# SPDX-FileCopyrightText: 2022-present deepset GmbH # # SPDX-License-Identifier: Apache-2.0 import os from dataclasses import dataclass, field from enum import Enum from typing import Any, Dict, Optional, Tuple, Union from haystack import logging from haystack.lazy_imports import LazyImport logger = logging.getLogger(__name__) with LazyImport( message="PyTorch must be installed to use torch.device or use GPU support in HuggingFace transformers. " "Run 'pip install \"transformers[torch]\"'" ) as torch_import: import torch class DeviceType(Enum): """ Represents device types supported by Haystack. This also includes devices that are not directly used by models - for example, the disk device is exclusively used in device maps for frameworks that support offloading model weights to disk. """ CPU = "cpu" GPU = "cuda" DISK = "disk" MPS = "mps" def __str__(self): return self.value @staticmethod def from_str(string: str) -> "DeviceType": """ Create a device type from a string. :param string: The string to convert. :returns: The device type. """ mapping = {e.value: e for e in DeviceType} _type = mapping.get(string) if _type is None: raise ValueError(f"Unknown device type string '{string}'") return _type @dataclass class Device: """ A generic representation of a device. :param type: The device type. :param id: The optional device id. """ type: DeviceType id: Optional[int] = field(default=None) def __init__(self, type: DeviceType, id: Optional[int] = None): # noqa:A002 """ Create a generic device. :param type: The device type. :param id: The device id. """ if id is not None and id < 0: raise ValueError(f"Device id must be >= 0, got {id}") self.type = type self.id = id def __str__(self): if self.id is None: return str(self.type) else: return f"{self.type}:{self.id}" @staticmethod def cpu() -> "Device": """ Create a generic CPU device. :returns: The CPU device. """ return Device(DeviceType.CPU) @staticmethod def gpu(id: int = 0) -> "Device": # noqa:A002 """ Create a generic GPU device. :param id: The GPU id. :returns: The GPU device. """ return Device(DeviceType.GPU, id) @staticmethod def disk() -> "Device": """ Create a generic disk device. :returns: The disk device. """ return Device(DeviceType.DISK) @staticmethod def mps() -> "Device": """ Create a generic Apple Metal Performance Shader device. :returns: The MPS device. """ return Device(DeviceType.MPS) @staticmethod def from_str(string: str) -> "Device": """ Create a generic device from a string. :returns: The device. """ device_type_str, device_id = _split_device_string(string) return Device(DeviceType.from_str(device_type_str), device_id) @dataclass class DeviceMap: """ A generic mapping from strings to devices. The semantics of the strings are dependent on target framework. Primarily used to deploy HuggingFace models to multiple devices. :param mapping: Dictionary mapping strings to devices. """ mapping: Dict[str, Device] = field(default_factory=dict, hash=False) def __getitem__(self, key: str) -> Device: return self.mapping[key] def __setitem__(self, key: str, value: Device): self.mapping[key] = value def __contains__(self, key: str) -> bool: return key in self.mapping def __len__(self) -> int: return len(self.mapping) def __iter__(self): return iter(self.mapping.items()) def to_dict(self) -> Dict[str, str]: """ Serialize the mapping to a JSON-serializable dictionary. :returns: The serialized mapping. """ return {key: str(device) for key, device in self.mapping.items()} @property def first_device(self) -> Optional[Device]: """ Return the first device in the mapping, if any. :returns: The first device. """ if not self.mapping: return None else: return next(iter(self.mapping.values())) @staticmethod def from_dict(dict: Dict[str, str]) -> "DeviceMap": # noqa:A002 """ Create a generic device map from a JSON-serialized dictionary. :param dict: The serialized mapping. :returns: The generic device map. """ mapping = {} for key, device_str in dict.items(): mapping[key] = Device.from_str(device_str) return DeviceMap(mapping) @staticmethod def from_hf(hf_device_map: Dict[str, Union[int, str, "torch.device"]]) -> "DeviceMap": """ Create a generic device map from a HuggingFace device map. :param hf_device_map: The HuggingFace device map. :returns: The deserialized device map. """ mapping = {} for key, device in hf_device_map.items(): if isinstance(device, int): mapping[key] = Device(DeviceType.GPU, device) elif isinstance(device, str): device_type, device_id = _split_device_string(device) mapping[key] = Device(DeviceType.from_str(device_type), device_id) elif isinstance(device, torch.device): device_type = device.type device_id = device.index mapping[key] = Device(DeviceType.from_str(device_type), device_id) else: raise ValueError( f"Couldn't convert HuggingFace device map - unexpected device '{str(device)}' for '{key}'" ) return DeviceMap(mapping) @dataclass(frozen=True) class ComponentDevice: """ A representation of a device for a component. This can be either a single device or a device map. """ _single_device: Optional[Device] = field(default=None) _multiple_devices: Optional[DeviceMap] = field(default=None) @classmethod def from_str(cls, device_str: str) -> "ComponentDevice": """ Create a component device representation from a device string. The device string can only represent a single device. :param device_str: The device string. :returns: The component device representation. """ device = Device.from_str(device_str) return cls.from_single(device) @classmethod def from_single(cls, device: Device) -> "ComponentDevice": """ Create a component device representation from a single device. Disks cannot be used as single devices. :param device: The device. :returns: The component device representation. """ if device.type == DeviceType.DISK: raise ValueError("The disk device can only be used as a part of device maps") return cls(_single_device=device) @classmethod def from_multiple(cls, device_map: DeviceMap) -> "ComponentDevice": """ Create a component device representation from a device map. :param device_map: The device map. :returns: The component