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Are 17 granular commits needed? If not, please plan to squash them |
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| |__SDK_DOWNLOAD_URL__| | ||
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| Look for the file: ``tisdk-edgeai-image-am62dxx-evm.rootfs.wic.xz`` |
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Could you please go through all the comments on the draft PR and make sure they are addressed? Ideally, the same draft PR should have been opened for review, which would make it easier to verify that all comments have been handled.
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We had some changes which modified build.yml and deploy.yml file to run github actions on the fork (And the generated github.io link was shared amongst other members). Hence we created a separate PR with clean commits.
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| .. _edgeai-introduction: | ||
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| ######################## |
| At run time on the AM62D, the TVM runtime loads the artifact and dispatches the | ||
| offloaded subgraphs to TIDL-RT on the C7\ |trade| NPU. | ||
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| .. figure:: ../../../images/audioai/tvm_tidl_flow.svg |
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why relative path is required here?
/images/audioai/tvm_tidl_flow.svg should work I believe
cshilwant
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Please review all comments from the draft PR and ensure they are addressed in this PR. Several comments from the draft PR are still unresolved here.
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Squashed into a single commit |
cshilwant
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Run your commit by Claude against our CONTRIBUTING guide [0] to spot potential issues. Go through its findings, separate real non-compliance from false alarms, and fix what's actually broken.
[0] - https://github.com/TexasInstruments/processor-sdk-doc/blob/master/CONTRIBUTING.md
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| .. code-block:: bash | ||
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| sudo minicom -D /dev/ttyUSB1 -c on |
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Please highlight baudrate in command itself
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| host# ssh root@<EVM_IP_ADDRESS> | ||
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| If using Ubuntu 22.04, add the following to ``~/.ssh/config``: |
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use role file - https://www.sphinx-doc.org/en/master/usage/restructuredtext/roles.html#role-file
Note - this comment is not just for this section. Please update it for all such file & directory references in all such references in the PR
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I have addressed this as well. The role-file was missing in multiple files, thanks for identifying this issue.
| root@am62dxx-evm:~# git clone https://github.com/TexasInstruments/rpmsg-dma.git -b main | ||
| root@am62dxx-evm:~# cd rpmsg-dma | ||
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| The example is under ``example/edge-ai/`` and contains: |
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| * - GTCRN | ||
| - Speech enhancement (VoiceBank-DEMAND-16k) | ||
| - ``ase-0100`` | ||
| - Arm core (ONNX runtime, FP32) |
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is this correct that GTCRN runs entirely on Arm that too with ONNX-RT ?
@PrathamTI / @v-singh1
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Removed all the GTCRN references
| - BOOTMODE [8:15] (SW3) = 0100 0000 | ||
| - BOOTMODE [0:7] (SW2) = 1100 0010 | ||
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| .. figure:: /images/am62dx_boot_pin.png |
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Just for confirmation. I can see SW1 in the image (the board image displayed). Can you check if it is SW1? The other bootmode switch naming is also not clear
| a network, the web portal can be accessed from any device on the same network without | ||
| any additional setup. | ||
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| The portal showcases the three core EdgeAI pipelines — home screen, speech |
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home screen as EdgeAI pipeline?
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Removed this statement.
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Any release notes section planned to be added somewhere at the bottom? |
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| Connect the components to the AM62D EVM as shown below: | ||
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| .. figure:: /images/am62dx_board_config.png |
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In this image, there are 3 unmarked arrows (the arrows are pointing towards a component) without any labelling. Kindly mark some label and also the image is not clear
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Thanks for identifying this issue. @paresh-bhagat is working on adding the image with proper labels
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| For **Windows** use Tera Term: | ||
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| https://learn.sparkfun.com/tutorials/terminal-basics/tera-term-windows |
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Do we need this part since we haven't tested this for windows
| On-target measured latency and RTF for all four models are **TBD** - to be | ||
| filled in from the Model Zoo inference scripts on the AM62D EVM: | ||
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| .. list-table:: | ||
| :header-rows: 1 | ||
| :widths: 20 20 30 30 | ||
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| * - Model | ||
| - On target | ||
| - Measured latency | ||
| - RTF | ||
| * - VGGish11 | ||
| - C7\ |trade| NPU | ||
| - TBD | ||
| - - (clip classifier) | ||
| * - YAMNet | ||
| - C7\ |trade| NPU | ||
| - TBD | ||
| - - (clip classifier) | ||
| * - GCRN | ||
| - C7\ |trade| NPU | ||
| - TBD | ||
| - TBD | ||
| * - GTCRN | ||
| - Arm core |
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Small question. If its TBD do we need to mention this part in the docs? Also add the arm core GTCRN model if the section will be included
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Yes we will create a separate section for release notes, but its not planned as of yet. |
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Adds the full EdgeAI documentation set for AM62DX covering audio deep-learning inference (speech enhancement and audio classification) on the C7x DSP via TVM + TIDL. The guide spans platform overview, hardware setup, the out-of-box web GUI demo, the C++ inference application, GStreamer audio pipeline development, the model workflow (zoo, compile/evaluate, inspect), integrating a new model, and performance benchmarking. Co-authored-by: JuneChul Roh <jroh@ti.com> Co-authored-by: Paresh Bhagat <p-bhagat@ti.com> Signed-off-by: Pratham Deshmukh <p-deshmukh@ti.com>

This PR adds documentation for the AM62DX EdgeAI software stack — audio deep-learning inference (speech enhancement and audio classification) running on the C7x DSP via TVM .