Spaces:
Runtime error
Runtime error
File size: 6,230 Bytes
6a62ffb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import hashlib
import json
import subprocess
import tempfile
from typing import Hashable
try:
import pyarrow.plasma as plasma
PYARROW_AVAILABLE = True
except ImportError:
plasma = None
PYARROW_AVAILABLE = False
class PlasmaArray:
"""
Wrapper around numpy arrays that automatically moves the data to shared
memory upon serialization. This is particularly helpful when passing numpy
arrays through multiprocessing, so that data is not unnecessarily
duplicated or pickled.
"""
def __init__(self, array):
super().__init__()
self.array = array
self.disable = array.nbytes < 134217728 # disable for arrays <128MB
self.object_id = None
self.path = None
# variables with underscores shouldn't be pickled
self._client = None
self._server = None
self._server_tmp = None
self._plasma = None
@property
def plasma(self):
if self._plasma is None and not self.disable:
self._plasma = plasma
return self._plasma
def start_server(self):
if self.plasma is None or self._server is not None:
return
assert self.object_id is None
assert self.path is None
self._server_tmp = tempfile.NamedTemporaryFile()
self.path = self._server_tmp.name
self._server = subprocess.Popen(
["plasma_store", "-m", str(int(1.05 * self.array.nbytes)), "-s", self.path]
)
@property
def client(self):
if self._client is None:
assert self.path is not None
self._client = self.plasma.connect(self.path, num_retries=200)
return self._client
def __getstate__(self):
"""Called on pickle load"""
if self.plasma is None:
return self.__dict__
if self.object_id is None:
self.start_server()
self.object_id = self.client.put(self.array)
state = self.__dict__.copy()
del state["array"]
state["_client"] = None
state["_server"] = None
state["_server_tmp"] = None
state["_plasma"] = None
return state
def __setstate__(self, state):
"""Called on pickle save"""
self.__dict__.update(state)
if self.plasma is None:
return
self.array = self.client.get(self.object_id)
def __del__(self):
if self._server is not None:
self._server.kill()
self._server = None
self._server_tmp.close()
self._server_tmp = None
DEFAULT_PLASMA_PATH = "/tmp/plasma"
class PlasmaView:
"""Interface to write and read from shared memory. Whereas PlasmaArray writes to plasma on serialization,
PlasmaView writes to shared memory on instantiation."""
def __init__(self, array, split_path: str, hash_data: Hashable, plasma_path=None):
"""
Args:
array: numpy array to store. This can be read with ``PlasmaView().array``
split_path: the path whence the data was read, used for hashing
hash_data: other metadata about the array that can be used to create a unique key.
as of writing, the 3 callers in ``TokenBlockDataset`` use::
hash_data = ((block_size, document_sep_len, str(break_mode), len(dataset)), 0|1|2)
"""
assert PYARROW_AVAILABLE
assert split_path is not None
if plasma_path is None:
plasma_path = DEFAULT_PLASMA_PATH
self.path = plasma_path
self.split_path = split_path
self._client = None # Initialize lazily for pickle. plasma clients should not be deep copied or serialized.
self._n = None
self.object_id = self.get_object_id(self.split_path, hash_data)
try:
self.client.put(array, object_id=self.object_id)
except plasma.PlasmaObjectExists:
pass
@property
def client(self):
if self._client is None:
self._client = plasma.connect(self.path, num_retries=200)
return self._client
@property
def array(self):
"""Fetch a read only view of an np.array, stored in plasma."""
ret = self.client.get(self.object_id)
return ret
@staticmethod
def get_object_id(split_path: str, hash_data: Hashable):
"""Returns plasma.ObjectID from hashing split_path and object_num."""
hash = hashlib.blake2b(bytes(split_path, "utf-8"), digest_size=20)
harg = json.dumps(hash_data).encode("utf-8")
hash.update(harg)
return plasma.ObjectID(hash.digest())
def __getstate__(self):
"""Called on pickle save"""
self.disconnect()
state = self.__dict__.copy()
assert state["_client"] is None
assert "object_id" in state
return state
def __setstate__(self, state):
"""Called on pickle load"""
self.__dict__.update(state)
def __del__(self):
self.disconnect()
def disconnect(self):
if self._client is not None:
self._client.disconnect()
self._client = None
def __len__(self):
"""Save reads by caching len"""
if self._n is None:
self._n = len(self.array)
return self._n
GB100 = (1024**3) * 100
class PlasmaStore:
def __init__(self, path=DEFAULT_PLASMA_PATH, nbytes: int = GB100):
self.server = self.start(path, nbytes)
def __del__(self):
self.server.kill()
@staticmethod
def start(path=DEFAULT_PLASMA_PATH, nbytes: int = GB100) -> subprocess.Popen:
if not PYARROW_AVAILABLE:
raise ImportError("please run pip install pyarrow to use --use_plasma_view")
# best practice is to allocate more space than we need. The limitation seems to be the size of /dev/shm
_server = subprocess.Popen(["plasma_store", "-m", str(nbytes), "-s", path])
plasma.connect(path, num_retries=200) # If we can't connect we fail immediately
return _server
|