Setting up Log Analysis and KVS stream with Deepracer for cloud on EC2

View of the model training.
model_logs_root = 'rl-deepracer-1/'
my_bucket ='deepracer-finlay-macrae'
import boto3
import os
def download_dir(client, resource, dist, local='/tmp', bucket='your_bucket'):
paginator = client.get_paginator('list_objects')
for result in paginator.paginate(Bucket=bucket, Delimiter='/', Prefix=dist):
if result.get('CommonPrefixes') is not None:
for subdir in result.get('CommonPrefixes'):
download_dir(client, resource, subdir.get('Prefix'), local, bucket)
for file in result.get('Contents', []):
dest_pathname = os.path.join(local, file.get('Key'))
if not os.path.exists(os.path.dirname(dest_pathname)):
if not file.get('Key').endswith('/'):
resource.meta.client.download_file(bucket, file.get('Key'), dest_pathname)

client = boto3.client('s3')
resource = boto3.resource('s3')
download_dir(client, resource, model_logs_root, '/workspace', bucket=my_bucket)
log = DeepRacerLog(model_logs_root)# load logs into a dataframe
except Exception:
print("Robomaker logs not available")
df = log.dataframe()




Virgin Money UK IT manager and AWS Deepracer Pro racer.

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Finlay Macrae

Finlay Macrae

Virgin Money UK IT manager and AWS Deepracer Pro racer.

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