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feat: skyrl-shm reasoning infrastructure integration
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parent
c20c85256e
commit
4f0acead3f
4 changed files with 351 additions and 19 deletions
143
atroposlib/api/shm_buffer.py
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143
atroposlib/api/shm_buffer.py
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import array
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import json
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import logging
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import mmap
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import os
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import struct
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from multiprocessing import shared_memory
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from typing import Any, Dict, List, Optional, Tuple, Union
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import numpy as np
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logger = logging.getLogger(__name__)
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class SHMBufferConfig:
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"""
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Control block for Shared Memory Buffer.
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Stored at the beginning of the SHM segment.
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"""
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# [Magic (4B) | Version (2B) | ReadIdx (4B) | WriteIdx (4B) | MaxSize (4B) | EntrySize (4B)]
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FORMAT = "4sHIIII"
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SIZE = struct.calcsize(FORMAT)
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MAGIC = b"ATRP"
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VERSION = 1
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class ZeroCopySHMBuffer:
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"""
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High-performance circular buffer using multiprocessing.shared_memory.
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Eliminates JSON serialization and HTTP overhead for trajectory transport.
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"""
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def __init__(
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self,
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name: str,
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size: int = 1000,
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entry_size: int = 4096, # Max tokens per trajectory
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create: bool = False,
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):
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self.name = name
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self.max_size = size
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self.entry_size = entry_size
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# Total size = Control Block + Data Segment
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self.total_size = SHMBufferConfig.SIZE + (size * entry_size * 4) # 4 bytes per int32 token
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try:
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if create:
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# Remove existing if any (OS-level cleanup)
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try:
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shm = shared_memory.SharedMemory(name=name)
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shm.unlink()
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except FileNotFoundError:
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pass
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self.shm = shared_memory.SharedMemory(name=name, create=True, size=self.total_size)
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self._init_control_block()
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logger.info(f"Created SHM buffer '{name}' with size {self.total_size} bytes")
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else:
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self.shm = shared_memory.SharedMemory(name=name)
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logger.debug(f"Attached to SHM buffer '{name}'")
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self.buf = self.shm.buf
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except Exception as e:
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logger.error(f"Failed to initialize SHM buffer: {e}")
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raise
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def _init_control_block(self):
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struct.pack_into(
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SHMBufferConfig.FORMAT,
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self.buf,
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0,
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SHMBufferConfig.MAGIC,
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SHMBufferConfig.VERSION,
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0, # ReadIdx
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0, # WriteIdx
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self.max_size,
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self.entry_size,
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)
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def _get_control(self) -> Tuple[int, int, int, int]:
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magic, version, read_idx, write_idx, max_size, entry_size = struct.unpack_from(
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SHMBufferConfig.FORMAT, self.buf, 0
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)
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if magic != SHMBufferConfig.MAGIC:
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raise ValueError("Invalid SHM Magic")
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return read_idx, write_idx, max_size, entry_size
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def _set_indices(self, read_idx: int, write_idx: int):
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# We only update these two fields
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struct.pack_into("II", self.buf, 6, read_idx, write_idx)
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def write_trajectory(self, tokens: List[int], score: float, metadata: Dict[str, Any] = None):
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"""
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Writes a trajectory to the buffer without any Python-side copies.
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"""
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read_idx, write_idx, max_size, entry_size = self._get_control()
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# Check for overflow
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next_write = (write_idx + 1) % max_size
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if next_write == read_idx:
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logger.warning("SHM Buffer Overflow! Dropping trajectory.")
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return False
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# Calculate offset in data segment
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offset = SHMBufferConfig.SIZE + (write_idx * entry_size * 4)
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# Zero-copy write using numpy view
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token_arr = np.array(tokens, dtype=np.int32)
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token_len = min(len(token_arr), entry_size)
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# View the SHM as a numpy array for the specific slot
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shm_slot = np.ndarray((entry_size,), dtype=np.int32, buffer=self.buf, offset=offset)
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shm_slot[:token_len] = token_arr[:token_len]
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if token_len < entry_size:
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shm_slot[token_len:] = 0 # Padding
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# Update write index
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self._set_indices(read_idx, next_write)
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return True
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def read_next(self) -> Optional[np.ndarray]:
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"""
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Reads the next available trajectory as a numpy view (no copy).
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"""
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read_idx, write_idx, max_size, entry_size = self._get_control()
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if read_idx == write_idx:
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return None # Buffer empty
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offset = SHMBufferConfig.SIZE + (read_idx * entry_size * 4)
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# Return a view of the memory
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data = np.ndarray((entry_size,), dtype=np.int32, buffer=self.buf, offset=offset)
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# Advance read index
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self._set_indices((read_idx + 1) % max_size, write_idx)
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return data
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def close(self, unlink: bool = False):
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self.shm.close()
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if unlink:
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self.shm.unlink()
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