neuralmagic/deepsparse v1.2.0

DeepSparse v1.2.0

on GitHub

New Features:

• DeepSparse Engine Trial and Enterprise Editions now available, including license key activations.
• DeepSparse Pipelines document classification use case in NLP supported.

Changes:

• Mock engine tests added to enable faster and more precise unit tests in pipelines and Python code.
• DeepSparse Engine benchmarking updated to use time.perf_counter for more accurate benchmarks.
• Dynamic batch implemented to be more generic so it can support any pipeline.
• Minimum Python version changed to 3.7 as 3.6 reached EOL.

Performance:

• Performance improvements for unstructured sparse quantized convolutional neural networks implemented for throughput use cases.

Resolved Issues:

• In the C++ interface, the engine no longer crashes with a segmentation fault when the num_streams provided to the engine_context_t is greater than the number of physical CPU cores.
• The engine no longer crashes with assertion failures when running YOLOv4.
• YOLACT pipelines fixed where dynamic batch was not working and exported images had color channels improperly swapped.
• DeepSparse Server no longer crashes for hyphenated task names such as "question-answering."
• Computer vision pipelines now additionally accept single NumPy array inputs.
• Protobuf version for ONNX 1.12 compatibility pinned to prevent installation failures on some systems.

Known Issues:

• None