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_auto_parallel/test_tensor_shard/test_node_handler/test_embedding_handler.py |
unit
|
python | This PyTest unit test verifies embedding handler implementations for both module-based and functional embedding operations in distributed environments using ColossalAI’s auto-parallel system. |
| tests/test_auto_parallel/test_tensor_shard/test_node_handler/test_getitem_handler.py |
unit
|
python | This PyTest unit test verifies GetItem handler functionality for tensor sharding strategies in ColossalAI’s auto-parallel system |
| tests/test_auto_parallel/test_tensor_shard/test_node_handler/test_layer_norm_handler.py |
unit
|
python | This PyTest unit test verifies LayerNorm module handler functionality in distributed tensor sharding operations for ColossalAI’s auto-parallel system. |
| tests/test_auto_parallel/test_tensor_shard/test_node_handler/test_linear_handler.py |
unit
|
python | This PyTest unit test verifies linear layer sharding strategies and tensor distributions in ColossalAI’s auto-parallel system. |
| tests/test_auto_parallel/test_tensor_shard/test_node_handler/test_matmul_handler.py |
unit
|
python | This PyTest unit test verifies matrix multiplication operations and sharding strategies in ColossalAI’s auto-parallel tensor system. |
| applications/ColossalQA/tests/test_document_loader.py |
unit
|
python | This Python unit test verifies document loading functionality and metadata handling in the ColossalQA DocumentLoader class. |
| tests/test_analyzer/test_subclasses/test_flop_tensor.py |
unit
|
python | This pytest unit test verifies FLOP counting accuracy for PyTorch modules and functions in ColossalAI’s analyzer component. |
| applications/ColossalQA/tests/test_retrieval_qa.py |
unit
|
python | This Python unit test verifies bilingual retrieval QA functionality in ColossalAI’s UniversalRetrievalConversation system for both English and Chinese queries. |
| colossalai/fx/passes/passes_for_gpt2_test.py |
unit
|
python | This PyTorch unit test verifies GPT-2 pipeline parallelism implementation through custom splitting and partition management in ColossalAI. |
| colossalai/testing/pytest_wrapper.py |
unit
|
python | This pytest unit test verifies environment-based conditional test execution through flag-controlled test skipping. |