device representation. """ return cls(_multiple_devices=device_map) def _validate(self): """ Validate the component device representation. """ if not (self._single_device is not None) ^ (self._multiple_devices is not None): raise ValueError( "The component device can neither be empty nor contain both a single device and a device map" ) def to_torch(self) -> "torch.device": """ Convert the component device representation to PyTorch format. Device maps are not supported. :returns: The PyTorch device representation. """ self._validate() if self._single_device is None: raise ValueError("Only single devices can be converted to PyTorch format") torch_import.check() assert self._single_device is not None return torch.device(str(self._single_device)) def to_torch_str(self) -> str: """ Convert the component device representation to PyTorch string format. Device maps are not supported. :returns: The PyTorch device string representation. """ self._validate() if self._single_device is None: raise ValueError("Only single devices can be converted to PyTorch format") assert self._single_device is not None return str(self._single_device) def to_spacy(self) -> int: """ Convert the component device representation to spaCy format. Device maps are not supported. :returns: The spaCy device representation. """ self._validate() if self._single_device is None: raise ValueError("Only single devices can be converted to spaCy format") assert self._single_device is not None if self._single_device.type == DeviceType.GPU: assert self._single_device.id is not None return self._single_device.id else: return -1 def to_hf(self) -> Union[Union[int, str], Dict[str, Union[int, str]]]: """ Convert the component device representation to HuggingFace format. :returns: The HuggingFace device representation. """ self._validate() def convert_device(device: Device, *, gpu_id_only: bool = False) -> Union[int, str]: if gpu_id_only and device.type == DeviceType.GPU: assert device.id is not None return device.id else: return str(device) if self._single_device is not None: return convert_device(self._single_device) assert self._multiple_devices is not None return {key: convert_device(device, gpu_id_only=True) for key, device in self._multiple_devices.mapping.items()} def update_hf_kwargs(self, hf_kwargs: Dict[str, Any], *, overwrite: bool) -> Dict[str, Any]: """ Convert the component device representation to HuggingFace format. Add them as canonical keyword arguments to the keyword arguments dictionary. :param hf_kwargs: The HuggingFace keyword arguments dictionary. :param overwrite: Whether to overwrite existing device arguments. :returns: The HuggingFace keyword arguments dictionary. """ self._validate() if not overwrite and any(x in hf_kwargs for x in ("device", "device_map")): return hf_kwargs converted = self.to_hf() key = "device_map" if self.has_multiple_devices else "device" hf_kwargs[key] = converted return hf_kwargs @property def has_multiple_devices(self) -> bool: """ Whether this component device representation contains multiple devices. """ self._validate() return self._multiple_devices is not None @property def first_device(self) -> Optional["ComponentDevice"]: """ Return either the single device or the first device in the device map, if any. :returns: The first device. """ self._validate() if self._single_device is not None: return self.from_single(self._single_device) assert self._multiple_devices is not None assert self._multiple_devices.first_device is not None return self.from_single(self._multiple_devices.first_device) @staticmethod def resolve_device(device: Optional["ComponentDevice"] = None) -> "ComponentDevice": """ Select a device for a component. If a device is specified, it's used. Otherwise, the default device is used. :param device: The provided device, if any. :returns: The resolved device. """ if not isinstance(device, ComponentDevice) and device is not None: raise ValueError( f"Invalid component device type '{type(device).__name__}'. Must either be None or ComponentDevice." ) if device is None: device = ComponentDevice.from_single(_get_default_device()) return device def to_dict(self) -> Dict[str, Any]: """ Convert the component device representation to a JSON-serializable dictionary. :returns: The dictionary representation. """ if self._single_device is not None: return {"type": "single", "device": str(self._single_device)} elif self._multiple_devices is not None: return {"type": "multiple", "device_map": self._multiple_devices.to_dict()} else: # Unreachable assert False @classmethod def from_dict(cls, dict: Dict[str, Any]) -> "ComponentDevice": # noqa:A002 """ Create a component device representation from a JSON-serialized dictionary. :param dict: The serialized representation. :returns: The deserialized component device. """ if dict["type"] == "single": return cls.from_str(dict["device"]) elif dict["type"] == "multiple": return cls.from_multiple(DeviceMap.from_dict(dict["device_map"])) else: raise ValueError(f"Unknown component device type '{dict['type']}' in serialized data") def _get_default_device() -> Device: """ Return the default device for Haystack. Precedence: GPU > MPS > CPU. If PyTorch is not installed, only CPU is available. :returns: The default device. """ try: torch_import.check() has_mps = ( hasattr(torch.backends, "mps") and torch.backends.mps.is_available() and os.getenv("HAYSTACK_MPS_ENABLED", "true") != "false" ) has_cuda = torch.cuda.is_available() except ImportError: has_mps = False has_cuda = False if has_cuda: return Device.gpu() elif has_mps: return Device.mps() else: return Device.cpu() def _split_device_string(string: str) -> Tuple[str, Optional[int]]: """ Split a device string into device type and device id. :param string: The device string to split. :returns: The device type and device id, if any. """ if ":" in string: device_type, device_id_str = string.split(":") try: device_id = int(device_id_str) except ValueError: raise ValueError(f"Device id must be an integer, got {device_id_str}") else: device_type = string device_id = None return device_type, device_id