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| |
| |
|
|
| 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): |
| """ |
| 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": |
| """ |
| 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": |
| """ |
| 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: |
| |
| assert False |
|
|
| @classmethod |
| def from_dict(cls, dict: Dict[str, Any]) -> "ComponentDevice": |
| """ |
| 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 |
|
|