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MIPLearn/miplearn/features/sample.py

101 lines
2.8 KiB

# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
from abc import ABC, abstractmethod
from typing import Dict, Optional, Any
import h5py
import numpy as np
from overrides import overrides
class Sample(ABC):
"""Abstract dictionary-like class that stores training data."""
@abstractmethod
def get(self, key: str) -> Optional[Any]:
pass
@abstractmethod
def put(self, key: str, value: Any) -> None:
"""
Add a new key/value pair to the sample. If the key already exists,
the previous value is silently replaced.
Only the following data types are supported:
- str, bool, int, float
- List[str], List[bool], List[int], List[float]
"""
pass
def _assert_supported(self, value: Any) -> None:
def _is_primitive(v: Any) -> bool:
if isinstance(v, (str, bool, int, float)):
return True
return False
if _is_primitive(value):
return
if isinstance(value, list):
if _is_primitive(value[0]):
return
assert False, f"Value has unsupported type: {value}"
class MemorySample(Sample):
"""Dictionary-like class that stores training data in-memory."""
def __init__(
self,
data: Optional[Dict[str, Any]] = None,
) -> None:
if data is None:
data = {}
self._data: Dict[str, Any] = data
@overrides
def get(self, key: str) -> Optional[Any]:
if key in self._data:
return self._data[key]
else:
return None
@overrides
def put(self, key: str, value: Any) -> None:
# self._assert_supported(value)
self._data[key] = value
class Hdf5Sample(Sample):
"""
Dictionary-like class that stores training data in an HDF5 file.
Unlike MemorySample, this class only loads to memory the parts of the data set that
are actually accessed, and therefore it is more scalable.
"""
def __init__(self, filename: str) -> None:
self.file = h5py.File(filename, "r+")
@overrides
def get(self, key: str) -> Optional[Any]:
ds = self.file[key]
if h5py.check_string_dtype(ds.dtype):
if ds.shape == ():
return ds.asstr()[()]
else:
return ds.asstr()[:].tolist()
else:
if ds.shape == ():
return ds[()].tolist()
else:
return ds[:].tolist()
@overrides
def put(self, key: str, value: Any) -> None:
self._assert_supported(value)
if key in self.file:
del self.file[key]
self.file.create_dataset(key, data=value)