This past week I struggled to get a working GASNet build locally, with either the MPI or UDP conduits. After basically and entire day of frustration, I was finally able to get things working only by using the conda compilers and openmpi packages from (conda-forge).

Should we just add these to dev/test conda env files to use by default?

I am not uncertain if there are any potential downsides to this, so I wanted to open this issue for discussion.

cc @magnatelee @ipdemes @marcinz @trxcllnt

This change would prevent OpenBLAS from running tests during compilation. This is needed when building on machines or in conditions (e.g., using docker) that cause some of the OpenBLAS tests to fail. The potential downside of this is that we would want to run with OpenBLAS checks by default when users are building in the same environment in which they will run. If we want to run OpenBLAS tests by default, we could add an option to prevent testing at build time.

I've been testing a simple Laplace Eq. solver to compare Python+Numpy to legate.numpy and legate is hugely slower than Numpy.

The code is taken from: https://barbagroup.github.io/essential_skills_RRC/laplace/1/ . The code I actually run is the following:

import numpy as np
import time


def L2_error(p, pn):
    return np.sqrt(np.sum((p - pn)**2)/np.sum(pn**2))
# end if


def laplace2d(p, l2_target):
    '''Iteratively solves the Laplace equation using the Jacobi method

    Parameters:
    ----------
    p: 2D array of float
        Initial potential distribution
    l2_target: float
        target for the difference between consecutive solutions

    Returns:
    -------
    p: 2D array of float
        Potential distribution after relaxation
    '''

    l2norm = 1.0
    icount = 0
    tot_time = 0.0
    pn = np.empty_like(p)
    while l2norm > l2_target:

        start = time.perf_counter()

        icount = icount + 1
        pn = p.copy()
        p[1:-1,1:-1] = .25 * (pn[1:-1,2:] + pn[1:-1, :-2] \
                              + pn[2:, 1:-1] + pn[:-2, 1:-1])

        ##Neumann B.C. along x = L
        p[1:-1, -1] = p[1:-1, -2]     # 1st order approx of a derivative 
        l2norm = L2_error(p, pn)
        end = time.perf_counter()

        tot_time = tot_time + (end-start)

    # end while

    print("l2norm = ",l2norm)
    print("icount = ",icount)
    print("Total Iteration Time = ",tot_time)
    print("   Time per iteration = ",tot_time/icount)

    return p
# end if



if __name__ == "__main__":

    nx = 401
    ny = 401

    # Initial conditions
    p = np.zeros((ny,nx)) ##create a XxY vector of 0's

    # Dirichlet boundary conditions
    x = np.linspace(0,1,nx)
    p[-1,:] = np.sin(1.5*np.pi*x/x[-1])
    del x


    start = time.time()
    p = laplace2d(p.copy(), 1e-8)
    stop = time.time()

    print("Elapsed time = ",(stop-start)," secs")
    print(" ")


# end if

When I run it on my laptop with Anaconda Python3 and Numpy I get the following:

$ python3 jacobi.py 
l2norm =  9.99986062249016e-09
icount =  153539
Total Iteration Time =  127.02529454990054
   Time per iteration =  0.0008273161512703648
Elapsed time =  127.14257955551147  secs

When I change the import line to legate.numpy, I usually stop the code after 15 minutes of wall time. I have let it run for up to 60 minutes and it never converges.

As a check, I've run the Numpy code with legate itself and it exactly matches the Numpy results.

I have been experimenting with replacing the l2norm computations with numpy specific functions (np.subtract, np.square, etc.) but I have achieved no increase in performance.

Does anyone have any recommendations?

Thanks!

Jeff

(edit by Manolis: added some formatting for the code sections)

This is clearly an issue in OpenBLAS but it blocks my Legate Numpy install and is unexpected, based on my experience with OpenBLAS in other contexts.

[email protected]:~/LEGATE/np$ python3 ./install.py --install-dir $HOME/LEGATE --with-core $HOME/LEGATE 2>&1 | tee log
Verbose build is  off
Legate is installing OpenBLAS into a local directory...
Cloning into '/tmp/tmpm780ryjm'...
Note: switching to 'd2b11c47774b9216660e76e2fc67e87079f26fa1'.

You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by switching back to a branch.

If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -c with the switch command. Example:

  git switch -c <new-branch-name>

Or undo this operation with:

