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- Add four-tier testing architecture (inline, module, integration, system) - Implement comprehensive inline testing for Tensor, Activations, Layers, Networks modules - Create mock-based module testing approach to avoid dependency cascade - Add integration and system test directory structure - Update testing documentation with design principles and guidelines - Enhance educational testing with visual feedback and real ML scenarios - Total: 2,200+ lines of comprehensive testing across modules
6 lines
149 B
Python
6 lines
149 B
Python
"""
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Integration tests for TinyTorch.
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These tests verify that different modules work together correctly
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in realistic ML workflows and pipelines.
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""" |