fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays #937

Mystic-Slice · 2022-03-23T03:52:21Z

Description

Switched out the torch's non-zero function with the NumPy version. Works as described in the issue ticket. Testing to be done.

Issue/s resolved: #925

Due Diligence

All split configurations tested
Multiple dtypes tested in relevant functions
Documentation updated (if needed)
Updated changelog.md under the title "Pending Additions"

Does this change modify the behaviour of other functions? If so, which?

no

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mtar · 2022-03-23T03:52:24Z

GPU cluster tests are currently disabled on this Pull Request.

Mystic-Slice · 2022-03-23T03:55:35Z

Hi @ClaudiaComito. This is the solution that I could come up with at first glance. It works well for the arrays I tested. But I still have to test different edge-cases like 1-D arrays, etc... Just thought I could get your input before proceeding further.
I also don't know if I handled the split, gout, and other things correctly. Let me know what you think.

Mystic-Slice · 2022-03-23T08:04:21Z

My fix failed for 1-D arrays. I think I fixed it now!

Mystic-Slice · 2022-03-23T08:05:57Z

I will update the documentation and the tests a little bit later.

ClaudiaComito

Hey @Mystic-Slice thanks a lot for diving into this right away!

Note that we only use torch operations internally. Our tensors might reside on GPUs, and a numpy operation would require copying the tensor to CPU.

heat/core/indexing.py

ClaudiaComito

Well done @Mystic-Slice, we're getting close, thanks a lot! The tests will be more work because many existing functions rely on the previous nonzero format.

heat/core/indexing.py

heat/core/tests/test_indexing.py

heat/core/indexing.py

ClaudiaComito · 2022-03-25T08:55:35Z

@Mystic-Slice I changed the base branch of this PR, because the change you implemented is needed in our indexing overhaul PR #938.

I've taken care of resolving conflicts (hence the commits). I hope you don't mind.

Mystic-Slice · 2022-03-25T12:54:44Z

Not at all.
I still can make the required changes to this branch right?

ClaudiaComito · 2022-03-25T13:12:40Z

Not at all. I still can make the required changes to this branch right?

Absolutely!

Mystic-Slice · 2022-03-25T13:12:40Z

@ClaudiaComito
I don't know if we even need to keep track of gout (shape of the output), split, etc...
Because anyways we convert it into a tuple and we lose all this information.
What do you think?

Mystic-Slice · 2022-03-28T17:02:38Z

@ClaudiaComito Hi, I made the fixes. But I am not able to get rid of a few errors that arise in testing. Can you please take a look?

ClaudiaComito · 2022-03-30T07:22:22Z

@ClaudiaComito I don't know if we even need to keep track of gout (shape of the output), split, etc... Because anyways we convert it into a tuple and we lose all this information. What do you think?

@Mystic-Slice , the DNDarray metadata always have to be correct. The information doesn't get lost, it gets used in all subsequent operations, and the returned tuple is a tuple of DNDarrays whose metadata will be based on the original one.

heat/core/indexing.py

ClaudiaComito · 2022-03-30T07:24:17Z

heat/core/indexing.py

-        comm=x.comm,
-        balanced=False,
+    lcl_nonzero = lcl_nonzero.transpose(0, 1)
+


gout must reflect the transposed global shape

ClaudiaComito

@Mystic-Slice thanks for the changes. Just two more changes are needed as far as I'm concerned.

Don't worry about the tests, they fail because our getitem/setitem is transitioning (among other things) from the old nonzero format to the new one, so basically every operation fails. We will take care of this in the parent branch/PR.

Mystic-Slice · 2022-03-30T14:41:13Z

@Mystic-Slice thanks for the changes. Just two more changes are needed as far as I'm concerned.

Don't worry about the tests, they fail because our getitem/setitem is transitioning (among other things) from the old nonzero format to the new one, so basically every operation fails. We will take care of this in the parent branch/PR.

Ahh okok. I was so lost becoz the changes I made had nothing to do with the errors I got. Thnkx for the clarification.
I have made the changes you requested.

Mystic-Slice · 2022-03-30T14:43:38Z

I made this change because when the DNDarray is converted into a tuple, the meta-data is not really being passed on to the tuple members. This fix solves it.

ClaudiaComito

I've been losing (lengthy) comments so I'll submit this review now even if it's not quite finished and fix it later. Thanks @Mystic-Slice !

