######### Changelog ######### 1.4.0 [Processor Linux SDK 6.2] =============================== **Added** #. Subgraph execution support. 1.3.3 [Processor Linux SDK 6.1] =============================== **Added** #. Added imagenet python example. #. Added MobileNet v2 support. #. Added environment variables to control pre-allocated network memory sizes. TIDL_{PARAM,NETWORK}_HEAP_SIZE_{DSP,EVE} **Changed** #. Trace data now also include dataQ/minValue/maxValue info. #. ssd_multibox example now can also run the whole netework on a single core. #. Shipped network binaries are in new file format, of size 484384 bytes. 1.3.0 [Processor Linux SDK 5.3] =============================== **Added** #. Added DSP support for MNIST example. **Changed** #. PSDK 5.3 and TIDL-API 1.3 use a slightly modified TIDL network binary format to support ONNX network import. TIDL-API 1.3, as well as tidl-viewer utility, can read both network formats before and after the change. Network binary in TIDL-API 1.2 and earlier is of size 483364 bytes, network binary in TIDL-API 1.3 is of size 484384 bytes. #. Improved performance of concat layer on C66x DSP. 1.2.2 [Processor Linux SDK 5.2] =============================== **Added** #. Updated API implementation to minimize TIDL API/OpenCL dispatch overhead using multiple execution contexts in the :term:`ExecutionObject`. Refer to :ref:`mnist-example` example for details. #. Execution Graph generation Enable a two phase approach to generating execution graphs. Use the following API function to enable timestamp generation: .. code:: cpp bool EnableTimeStamps(const std::string& file = "timestamp.log", size_t num_frames=32); The generated log file can be viewed by using the execution_graph.py script. Refer to :ref:`execution-graph` for details. #. Added Python 3 bindings for TIDL API. See the ``examples/pybind`` directory for examples of using the Python bindings. Set PYTHONPATH to the location of ``tidl.so``. .. code:: bash root@am57xx-evm:~# export PYTHONPATH=/home/root/tidl-api/tidl_api root@am57xx-evm:~# python3 >>> import tidl >>> help (tidl) **Removed** #. Configuration::enableInternalInput. Not used by the API. #. Execution::GetExecutionObjects(). Use Execution::operator[] and Execution::GetNumExecutionObjects() instead. See :ref:`examples` for usage. #. The timing methods for host execution in EOPs and EOs: * GetProcessTimeInMilliSeconds() * GetHostProcessTimeInMilliSeconds() These methods were replaced by a timestamp based approach because they were no longer accurate with multiple ExecutionObject contexts and pipelining. Refer to :ref:`execution-graph` for details. 1.1.0 [Processor Linux SDK 5.1] =============================== **Added** #. :term:`ExecutionObjectPipeline` class to hide complexity of executing network across C66x/EVE #. API methods for tracing outputs from intermediate network layers - see :ref:`network_layer_output`. #. Support for updating layer group id assignment before execution - see :ref:`layer-group-override`. #. Provide feedback to the user on parameter and network heap size requirements - see :ref:`sizing_device_heaps`. 1.0.0 [Processor Linux SDK 5.0] =============================== First release of the TI Deep Learning API. TIDL API brings deep learning to the edge by enabling applications to leverage TI's proprietary, highly optimized CNN/DNN implementation on the EVE and C66x DSP compute engines. TIDL will initially target Vision/2D use cases. **Supported AM57x Sitara Processors** * `AM5749`_ (offload to EVEs and C66x DSPs) * `AM571x`_ (offload to C66x DSPs) * `AM5728`_ (offload to C66x DSPs) * `AM5748`_ (offload to C66x DSPs) **Supported Evaluation Modules (EVMs)** * `AM574x IDK EVM`_ * `AM572x EVM`_ * `AM571x IDK EVM`_ .. _AM572x EVM: http://www.ti.com/tool/tmdsevm572x .. _AM571x IDK EVM: http://www.ti.com/tool/tmdxidk5718 .. _AM574x IDK EVM: http://www.ti.com/tool/tmdsidk574 .. _AM571x: http://www.ti.com/processors/sitara/arm-cortex-a15/am57x/products.html#p2098=1%20C66x&p809=2;2 .. _AM5728: http://www.ti.com/product/AM5728 .. _AM5748: http://www.ti.com/product/am5748 .. _AM5749: http://www.ti.com/product/am5749 .. _AM574x: http://www.ti.com/processors/sitara/arm-cortex-a15/am57x/products.html#p2098=2%20C66x&p815=ECC