Back to Repositories

ColossalAI Testing: Distributed GPU Computing and Model Optimization Validation

The ColossalAI testing framework implements a comprehensive suite of unit tests using pytest, focusing on verifying critical distributed computing and model optimization functionalities. With 179 test cases, the framework thoroughly validates components like FP8 operations, bias additions, and distributed GPU communications, ensuring the reliability of ColossalAI's large-scale AI training capabilities. Qodo Tests Hub provides developers with detailed insights into ColossalAI's testing patterns, making it easier to understand how to implement robust tests for distributed AI systems. Through interactive exploration of real test implementations, developers can learn best practices for testing complex operations like model sharding, precision formats, and multi-GPU communications – essential knowledge for building reliable AI infrastructure.

Path	Test Type	Language	Description
tests/test_fx/test_parallel_1d.py	unit	python	This PyTest unit test verifies column-wise sharding of linear layers in distributed model execution using 1D tensor parallelism.
tests/test_fx/test_pipeline/test_hf_model/hf_utils.py	unit	python	This PyTorch unit test verifies the correct splitting and output consistency of HuggingFace models in ColossalAI’s model parallelism implementation.
tests/test_fx/test_tracer/test_hf_model/test_hf_albert.py	unit	python	This PyTest unit test verifies the compatibility and functionality of ALBERT models from Hugging Face within the ColossalAI framework.
tests/test_fx/test_pipeline/test_hf_model/test_opt.py	unit	python	This pytest unit test verifies the correct splitting and output comparison of OPT models in the ColossalAI framework.
tests/test_fx/test_pipeline/test_timm_model/test_timm.py	unit	python	This PyTest unit test verifies the splitting and output consistency of various TIMM model architectures in ColossalAI.
tests/test_fx/test_tracer/test_hf_model/test_hf_bert.py	unit	python	This pytest unit test verifies the tracing and output consistency of BERT models from Hugging Face Transformers in ColossalAI.
tests/test_fx/test_pipeline/test_timm_model/timm_utils.py	unit	python	This PyTorch unit test verifies model splitting functionality and output consistency in the ColossalAI framework using FX graph manipulation.
tests/test_fx/test_pipeline/test_torchvision/test_torchvision.py	unit	python	This PyTest unit test verifies the model splitting functionality across various TorchVision models in ColossalAI while maintaining output consistency.
tests/test_fx/test_pipeline_passes.py	unit	python	This PyTorch unit test verifies pipeline parallelism splitting strategies in ColossalAI by validating model output consistency across different splitting algorithms.
tests/test_fx/test_tracer/test_hf_model/test_hf_diffuser.py	unit	python	This pytest unit test verifies the correct symbolic tracing and execution of Hugging Face Diffuser models in ColossalAI.