mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
from __future__ import annotations
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from contextlib import nullcontext
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import torch
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from torch import autocast
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from ldm.invoke.globals import Globals
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CPU_DEVICE = torch.device("cpu")
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def choose_torch_device() -> torch.device:
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'''Convenience routine for guessing which GPU device to run model on'''
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if Globals.always_use_cpu:
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return CPU_DEVICE
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if torch.cuda.is_available():
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return torch.device('cuda')
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if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
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return torch.device('mps')
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return CPU_DEVICE
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def choose_precision(device: torch.device) -> str:
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'''Returns an appropriate precision for the given torch device'''
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if device.type == 'cuda':
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device_name = torch.cuda.get_device_name(device)
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if not ('GeForce GTX 1660' in device_name or 'GeForce GTX 1650' in device_name):
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return 'float16'
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return 'float32'
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def torch_dtype(device: torch.device) -> torch.dtype:
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if Globals.full_precision:
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return torch.float32
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if choose_precision(device) == 'float16':
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return torch.float16
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else:
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return torch.float32
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def choose_autocast(precision):
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'''Returns an autocast context or nullcontext for the given precision string'''
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# float16 currently requires autocast to avoid errors like:
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# 'expected scalar type Half but found Float'
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if precision == 'autocast' or precision == 'float16':
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return autocast
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return nullcontext
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def normalize_device(device: str | torch.device) -> torch.device:
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"""Ensure device has a device index defined, if appropriate."""
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device = torch.device(device)
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if device.index is None:
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# cuda might be the only torch backend that currently uses the device index?
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# I don't see anything like `current_device` for cpu or mps.
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if device.type == 'cuda':
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device = torch.device(device.type, torch.cuda.current_device())
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return device
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