add new files

tensile_origin.py

+# This is a sample Python script.
+
+# Press Shift+F10 to execute it or replace it with your code.
+# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
+
+import csv
+import os
+import pandas as pd
+import numpy as np
+import pandas as pd
+
+class tensileOriginfile():
+
+    def __init__(self, file):
+        self.file = file
+        self.TransA = []
+        self.TransB = []
+        self.M = []
+        self.N = []
+        self.B = []
+        self.K = []
+        self.ldd = []
+        self.ldc = []
+        self.lda = []
+        self.ldb = []
+        self.strideA = []
+        self.strideB = []
+        self.strideC = []
+        self.strideD = []
+        self.compute_type = []
+        self.api_type = []
+
+
+    def analyszie_file(self):
+        with open(self.file, 'r') as txt:
+            content = txt.readlines()
+            txt.close()
+        lines = np.array(content)
+        num_of_instances = lines.size
+        str_line = str()
+        for i in range(0, num_of_instances):
+            str_line = str(lines[i])
+            str_list = str_line.split()
+            print(str_list)
+            if "--transposeA" in str_list:
+                self.TransA.append(str_list[str_list.index("--transposeA")+1])
+                self.TransB.append(str_list[str_list.index("--transposeB") + 1])
+                self.api_type.append(str_list[str_list.index("-f") + 1])
+                self.M.append(str_list[str_list.index("-m") + 1])
+                self.N.append(str_list[str_list.index("-n") + 1])
+                if "--batch_count" in str_list:
+                    self.B.append(str_list[str_list.index("--batch_count") + 1])
+                else:
+                    self.B.append(str(1))
+                self.K.append(str_list[str_list.index("-k") + 1])
+                if "--ldd" in str_list:
+                    self.ldd.append(str_list[str_list.index("--ldd") + 1])
+                else:
+                    self.ldd.append(str_list[str_list.index("--ldc") + 1])
+                self.ldc.append(str_list[str_list.index("--ldc") + 1])
+                self.lda.append(str_list[str_list.index("--lda") + 1])
+                self.ldb.append(str_list[str_list.index("--ldb") + 1])
+                if "--compute_type" in str_list:
+                    self.compute_type.append(str_list[str_list.index("--compute_type") + 1])
+                else:
+                    self.compute_type.append("none")
+                if "--stride_a" in str_list:
+                    self.strideA.append(str_list[str_list.index("--stride_a") + 1])
+                else:
+                    self.strideA.append("1")
+                if "--stride_b" in str_list:
+                    self.strideB.append(str_list[str_list.index("--stride_b") + 1])
+                else:
+                    self.strideB.append("1")
+                if "--stride_c" in str_list:
+                    self.strideC.append(str_list[str_list.index("--stride_c") + 1])
+                else:
+                    self.strideC.append("1")
+                if "--stride_d" in str_list:
+                    self.strideD.append(str_list[str_list.index("--stride_d") + 1])
+                else:
+                    self.strideD.append("1")
+
+    def create_csv(self):
+        frame = pd.DataFrame({'TransA': self.TransA, 'TransB': self.TransB, 'api_type': self.api_type, 'M': self.M,
+                              'N': self.N, 'B': self.B, 'K': self.K, 'ldd': self.ldd, 'ldc': self.ldc,
+                              'lda': self.lda, 'ldb': self.ldb, 'compute_type': self.compute_type,
+                              'strideA': self.strideA, 'strideB': self.strideB, 'strideC': self.strideC,
+                              'strideD': self.strideD})
+
+        frame.to_csv("rocblas_extract.csv", index=False, sep=',')
+
+
+if __name__ == "__main__":
+    ts = tensileOriginfile("rocblas.log")
+    ts.analyszie_file()
+    ts.create_csv()
+
+
+    df = pd.read_csv('rocblas_extract.csv')
+    df = df.drop_duplicates()
+    df.to_csv('rocblas_extract_without_duplicates.csv', index=False)