| import os |
| import pandas as pd |
|
|
|
|
| def create_directory(primary_directory_name): |
| result_dir = f"{primary_directory_name}/results" |
| try: |
| os.mkdir(result_dir) |
| except FileExistsError: |
| print("Folder is Exist") |
|
|
| return result_dir |
|
|
|
|
| def creating_error_csv( |
| primary_directory_name, |
| learning_rate, |
| iteration_number, |
| round_number, |
| breakpoint_number, |
| ): |
| result_dir = create_directory(primary_directory_name) |
| overall_learning_rate_err_ = [] |
| for lr in learning_rate: |
| round_err_list = [] |
| round_percent_list = [] |
| round_validate_err_list = [] |
| round_validate_err_percent_list = [] |
| round_brakpoint_err_list = [] |
| round_brakpoint_err_percent_list = [] |
| round_brakpoint_val_err_list = [] |
| round_brakpoint_val_err_percent_list = [] |
| round_errors = [] |
| learning_rate_err_dict = {"learning_rate": str(lr)} |
| for round_no in range(round_number): |
| round_err_dict = {"learning_rate": str(lr)} |
| directory_name = primary_directory_name + "/round" + str(round_no + 1) |
| df = pd.read_csv(f"{directory_name}/{iteration_number}-{lr}.csv") |
| round_err_list.append(df["error"].values[-1]) |
| round_percent_list.append(df["error_percent"].values[-1]) |
| round_validate_err_list.append(df["validate_error"].values[-1]) |
| round_validate_err_percent_list.append( |
| df["validate_error_percent"].values[-1] |
| ) |
| breakpoint_df = df[df["epoch"] <= breakpoint_number] |
| round_brakpoint_err_list.append(breakpoint_df["error"].values[-1]) |
| round_brakpoint_err_percent_list.append( |
| breakpoint_df["error_percent"].values[-1] |
| ) |
| round_brakpoint_val_err_list.append( |
| breakpoint_df["validate_error"].values[-1] |
| ) |
| round_brakpoint_val_err_percent_list.append( |
| breakpoint_df["validate_error_percent"].values[-1] |
| ) |
|
|
| |
| round_err_dict[f"round"] = round_no |
| round_err_dict[f"error"] = df["error"].values[-1] |
| round_err_dict[f"error_percent"] = df["error_percent"].values[-1] |
| round_err_dict[f"validate_error"] = df["validate_error"].values[-1] |
| round_err_dict[f"validate_error_percent"] = df[ |
| "validate_error_percent" |
| ].values[-1] |
| round_err_dict[f"brakpoint_error"] = breakpoint_df["error"].values[-1] |
| round_err_dict[f"brakpoint_error_percent"] = breakpoint_df[ |
| "error_percent" |
| ].values[-1] |
| round_err_dict[f"brakpoint_validate_error"] = breakpoint_df[ |
| "validate_error" |
| ].values[-1] |
| round_err_dict[f"brakpoint_validate_error_percent"] = breakpoint_df[ |
| "validate_error_percent" |
| ].values[-1] |
| round_errors.append(round_err_dict) |
|
|
| round_err_df = pd.DataFrame(round_errors) |
| round_err_df.to_csv(f"{result_dir}/{lr}_round_error.csv", index=False) |
|
|
| average_error = round_err_df["error"].mean() |
| average_error_percent = round_err_df["error_percent"].mean() |
| average_validate_error = round_err_df["validate_error"].mean() |
| average_validate_error_percent = round_err_df["validate_error_percent"].mean() |
| average_brakpoint_error = round_err_df["brakpoint_error"].mean() |
| average_brakpoint_error_percent = round_err_df["brakpoint_error_percent"].mean() |
| average_brakpoint_validate_error = round_err_df[ |
| "brakpoint_validate_error" |
| ].mean() |
| average_brakpoint_validate_error_percent = round_err_df[ |
| "brakpoint_validate_error_percent" |
| ].mean() |
| learning_rate_err_dict["average_error"] = average_error |
| learning_rate_err_dict["average_error_percent"] = average_error_percent |
| learning_rate_err_dict["average_validate_error"] = average_validate_error |
| learning_rate_err_dict["average_validate_error_percent"] = ( |
| average_validate_error_percent |
| ) |
| learning_rate_err_dict["average_brakpoint_error"] = average_brakpoint_error |
| learning_rate_err_dict["average_brakpoint_error_percent"] = ( |
| average_brakpoint_error_percent |
| ) |
| learning_rate_err_dict["average_brakpoint_validate_error"] = ( |
| average_brakpoint_validate_error |
| ) |
| learning_rate_err_dict["average_brakpoint_validate_error_percent"] = ( |
| average_brakpoint_validate_error_percent |
| ) |
|
|
| overall_learning_rate_err_.append(learning_rate_err_dict) |
|
|
| overall_learning_rate_err_df = pd.DataFrame(overall_learning_rate_err_) |
| overall_learning_rate_err_df.to_csv( |
| f"{result_dir}/overall_learning_rate_err.csv", index=False |
| ) |
|
|
