# Using ITK with Dask - resolving issues due to Lazy Loading

**URL:** <https://discourse.itk.org/t/using-itk-with-dask-resolving-issues-due-to-lazy-loading/346>\
**Category:** Community\
**Tags:** dask, python\
**Created:** [October 20, 2017, 8:55pm UTC](https://discourse.itk.org/t/using-itk-with-dask-resolving-issues-due-to-lazy-loading/346 "2017-10-20T20:55:32Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![cdeepakroy](https://discourse.itk.org/user_avatar/discourse.itk.org/cdeepakroy/32/50_2.png) [@cdeepakroy](https://discourse.itk.org/u/cdeepakroy)\
**Post date:** [October 20, 2017, 8:55pm UTC](https://discourse.itk.org/t/using-itk-with-dask-resolving-issues-due-to-lazy-loading/346/1 "2017-10-20T20:55:32Z")

</div>

I was trying to use Dask to parallelize the application of a python function that uses ITK on multiple images, and encountered issues if LazyLoading is enabled.

Here is a code that replicates the error:

```auto
import os
import skimage.data
import skimage.io

import dask
import dask.distributed

import itk

# Instantiate a client to the dask cluster
scheduler = 'localhost:8786'
c = dask.distributed.Client(scheduler)
print c

# get and save sample image for testing
skimage.io.imsave('camera_man.jpg', skimage.data.camera())
fpath = os.path.abspath('camera_man.jpg')

# try parallelizing a function that uses itk.imread using Dask
result = []

def process(i):        
    im_itk = itk.imread(fpath)    
    time.sleep(0.2) # simulate some processing time
    return i
    
for i in range(1000):    
    result.append(dask.delayed(process)(i))
    
result = dask.delayed(result).compute()

```

This resulted in the following error:

> distributed.protocol.pickle - INFO - Failed to serialize \<function process at 0x7f4e4f98ab90\>. Exception: ‘LazyITKModule’ object has no attribute ‘ **package** ’

I managed to resolve this by disabling Lazy Loading before importing itk as shown below:

```auto
import os
import skimage.data
import skimage.io

import dask
import dask.distributed

# disable lazy loading first and then import itk
import itkConfig
itkConfig.LazyLoading = False
import itk

# Instantiate a client to the dask cluster
scheduler = 'localhost:8786'
c = dask.distributed.Client(scheduler)
print c

# get and save sample image for testing
skimage.io.imsave('camera_man.jpg', skimage.data.camera())
fpath = os.path.abspath('camera_man.jpg')

# try parallelizing a function that uses itk.imread using Dask
result = []

def process(i):        
    im_itk = itk.imread(fpath)    
    time.sleep(0.2) # simulate some processing time
    return i
    
for i in range(1000):    
    result.append(dask.delayed(process)(i))
    
result = dask.delayed(result).compute()

```

---

<div class="post-metadata">

**Author:** ![matt.mccormick](https://discourse.itk.org/user_avatar/discourse.itk.org/matt.mccormick/32/7_2.png) [@matt.mccormick](https://discourse.itk.org/u/matt.mccormick)\
**Post date:** [October 20, 2017, 9:16pm UTC](https://discourse.itk.org/t/using-itk-with-dask-resolving-issues-due-to-lazy-loading/346/2 "2017-10-20T21:16:54Z")

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@cdeepakroy Very cool! Thanks for sharing the workaround.