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Preparing

Get the model file:

wget https://github.com/alexeygrigorev/mlbookcamp-code/releases/download/chapter7-model/xception_v4_large_08_0.894.h5

Covert it:

python convert.py

Build the image:

docker build -t tf-lite-lambda .

Running locally

To run locally

docker run --rm -p 8080:8080 tf-lite-lambda

Test it

python test.py

Publishing

Create an ECR repo:

aws ecr create-repository --repository-name lambda-images

Login to Docker:

$(aws ecr get-login --no-include-email)

Publish the image:

REGION=eu-west-1
ACCOUNT=XXXXXXXXXXXX
REMOTE_NAME=${ACCOUNT}.dkr.ecr.${REGION}.amazonaws.com/lambda-images:tf-lite-lambda 
docker tag tf-lite-lambda ${REMOTE_NAME}
docker push ${REMOTE_NAME}

Create a lambda function

  • Go to Lambda, create a new function, select "container image"
  • Put the image we just created there
  • Go to basic settings and adjust timeout (30 sec) and memory (1GB)
  • Test it with the following payload:
{
    "url": "http://bit.ly/mlbookcamp-pants"
}

Deploying

To deploy it with AWS Lambda and API Gateway, follow this tutorial: https://github.com/alexeygrigorev/aws-lambda-docker/blob/main/guide.md