ivila commented on code in PR #173:
URL:
https://github.com/apache/incubator-teaclave-trustzone-sdk/pull/173#discussion_r1992899155
##########
examples/mnist-rs/README.md:
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+# MNIST-rs
+
+This demo project demonstrates how to train and perform inference in TEE.
+
+## Install the TAs
+
+There are two TAs in the project:
+
+| TA | UUID | Usage |
+| ---- | ---- | ---- |
+| Train | 1b5f5b74-e9cf-4e62-8c3e-7e41da6d76f6 | for training new Model|
+| Inference | ff09aa8a-fbb9-4734-ae8c-d7cd1a3f6744 | for performing reference|
+
+The `Train TA` consumes more memory than `Inference TA`.
+
+Make sure to install them before attempting to use any functions.
+
+## Running the Host
+
+There are three subcommands in the host:
+
+1. Train
+
+ Trains a new model and exports it to the given path.
+
+ ``` shell
+ cargo run -- train -o model.bin
+ ```
+
+ This subcommand downloads the MNIST dataset, trains a new model, and
outputs
+ the model to the given path.
+
+ For detailed usage, run: `cargo run -- train --help`.
+
+2. Infer
+
+ Loads a model from the given path, tests it with a given image, and prints
+ the inference result.
+
+ ```shell
+ # cargo run -- infer -m model.bin -b samples/7.bin -i samples/7.png
+ cargo run -- infer [-b ${binary_path} | -i ${image_path}]
+ ```
+
+ This subcommand loads the model the model from the given path and tests it
+ with the given binaries and images, and prints the inference results. For
+ convenience, you can use the sample binaries and images in the `samples`
+ folder.
+
+ For detailed usage, run: `cargo run -- infer --help`.
+
+3. Serve
+
+ Loads a model from the given path, starts a web server and serves it as an
+ API.
+
+ ```shell
+ cargo run -- serve -m model.bin
+ ```
+
+ This subcommand loads the model the model from the given path and starts a
+ web server to provide inference APIs.
+
+ **Available APIs**:
+
+ | Method | Endpoint | Body |
+ | ---- | ---- | ---- |
+ | POST | `/inference/image` | an image with dimensions 28x28 |
+ | POST | `/inference/binary` | a 784-byte binary |
+
+ You can test the server with the following commands:
+
+ ```shell
+ # Perform inference using an image
+ curl --data-binary "@./samples/7.png" http://localhost:3000/inference/image
+ # Perform inference using a binary file
+ curl --data-binary "@./samples/7.bin"
http://localhost:3000/inference/binary
+ ```
+
+ For detailed usage, run: `cargo run -- serve --help`.
+
+## Credits
+
+This demo project is inspired by the crates and examples from
+[tracel-ai/burn](https://github.com/tracel-ai/burn), including:
+
+1.
[crates/burn-no-std-tests](https://github.com/tracel-ai/burn/tree/v0.16.0/crates/burn-dataset)
+2.
[examples/custom-training-loop](https://github.com/tracel-ai/burn/tree/v0.16.0/examples/custom-training-loop)
+3.
[examples/mnist-inference-web](https://github.com/tracel-ai/burn/tree/v0.16.0/examples/mnist-inference-web)
Review Comment:
Update: add TODO in README.md under Credits section
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