t3qai-client 1.1.5

t3qai client module

t3qai_client Description

a library for t3qai platform client.

The client module provides properties/functions that links platform and client's learning/Inference algorithm.

• Provide platform path properties
• Provides functions to link learning state, set log, call learning parameter elements, load data, save learning results, and download inference results

To install with pip

pip install t3qai_client

How to Use (Example)

properties

## train
from t3qai_client import T3QAI_TRAIN_OUTPUT_PATH, T3QAI_TRAIN_MODEL_PATH, T3QAI_TRAIN_DATA_PATH, T3QAI_TEST_DATA_PATH, T3QAI_MODULE_PATH

## inference
from t3qai_client import T3QAI_INIT_MODEL_PATH

functions

import t3qai_client as tc

## link learning state
tc.train_start()
tc.train_finish(result, result_msg)

## set log
# train
tc.train_set_logger()
# inference
tc.inference_set_logger()

## call learning parameter elements
# train
params = tc.train_load_param()
batch_size= int(params['batch_size'])
# inference
params = tc.inference_load_param()
batch_size= int(params['batch_size'])

## load data
# To use this function, the dataset with id and label must pass through the preprocessing module.
(train_id, train_x, train_y), (test_id, test_x, test_y) = tc.load_data()

## save learning results
# To draw charts inside the platform, use this function to save the learning results.
# save result (Loss, PCA 2D)
eval_results={}
eval_results['predict_y'] = [0, 1, 0]     # predict y
eval_results['actual_y'] = [[0], [1], [0]]  # actual y
eval_results['test_id'] = [0,1,2]        # test id(unique id)
eval_results['loss']=  float(0.3)        # loss
tc.train_save_result_metrics(eval_results)
# save classifacation result (Accuary, Loss, Confusion Matrix, Pricision/Recall//F1-score)
eval_results={}
eval_results['predict_y'] = [0, 1, 0]
eval_results['actual_y'] = [[0], [1], [0]]
eval_results['test_id'] = [0,1,2]
eval_results['loss'] =  float(0.3)
tc.train_save_classification_result(metrics)

## To download inference results at platform (2 options -> file_obj or file_path)
from t3qai_client import DownloadFile
result = DownloadFile(file_obj=resultobj, file_name=filename)
result = DownloadFile(file_path=save_path, file_name=filename)