gather_from_sequence_parallel_region:是对_GatherFromSequenceParallelRegion类使用的封装,_GatherFromSequenceParallelRegion继承自torch.autograd.Function的自定义Function,在parallel并行前向进行all_gather操作,反向是梯度reduce_scatter输出。对应Pipeline Parallel Linear Layer中的g函数。 class _GatherFromSequenceParallelRe...
Megatron-LM NVIDIA Megatron-LM 是一个基于 PyTorch 的分布式训练框架,用来训练基于Transformer的大型语言模型。Megatron-LM 综合应用了数据并行(Data Parallelism),张量并行(Tensor Parallelism)和流水线并行(Pipeline Parallelism)。很多大模型的训练过程都采用它,例如bloom、opt、智源等。 torch.distributed(dist) 为运行...
2024/02/26 Update:tensor parallel 在主流的推理框架已经很好的支持了, vLLM 和 lightllm 都是很好的选择。现在 tensor-parallel 这个项目的意义主要在做一些实验上,真实场景下不再适用。 上一篇文章中我用 Al…
Tensor parallelism takes place at the level ofnn.Modules; it partitions specific modules in the model across tensor parallel ranks. This is in addition to the existing partition of theset of modulesused in pipeline parallelism. When a module is partitioned through tensor parallelism, its for...
Tensor parallelism is a type of model parallelism in which specific model weights, gradients, and optimizer states are split across devices. In contrast to pipeline parallelism, which keeps individual weights intact but partitions the set of weights, gradients, or optimizer across devices, tensor para...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Specifying device_id in init_process_group causes tensor parallel + pipeline parallel to fail · pytorch/pytorch@d765077
tensor_parallel_size=2, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), observability_config=ObservabilityConfig(...
Pytorch中设备管理是直接在 Tensor 对象中设置设备,而MindSpore 的设备管理是通过上下文来实现的,因此,x.device 并不是一个有效的属性,需要使用 ms.context 模块来管理设备上下文。 例如,Pytorch代码中: device_type = x.device.type device_type = device_type if isinstance(device_type, str) and device_type ...
Fig. 2: A Comprehensive Pipeline for Neural Data Analysis. A Tensor construction: High-dimensional neural signals collected are transformed into a tensor data structure. B Tensor decomposition, using Tucker decomposition as an example. C Tensor inner product: The tensor inner product is estimated by...
For example, and without limitation, illustrative types of hardware logic circuits that can be used include an FPGA device, an application-specific integrated circuit (ASIC) device, a GPU, a massively parallel processor array (MPPA) device, an application-specific standard product (ASSP) device, ...