[MXNet Forum] [Gluon] Reading images fast: list comprehension vs for loop

[Olivier Cruchant via MXNet Forum <mx...@discoursemail.com.INVALID>]

Hi,

I'm looking for the fastest way to read a folder of same-size images into an NDArray. Surprisingly, using a `for loop` of `concats` is 3x faster than doing a list comprehension. Any idea why? Any suggestion of fast technique for that?

Idea 1: For Loop of concats (**100ms**)

    ims = (mxim.imread(batch_path + '/' + piclist[0])
           .expand_dims(0)  # Create an extra dim for the concat
           .as_in_context(ctx))

    for picname in piclist[1:]:
        pic = mxim.imread(batch_path + '/' + picname).expand_dims(0)
        ims = nd.concat(ims, pic.as_in_context(ctx), dim=0)
        
    nd.waitall()

Idea 2: list comprehension (**320ms**)

    ims = nd.concat(
        *[mxim.imread(batch_path + '/' + pic).expand_dims(0) for pic in piclist],
        dim=0).as_in_context(ctx)

    nd.waitall()





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[MXNet Forum] [Gluon] Reading images fast: list comprehension vs for loop

[Olivier Cruchant via MXNet Forum <mx...@discoursemail.com.INVALID>]

Turns out the list comprehension on the GPU is actually even faster (vs concatenating on CPU and sending the whole concat after)

**85ms:**

    ims = [mxim.imread(batch_path + '/' + pic).expand_dims(0).as_in_context(ctx) for pic in piclist]
    ims = nd.concat(*ims, dim=0)





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