[CI] Add Pylint gitaction for gitaction ci

Add pylint yml file for python lint
- we move to gitaction from TAOS CI
- using pylint file from tensorflow gitaction
    - ref : https://github.com/tensorflow/tensorflow/blob/master/.github/workflows/pylint-presubmit.yml
- and for test : fix python file's format

**Changes proposed in this PR:**
- pylint.yml

**Self evaluation:**
1. Build test:	 [X]Passed [ ]Failed [ ]Skipped
2. Run test:	 [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghak PARK <[email protected]>

.github/workflows/pylint.yml

@@ -0,0 +1,50 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+name: PyLint
+on:
+  pull_request:
+    paths:
+      - '**.py'
+
+permissions:
+  contents: read
+
+jobs:
+  build:
+    name: PyLint
+    runs-on: ubuntu-latest
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+    - name: Get file changes
+      id: get_file_changes
+      uses: trilom/[email protected]
+      with:
+        output: ' '
+    - name: Report list of changed files
+      run: |
+        echo Changed files: ${{ steps.get_file_changes.outputs.files }}
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v5
+      with:
+        python-version: "3.10"
+    - name: Install Python dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pylint==3.0.2 numpy wheel
+    - name: Run PyLint on changed files
+      run: |
+        echo "${{ steps.get_file_changes.outputs.files}}" | tr " " "\n" | grep ".py$" | xargs pylint 

Applications/VGG/Tensorflow/dataset.py

@@ -1,37 +1,52 @@
-#!/usr/bin/env python
-# SPDX-License-Identifier: Apache-2.0
-#
-# Copyright (C) 2020 Jijoong Moon <[email protected]>
-#
-# @file	  dataset.py
-# @date	  15 July 2020
-# @brief  This is for mnist input generation
-# @see    https://github.com/nnstreamer/nntrainer
-# @author Jijoong Moon <[email protected]>
-# @bug    No known bugs except for NYI items
-#
-#
+"""
+SPDX-License-Identifier: Apache-2.0
+
+Copyright (C) 2020 Jijoong Moon <[email protected]>
+
+@file   dataset.py
+@date   15 July 2020
+@brief  This is for mnist input generation
+@see    https://github.com/nnstreamer/nntrainer
+@author Jijoong Moon <[email protected]>
+@bug    No known bugs except for NYI items
+"""
+
 
 import struct
-import os
 import numpy as np
 
-TOTAL_TRAIN_DATA_SIZE=100
-TOTAL_LABEL_SIZE=100
-TOTAL_VAL_DATA_SIZE=20
+TOTAL_TRAIN_DATA_SIZE = 100
+TOTAL_LABEL_SIZE = 100
+TOTAL_VAL_DATA_SIZE = 20
 FEATURE_SIZE = 3072
 
-def get_data_info(target):
+
+def get_data_info():
+    """Return Data size
+
+    Returns:
+        t_data_size, v_data_size, TOTAL_LABEL_SIZE, FEATURE_SIZE
+    """
     t_data_size = TOTAL_TRAIN_DATA_SIZE
     v_data_size = TOTAL_VAL_DATA_SIZE
     return t_data_size, v_data_size, TOTAL_LABEL_SIZE, FEATURE_SIZE
 
 ##
 # @brief load input data from file
 # @return (InputVector, InputLabel, Validation Vector, ValidationLabel)
+
+
 def load_data(target):
+    """Load data && save as file
+
+    Args:
+        target (str): train || validation
+
+    Returns:
+        input_vector, input_label, val_vector, val_label
+    """
     # data_size = TOTAL_TRAIN_DATA_SIZE;
-    d_size = get_data_info(target)
+    d_size = get_data_info()
 
     if target == "validation":
         t_buf_size = d_size[0]
@@ -40,33 +55,33 @@ def load_data(target):
         t_buf_size = d_size[0]*TOTAL_LABEL_SIZE
         v_buf_size = d_size[1]*TOTAL_LABEL_SIZE
 
-    InputVector = np.zeros((t_buf_size, FEATURE_SIZE),dtype=np.float32)
-    InputLabel = np.zeros((t_buf_size, TOTAL_LABEL_SIZE),dtype=np.float32)
+    input_vector = np.zeros((t_buf_size, FEATURE_SIZE), dtype=np.float32)
+    input_label = np.zeros((t_buf_size, TOTAL_LABEL_SIZE), dtype=np.float32)
 
-    ValVector = np.zeros((v_buf_size,FEATURE_SIZE),dtype=np.float32)
-    ValLabel = np.zeros((v_buf_size, TOTAL_LABEL_SIZE),dtype=np.float32)
+    val_vector = np.zeros((v_buf_size, FEATURE_SIZE), dtype=np.float32)
+    val_label = np.zeros((v_buf_size, TOTAL_LABEL_SIZE), dtype=np.float32)
 
-    #read Input & Label
+    # read Input & Label
 
-    fin = open('vgg_valSet.dat','rb')
-    for i in range(v_buf_size):
-        for j in range(FEATURE_SIZE):
-            data_str = fin.read(4)
-            ValVector[i,j] = struct.unpack('f',data_str)[0]
-        for j in range(TOTAL_LABEL_SIZE):
-            data_str = fin.read(4)
-            ValLabel[i,j] = struct.unpack('f',data_str)[0]
-    fin.close()
+    with open('vgg_valSet.dat', 'rb') as fin:
+        for i in range(v_buf_size):
+            for j in range(FEATURE_SIZE):
+                data_str = fin.read(4)
+                val_vector[i, j] = struct.unpack('f', data_str)[0]
+            for j in range(TOTAL_LABEL_SIZE):
+                data_str = fin.read(4)
+                val_label[i, j] = struct.unpack('f', data_str)[0]
+        fin.close()
 
     # we are using same training data for validation to check how internal implementation is working
-    fin=open('vgg_trainingSet.dat','rb')
-    for i in range(t_buf_size):
-        for j in range(FEATURE_SIZE):
-            data_str = fin.read(4)
-            InputVector[i,j] = struct.unpack('f',data_str)[0]
-        for j in range(TOTAL_LABEL_SIZE):
-            data_str = fin.read(4)
-            InputLabel[i,j] = struct.unpack('f',data_str)[0]
-    fin.close()
-
-    return InputVector, InputLabel, ValVector, ValLabel
+    with open('vgg_trainingSet.dat', 'rb') as fin:
+        for i in range(t_buf_size):
+            for j in range(FEATURE_SIZE):
+                data_str = fin.read(4)
+                input_vector[i, j] = struct.unpack('f', data_str)[0]
+            for j in range(TOTAL_LABEL_SIZE):
+                data_str = fin.read(4)
+                input_label[i, j] = struct.unpack('f', data_str)[0]
+        fin.close()
+
+    return input_vector, input_label, val_vector, val_label