I8KECW?from=project-issue - torch.npu.set_device(0) with torch.npu.device(get_npu_device_string()): torch.npu.empty_cache() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index d16e3b9a..6d815c0b 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -150,10 +150,7 @@ class EmbeddingDatabase: return embedding def get_expected_shape(self): - # workaround - if devices.npu_specific.has_npu: - import torch - torch.npu.set_device(0) + devices.torch_npu_set_device() vec = shared.sd_model.cond_stage_model.encode_embedding_init_text(",", 1) return vec.shape[1] -- cgit v1.2.1