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- pip wheel CI release integration
- DRAM legend redesign to better support long buffer list
- Tensor deallocation report in operation details (inputs/outputs only)
- Memory leaks in operation details (inputs/outputs only)
- CBs timeline view
- Allow multiple instances of visualizer to run simultaneously
- Annotate CBs on plot
- Clear demarcation of CBs vs tensors and improved CBs plot output
hinting
- Improved ssh connection related error messaging
- Improved UI for remote connection
- Backwards compatibility with old data format
- Fix for negative memory fragmentation records
- Fix for deallocation lookup logic
- Fix for ssh report list api generating 500
- Fix for L1 plot becoming randomly unresponsive
*[Expanding the ESLint configuration](#expanding-the-eslint-configuration)
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*[Environment ](#environment)
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*[Frontend](#frontend)
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*[Backend](#backend)
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*[Development](#development)
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+[Fix for python random errors not finding modules:](#fix-for-python-random-errors-not-finding-modules)
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+[Fix for missing distutils package](#fix-for-missing-distutils-package)
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*[Docker](#docker)
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+[Running project](#running-project)
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## Running Application
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### Installing as Wheel
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Download the wheel file from the [releases page](https://github.com/tenstorrent/ttnn-visualizer/releases) and install using `pip install release_name.whl`. After installation
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simply run `ttnn-visualizer` to start the application.
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### Downloading Docker Image
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Before executing the command below please see the note on SSH agent configuration.
@@ -189,9 +214,3 @@ To run the application you can simply run `docker-compose up web`. To rebuild ad
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To use the [provided SSH container](./docker/SSH/README.md) with the compose configuration you can substitute `web` in the above commands for `ssh`. To run the container in the background use `docker-compose up ssh -d`
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To connect to this container through the remote connection manager you use the name of the service (`ssh`) as the 'host' and the default SSH port 22.
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### Installing as Wheel
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Download the wheel file from the [releases page]() and install using `pip install release_name.whl`. After installation
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simply run `ttnn-visualizer` to start the application.
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