ClaudiaComito · 2022-03-31T03:17:40Z

heat/core/indexing.py

    """
-    Return a :class:`~heat.core.dndarray.DNDarray` containing the indices of the elements that are non-zero.. (using ``torch.nonzero``)
+    Return a Tuple of :class:`~heat.core.dndarray.DNDarray`s, one for each dimension of a,


"... one for each dimension of x"

ClaudiaComito · 2022-03-31T03:18:55Z

heat/core/indexing.py

    """
-    Return a :class:`~heat.core.dndarray.DNDarray` containing the indices of the elements that are non-zero.. (using ``torch.nonzero``)
+    Return a Tuple of :class:`~heat.core.dndarray.DNDarray`s, one for each dimension of a,
+    containing the indices of the non-zero elements in that dimension. (using ``torch.nonzero``)


I know it was there before you started working on it, but I would remove "(using torch.nonzero)" now.

ClaudiaComito · 2022-03-31T03:35:20Z

heat/core/indexing.py

    If ``x`` is split then the result is split in the 0th dimension. However, this :class:`~heat.core.dndarray.DNDarray`
    can be UNBALANCED as it contains the indices of the non-zero elements on each node.
-    Returns an array with one entry for each dimension of ``x``, containing the indices of the non-zero elements in that dimension.
-    The values in ``x`` are always tested and returned in row-major, C-style order.
+    The values in ``x`` are always tested and returned in column-major, F-style order.


No, they are still tested in row-major, C-style order, otherwise nonzero would return indices starting from the last dimension. Here's a good reference: Internal memory layout of an ndarray.

ClaudiaComito · 2022-04-01T04:32:00Z

heat/core/indexing.py

        gout = list(lcl_nonzero.size())
        gout[0] = x.comm.allreduce(gout[0], MPI.SUM)


I had written a lengthy detailed explanation of what's happening here, and then I lost it. Doh. Anyway.

The original torch.nonzero output shape is (number_of_nonzero_elements, number_of_dimensions). The process-local lcl_nonzero only know about how many nonzero elements are on process. But the global output DNDarray must know the total.

That allreduce call replaces the local value of gout[0] (local number of rows = local number of nonzero elements) with the sum of all gout[0] on all processes, in order to synchronize gout to the global (albeit memory-distributed) number of rows of the output.

Problem: lcl_nonzero has been transposed, so it's no longer the rows, but the columns that represent the number of nonzero elements.

My suggestion:

transpose before the if split check

adjust line 71 lcl_nonzero[..., x.split] += displs[x.comm.rank] to correct the row (not the column) corresponding to the split dimension

the MPI collective call at line 78 should sum along the dimension containing the number of nonzero elements, now the columns

Mystic-Slice · 2022-04-01T14:16:26Z

@ClaudiaComito Thanks for the detailed review. I have made the changes.

ClaudiaComito

Thanks @Mystic-Slice, one more change needed and then I think we're good to go.

ClaudiaComito · 2022-04-05T03:21:44Z

heat/core/indexing.py

+        [
+            DNDarray(
+                dim_indices,
+                gshape=tuple(dim_indices.size()),


gshape needs to be the global size of the array (you calculated it with the allreduce call), dim_indices are local slices of the array.

Ahh makes sense....will make the change

ClaudiaComito

@Mystic-Slice can you update the changelog? I'll merge this one into the parent branch afterwards. Thanks a lot!

Mystic-Slice · 2022-04-08T04:11:18Z

@Mystic-Slice can you update the changelog? I'll merge this one into the parent branch afterwards. Thanks a lot!

Done :)

ClaudiaComito

Great, thanks a lot @Mystic-Slice , I will merge this into the parent branch and we can take care of the tests with the rest.

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Mystic-Slice force-pushed the NonzeroFunction branch from 1d683cf to 96fabe5 Compare March 23, 2022 07:30

Mystic-Slice changed the title ~~fix #925: Nonzero function works like the numpy counterpart~~ fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays Mar 23, 2022

ClaudiaComito requested changes Mar 23, 2022

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Mystic-Slice force-pushed the NonzeroFunction branch from be699be to dd1b83d Compare March 23, 2022 15:18

ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays

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ClaudiaComito changed the base branch from main to 914_adv-indexing-outshape-outsplit March 25, 2022 08:43

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Mystic-Slice added 2 commits March 30, 2022 20:01

Fix return type of nonzero function and gout value

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Transpose before if-branching + adjustments to accomodate it

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Fixed global shape assignment

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ht.nonzero() should return tuple of 1-D arrays instead of an n-D array #925

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fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays #937

fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays #937

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		gout = list(lcl_nonzero.size())
		gout[0] = x.comm.allreduce(gout[0], MPI.SUM)

fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays #937

fix #925: ht.nonzero() returns tuple of 1-D arrays instead of n-D arrays #937

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Mystic-Slice commented Mar 23, 2022 • edited by ClaudiaComito Loading

Description

Due Diligence

Does this change modify the behaviour of other functions? If so, which?

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