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Steven Silvester
782ba46a4c
Punt on the issue of warnings with the minimum build Handle warnings in measure pkg Fix the rank filter test by forcing a random seed in the function Compare as boolean in imread test Import loadmat in test_setup to avoid warning Use a setup method for imread plugin test Revoke unintended changes Fix indentation to appease jni More indentation fixes Fix unintentional comment out
62 lines
1.8 KiB
Plaintext
Executable File
62 lines
1.8 KiB
Plaintext
Executable File
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How to parallelize loops
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In image processing, we frequently apply the same algorithm
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on a large batch of images. Here is an example:
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.. code-block:: python
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from skimage import data, color, util
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from skimage.restoration import denoise_tv_chambolle
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from skimage.feature import hog
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def task(image):
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"""
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Apply some functions and return an image.
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"""
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image = denoise_tv_chambolle(image[0][0], weight=0.1, multichannel=True)
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fd, hog_image = hog(color.rgb2gray(image), orientations=8,
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pixels_per_cell=(16, 16), cells_per_block=(1, 1),
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visualise=True)
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return hog_image
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# Prepare images
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hubble = data.hubble_deep_field()
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width = 10
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pics = util.view_as_windows(hubble, (width, hubble.shape[1], hubble.shape[2]), step=width)
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To call the function ``task`` on each element of the list ``pics``, it is
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usual to write a for loop. To measure the execution time of this loop, you can
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use ipython and measure the execution time with ``%timeit``.
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.. code-block:: python
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def classic_loop():
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for image in pics:
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task(image)
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%timeit classic_loop()
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Another equivalent way to code this loop is to use a comprehension list which has the same efficiency.
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.. code-block:: python
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def comprehension_loop():
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[task(image) for image in pics]
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%timeit comprehension_loop()
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``joblib`` is a library providing an easy way to parallelize for loops once we have a comprehension list.
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The number of jobs can be specified.
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.. code-block:: python
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from joblib import Parallel, delayed
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def joblib_loop():
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Parallel(n_jobs=4)(delayed(task)(i) for i in pics)
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%timeit joblib_loop()
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