utils.py

# Copyright 2023 The vLLM team.
# Adapted from
# https://github.com/NVIDIA/Megatron-LM/blob/main/megatron/core/tensor_parallel/utils.py
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from typing import Sequence, Tuple

import torch

import vllm.envs as envs
from vllm.logger import init_logger

logger = init_logger(__name__)


def ensure_divisibility(numerator, denominator):
    """Ensure that numerator is divisible by the denominator."""
    assert numerator % denominator == 0, "{} is not divisible by {}".format(
        numerator, denominator)


def divide(numerator, denominator):
    """Ensure that numerator is divisible by the denominator and return
    the division value."""
    ensure_divisibility(numerator, denominator)
    return numerator // denominator


def split_tensor_along_last_dim(
    tensor: torch.Tensor,
    num_partitions: int,
    contiguous_split_chunks: bool = False,
) -> Sequence[torch.Tensor]:
    """ Split a tensor along its last dimension.

        Arguments:
            tensor: input tensor.
            num_partitions: number of partitions to split the tensor
            contiguous_split_chunks: If True, make each chunk contiguous
                                     in memory.

        Returns:
            A list of Tensors
    """
    # Get the size and dimension.
    last_dim = tensor.dim() - 1
    last_dim_size = divide(tensor.size()[last_dim], num_partitions)
    # Split.
    tensor_list = torch.split(tensor, last_dim_size, dim=last_dim)
    # NOTE: torch.split does not create contiguous tensors by default.
    if contiguous_split_chunks:
        return tuple(chunk.contiguous() for chunk in tensor_list)

    return tensor_list


def get_pp_indices(num_hidden_layers: int, pp_rank: int,
                   pp_size: int) -> Tuple[int, int]:
    """Try to evenly distribute layers across partitions.
    If the number of layers is not divisible by the number of partitions,
    the last partition will have the remaining layers.
    """
    partition_list_str = envs.VLLM_PP_LAYER_PARTITION
    if partition_list_str is not None:
        try:
            partitions = [
                int(layer) for layer in partition_list_str.split(",")
            ]
        except ValueError as err:
            raise ValueError("Invalid partition string: {}".format(
                partition_list_str)) from err
        if len(partitions) != pp_size:
            raise ValueError(f"{len(partitions)=} does not match {pp_size=}.")
        if sum(partitions) != num_hidden_layers:
            raise ValueError(
                f"{sum(partitions)=} does not match {num_hidden_layers=}.")
        start_layer = sum(partitions[:pp_rank])
        end_layer = start_layer + partitions[pp_rank]
    else:
        layers_per_partition = num_hidden_layers // pp_size
        start_layer = pp_rank * layers_per_partition
        end_layer = start_layer + layers_per_partition

        if pp_rank == pp_size - 1:
            end_layer = num_hidden_layers

    return (start_layer, end_layer)