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Add Large Tensor Test for linalg_syrk #18782

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merged 5 commits into from
Jul 24, 2020

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Zha0q1
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@Zha0q1 Zha0q1 commented Jul 23, 2020

Description

Check if syrk_batch works correctly with large tensors. This test will fail with the current code base; #18752 should fix it.

TODO:

  1. make test function naming consistent with other large tensor tests (need to rebase after any of those tests are merged)
  2. merge this only after the fix has been merged

This test passes on both BLAS int32 and 64 builds.

ubuntu@ip-172-31-43-103:~$ MXNET_TEST_COUNT=10000 nosetests --logging-level=DEBUG --verbose -s mxnet/tests/nightly/test_large_array.py:test_linalg_operators
test_large_array.test_linalg_operators ... [23:14:57] ../src/storage/storage.cc:198: Using Pooled (Naive) StorageManager for CPU
ok

----------------------------------------------------------------------
Ran 1 test in 637.245s

OK

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@Zha0q1 can you fix this issue with your PR "This branch is out-of-date with the base branch"

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Zha0q1 commented Jul 23, 2020

@Zha0q1 can you fix this issue with your PR "This branch is out-of-date with the base branch"

Fixed.

A.attach_grad()
with mx.autograd.record():
out = nd.linalg.syrk(A, alpha=2, transpose=False)
for i in range(LARGE_SQ_X):
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You can check in 2 places in (0,y,y) and (1,y,y). No need to check in 70000 locations

assert out[0,i,i] == 2
assert_almost_equal(out[1,i,i], nd.array([0.02]), rtol=1e-3, atol=1e-5)
out.backward()
for i in range(LARGE_SQ_X):
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Same

for i in range(LARGE_SQ_X):
# check the first row
assert A.grad[0,0,i] == 4
assert_almost_equal(A.grad[1,0,i], nd.array([0.4]), rtol=1e-3, atol=1e-5)
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Question: Why did this become 0.4 and not 0.04 ? OR just let me know if this output is consistent with smaller inputs like 2x2 or 3x3.

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This is the correct result I believe. I verified with hand-written calculation. Yeah it also struck as counter-intuitive to me.. I am going to dive deep in matrix grad when I find time

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Can you just check with smaller input run and let me know the results. That should be good enough

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Few comments ... overall code is good

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Can you just check with smaller input run and let me know the results. That should be good enough .... overall LGTM!

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LGTM
Thanks!

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Zha0q1 commented Jul 24, 2020

Can you just check with smaller input run and let me know the results. That should be good enough .... overall LGTM!

This has been tested with both small and large input tensors

@Zha0q1 Zha0q1 changed the title [WIP] Add Large Tensor Test for linalg_syrk Add Large Tensor Test for linalg_syrk Jul 24, 2020
@@ -37,7 +37,7 @@
LARGE_X = 100000000
SMALL_X = 100
SMALL_Y = 50
LARGE_SQ_X = 80000
LARGE_SQ_X = 70000
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why?

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@ChaiBapchya ChaiBapchya Jul 24, 2020

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70000*70000/2**32 is just over 2**32
80k is lot more

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We figured 7000 is large enough to overflow int 32. This is a new constant just introduced so the few of us decided to tweak it to 70000

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70k * 70k = 4.9 billion
int32 range < 4.3 billion
Therefore increasing input size will only increase test runtime.

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ChaiBapchya commented Jul 24, 2020

@Zha0q1 also add your name to Contributors.md in the upcoming PR [let's not retrigger CI for that].
https://github.com/apache/incubator-mxnet/blob/master/CONTRIBUTORS.md
Thanks a lot for your contributions! :)

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Zha0q1 commented Jul 24, 2020

@Zha0q1 also add your name to Contributors.md in the upcoming PR [let's not retrigger CI for that].
https://github.com/apache/incubator-mxnet/blob/master/CONTRIBUTORS.md
Thanks a lot for your contributions! :)

will do!

@szha szha merged commit 85ff00d into apache:v1.x Jul 24, 2020
ChaiBapchya pushed a commit to ChaiBapchya/mxnet that referenced this pull request Aug 15, 2020
* add large tensor test for syrk, foward and backward

* change to batch input

* move syrk test into test-linalg

Co-authored-by: Ubuntu <[email protected]>
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5 participants