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update samples from Release-96 as a part of SDK release

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amlrelsa-ms
2021-05-10 18:38:34 +00:00
parent 441a5b0141
commit eac6b69bae
117 changed files with 451 additions and 2252 deletions
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10
how-to-use-azureml/automated-machine-learning/classification-text-dnn/infer.py
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@@ -1,5 +1,6 @@
import argparse
import pandas as pd
import numpy as np
from sklearn.externals import joblib
@@ -32,22 +33,21 @@ model = joblib.load(model_path)
run = Run.get_context()
# get input dataset by name
test_dataset = run.input_datasets['test_data']
train_dataset = run.input_datasets['train_data']
X_test_df = test_dataset.drop_columns(columns=[target_column_name]) \
.to_pandas_dataframe()
y_test_df = test_dataset.with_timestamp_columns(None) \
.keep_columns(columns=[target_column_name]) \
.to_pandas_dataframe()
y_train_df = test_dataset.with_timestamp_columns(None) \
.keep_columns(columns=[target_column_name]) \
.to_pandas_dataframe()
predicted = model.predict_proba(X_test_df)
if isinstance(predicted, pd.DataFrame):
predicted = predicted.values
# Use the AutoML scoring module
class_labels = np.unique(np.concatenate((y_train_df.values, y_test_df.values)))
train_labels = model.classes_
class_labels = np.unique(np.concatenate((y_test_df.values, np.reshape(train_labels, (-1, 1)))))
classification_metrics = list(constants.CLASSIFICATION_SCALAR_SET)
scores = scoring.score_classification(y_test_df.values, predicted,
classification_metrics,