import boto3, sagemaker | |
import pandas as pd | |
smrt = boto3.client('sagemaker-runtime') | |
sess = sagemaker.Session() | |
df = pd.read_csv('mnist/test.csv', chunksize=1000) | |
results_sub = [] | |
counter = 0 | |
for chunk in df: | |
payload = chunk.to_csv(header=False, index=False) | |
response = smrt.invoke_endpoint( | |
EndpointName="mnist-endopoint-1", | |
Body=payload.encode('utf8'), | |
ContentType='text/csv' | |
) | |
results = response['Body'].read().decode('utf-8') | |
results_final = list(map(lambda x: x, results.split('\n'))) | |
results_sub += [y for y in results_final if y] | |
counter += chunk.shape[0] | |
print(f'Predicted {counter}') | |
results_final_submition = list(zip(range(1, len(results_sub) + 1), results_sub)) | |
submitions = pd.DataFrame(results_final_submition) | |
submitions.columns = ['ImageId', 'Label'] | |
submitions.to_csv('kaggle_submission.csv', index=False) | |
# sess.delete_endpoint(endpoint_name="mnist-endopoint-1") |
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