update samples from Release-118 as a part of SDK release

how-to-use-azureml/machine-learning-pipelines/nyc-taxi-data-regression-model-building/scripts/prepdata/cleanse.py

@@ -5,6 +5,17 @@ import argparse
 import os
 from azureml.core import Run
 
+
+def get_dict(dict_str):
+    pairs = dict_str.strip("{}").split(r'\;')
+    new_dict = {}
+    for pair in pairs:
+        key, value = pair.strip().split(":")
+        new_dict[key.strip().strip("'")] = value.strip().strip("'")
+
+    return new_dict
+
+
 print("Cleans the input data")
 
 # Get the input green_taxi_data. To learn more about how to access dataset in your script, please
@@ -12,6 +23,7 @@ print("Cleans the input data")
 run = Run.get_context()
 raw_data = run.input_datasets["raw_data"]
 
+
 parser = argparse.ArgumentParser("cleanse")
 parser.add_argument("--output_cleanse", type=str, help="cleaned taxi data directory")
 parser.add_argument("--useful_columns", type=str, help="useful columns to keep")
@@ -26,8 +38,8 @@ print("Argument 3(output cleansed taxi data path): %s" % args.output_cleanse)
 # These functions ensure that null data is removed from the dataset,
 # which will help increase machine learning model accuracy.
 
-useful_columns = eval(args.useful_columns.replace(';', ','))
-columns = eval(args.columns.replace(';', ','))
+useful_columns = [s.strip().strip("'") for s in args.useful_columns.strip("[]").split(r'\;')]
+columns = get_dict(args.columns)
 
 new_df = (raw_data.to_pandas_dataframe()
           .dropna(how='all')

how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb

@@ -254,7 +254,6 @@
         "- conda-forge\n",
         "dependencies:\n",
         "- python=3.6.2\n",
-        "- pip=21.3.1\n",
         "- pip:\n",
         "  - azureml-defaults\n",
         "  - azureml-opendatasets\n",

how-to-use-azureml/ml-frameworks/keras/train-hyperparameter-tune-deploy-with-keras/train-hyperparameter-tune-deploy-with-keras.ipynb

@@ -431,7 +431,6 @@
         "- conda-forge\n",
         "dependencies:\n",
         "- python=3.6.2\n",
-        "- pip=21.3.1\n",
         "- pip:\n",
         "  - h5py<=2.10.0\n",
         "  - azureml-defaults\n",

how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/train-hyperparameter-tune-deploy-with-pytorch.ipynb

@@ -262,7 +262,6 @@
         "- conda-forge\n",
         "dependencies:\n",
         "- python=3.6.2\n",
-        "- pip=21.3.1\n",
         "- pip:\n",
         "  - azureml-defaults\n",
         "  - torch==1.6.0\n",