Issue with generic path

Hi, I am trying to profile a program. When I ran it with python3, the program could run smoothly. However, it failed when I tried to profile it. Here is my error message:

    Traceback (most recent call last):
      File "test.py", line 57, in <module>
        if not os.path.exists(filename):
      File "/home/yingj4/anaconda3/lib/python3.7/genericpath.py", line 19, in exists
        os.stat(path)
    TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType
    ==5317== Generated result file: /home/yingj4/Desktop/RITnetForFun/test.sql

Here is the code I tried to profile:

"""
Created on Mon Sep  2 11:37:59 2019

@author: aaa
"""
import torch
from dataset import IrisDataset
from torch.utils.data import DataLoader 
import numpy as np
import matplotlib.pyplot as plt
from dataset import transform
import os
from opt import parse_args
from models import model_dict
from tqdm import tqdm
from utils import get_predictions
#%%

"""
The new codes for profiling starts here

@author: Ying
"""

import torch.cuda.profiler as profiler
from apex import pyprof
pyprof.nvtx.init()

torch.autograd.profiler.emit_nvtx()

"""
The new codes for profiling ends here

@author: Ying
"""

if __name__ == '__main__':
    
    args = parse_args()
   
    if args.model not in model_dict:
        print ("Model not found !!!")
        print ("valid models are:",list(model_dict.keys()))
        exit(1)

    if args.useGPU:
        device=torch.device("cuda")
    else:
        device=torch.device("cpu")
        
    model = model_dict[args.model]
    model  = model.to(device)
    filename = args.load
    
    if not os.path.exists(filename):
        print("model path not found !!!")
        exit(1)
    
    
    model.load_state_dict(torch.load(filename))
    model = model.to(device)
    model.eval()

    test_set = IrisDataset(filepath = 'Semantic_Segmentation_Dataset/',\
                                 split = 'test',transform = transform)
    
    testloader = DataLoader(test_set, batch_size = args.bs,
                             shuffle=False, num_workers=2)
    counter=0
    
    os.makedirs('test/labels/',exist_ok=True)
    os.makedirs('test/output/',exist_ok=True)
    os.makedirs('test/mask/',exist_ok=True)
    
    with torch.no_grad():
        for i, batchdata in tqdm(enumerate(testloader),total=len(testloader)):
            img,labels,index,x,y= batchdata
            data = img.to(device)       
            output = model(data)            
            predict = get_predictions(output)
            for j in range (len(index)):       
                np.save('test/labels/{}.npy'.format(index[j]),predict[j].cpu().numpy())
                try:
                    plt.imsave('test/output/{}.jpg'.format(index[j]),255*labels[j].cpu().numpy())
                except:
                    pass
                
                pred_img = predict[j].cpu().numpy()/3.0
                inp = img[j].squeeze() * 0.5 + 0.5
                img_orig = np.clip(inp,0,1)
                img_orig = np.array(img_orig)
                combine = np.hstack([img_orig,pred_img])
                plt.imsave('test/mask/{}.jpg'.format(index[j]),combine)

    os.rename('test',args.save)

Here is the related code in genericpath.py:

Does a path exist?
This is false for dangling symbolic links on systems that support them.

def exists(path):
    """Test whether a path exists.  Returns False for broken symbolic links"""
    try:
        os.stat(path)
    except OSError:
        return False
    return True

Thank you!

Start at test.py line 57, where os.path.exists receives filename, and trace args.load back through parse_args. Compare the profiling setup using apex.pyprof and torch.autograd.profiler with the non-profiled run. Done means identifying whether Apex causes the None path or whether the reported failure is in the user's argument handling.