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TensorFlow Adaptation
Fully compatible with the mainstream TensorFlow framework, enabling accelerated execution of TensorFlow networks on the Ascend platform.
Adaptation to Ascend AI Processors
Supports native TensorFlow Python APIs and extended Python APIs.
Core Framework Functions
Supports TensorFlow graph execution, optimization, and more.
Custom Operator Development
Allows adding custom operators within the TensorFlow framework.
Distributed Training
Supports parallel training of distributed data, including single-server multi-device and multi-server multi-device scenarios.
Mixed Precision
Supports the use of FP16 and FP32 together to improve performance while retaining accuracy.
Model Inference
Outputs standard TensorFlow PB models and converts them into offline inference models using ATC.
Development Scenarios
Model Script Adaptation
Perform simple adaptation on model scripts so that models can be trained on Ascend AI Processors.
Model Training
Use Ascend AI Processors to train models.
Operator Development
Develop and adapt custom operators based on Ascend AI Processors.
Development Resources
TensorFlow Model Library
Mainstream TensorFlow models pre-trained on Ascend AI Processors to allow you to deploy and train models quickly