  git switch -

Turn off this advice by setting config variable advice.detachedHead to false

Switched to a new branch 'master'
getarch_2nd.c: In function ‘main’:
getarch_2nd.c:14:35: error: ‘SGEMM_DEFAULT_UNROLL_M’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_UNROLL_M’?
   14 |     printf("SGEMM_UNROLL_M=%d\n", SGEMM_DEFAULT_UNROLL_M);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   SBGEMM_DEFAULT_UNROLL_M
getarch_2nd.c:14:35: note: each undeclared identifier is reported only once for each function it appears in
getarch_2nd.c:15:35: error: ‘SGEMM_DEFAULT_UNROLL_N’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_UNROLL_N’?
   15 |     printf("SGEMM_UNROLL_N=%d\n", SGEMM_DEFAULT_UNROLL_N);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   SBGEMM_DEFAULT_UNROLL_N
getarch_2nd.c:16:35: error: ‘DGEMM_DEFAULT_UNROLL_M’ undeclared (first use in this function); did you mean ‘XGEMM_DEFAULT_UNROLL_M’?
   16 |     printf("DGEMM_UNROLL_M=%d\n", DGEMM_DEFAULT_UNROLL_M);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   XGEMM_DEFAULT_UNROLL_M
getarch_2nd.c:17:35: error: ‘DGEMM_DEFAULT_UNROLL_N’ undeclared (first use in this function); did you mean ‘QGEMM_DEFAULT_UNROLL_N’?
   17 |     printf("DGEMM_UNROLL_N=%d\n", DGEMM_DEFAULT_UNROLL_N);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   QGEMM_DEFAULT_UNROLL_N
getarch_2nd.c:21:35: error: ‘CGEMM_DEFAULT_UNROLL_M’ undeclared (first use in this function); did you mean ‘XGEMM_DEFAULT_UNROLL_M’?
   21 |     printf("CGEMM_UNROLL_M=%d\n", CGEMM_DEFAULT_UNROLL_M);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   XGEMM_DEFAULT_UNROLL_M
getarch_2nd.c:22:35: error: ‘CGEMM_DEFAULT_UNROLL_N’ undeclared (first use in this function); did you mean ‘QGEMM_DEFAULT_UNROLL_N’?
   22 |     printf("CGEMM_UNROLL_N=%d\n", CGEMM_DEFAULT_UNROLL_N);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   QGEMM_DEFAULT_UNROLL_N
getarch_2nd.c:23:35: error: ‘ZGEMM_DEFAULT_UNROLL_M’ undeclared (first use in this function); did you mean ‘XGEMM_DEFAULT_UNROLL_M’?
   23 |     printf("ZGEMM_UNROLL_M=%d\n", ZGEMM_DEFAULT_UNROLL_M);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   XGEMM_DEFAULT_UNROLL_M
getarch_2nd.c:24:35: error: ‘ZGEMM_DEFAULT_UNROLL_N’ undeclared (first use in this function); did you mean ‘QGEMM_DEFAULT_UNROLL_N’?
   24 |     printf("ZGEMM_UNROLL_N=%d\n", ZGEMM_DEFAULT_UNROLL_N);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~
      |                                   QGEMM_DEFAULT_UNROLL_N
getarch_2nd.c:71:50: error: ‘SGEMM_DEFAULT_Q’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_Q’?
   71 |     printf("#define SLOCAL_BUFFER_SIZE\t%ld\n", (SGEMM_DEFAULT_Q * SGEMM_DEFAULT_UNROLL_N * 4 * 1 *  sizeof(float)));
      |                                                  ^~~~~~~~~~~~~~~
      |                                                  SBGEMM_DEFAULT_Q
getarch_2nd.c:72:50: error: ‘DGEMM_DEFAULT_Q’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_Q’?
   72 |     printf("#define DLOCAL_BUFFER_SIZE\t%ld\n", (DGEMM_DEFAULT_Q * DGEMM_DEFAULT_UNROLL_N * 2 * 1 *  sizeof(double)));
      |                                                  ^~~~~~~~~~~~~~~
      |                                                  SBGEMM_DEFAULT_Q
getarch_2nd.c:73:50: error: ‘CGEMM_DEFAULT_Q’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_Q’?
   73 |     printf("#define CLOCAL_BUFFER_SIZE\t%ld\n", (CGEMM_DEFAULT_Q * CGEMM_DEFAULT_UNROLL_N * 4 * 2 *  sizeof(float)));
      |                                                  ^~~~~~~~~~~~~~~
      |                                                  SBGEMM_DEFAULT_Q
getarch_2nd.c:74:50: error: ‘ZGEMM_DEFAULT_Q’ undeclared (first use in this function); did you mean ‘SBGEMM_DEFAULT_Q’?
   74 |     printf("#define ZLOCAL_BUFFER_SIZE\t%ld\n", (ZGEMM_DEFAULT_Q * ZGEMM_DEFAULT_UNROLL_N * 2 * 2 *  sizeof(double)));
      |                                                  ^~~~~~~~~~~~~~~
      |                                                  SBGEMM_DEFAULT_Q
make: *** [Makefile.prebuild:74: getarch_2nd] Error 1
Makefile:154: *** OpenBLAS: Detecting CPU failed. Please set TARGET explicitly, e.g. make TARGET=your_cpu_target. Please read README for the detail..  Stop.
Traceback (most recent call last):
  File "./install.py", line 543, in <module>
    driver()
  File "./install.py", line 539, in driver
    install_legate_numpy(unknown=unknown, **vars(args))
  File "./install.py", line 359, in install_legate_numpy
    install_openblas(openblas_dir, thread_count, verbose)
  File "./install.py", line 143, in install_openblas
    execute_command(
  File "./install.py", line 62, in execute_command
    subprocess.check_call(args, cwd=cwd, shell=shell)
  File "/usr/lib/python3.8/subprocess.py", line 364, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['make', '-j', '8', 'USE_THREAD=1', 'NO_STATIC=1', 'USE_OPENMP=1', 'NUM_PARALLEL=32', 'LIBNAMESUFFIX=legate']' returned non-zero exit status 2.

Reciprocal is not valid for integers, which leads to test failures on certain platforms.

https://numpy.org/doc/stable/reference/generated/numpy.reciprocal.html

• Splits math ufunc tests into default operations and operations needing special values
• Enables easier customization of input values to the different tests
• Simplifies syntax for calling tests since all tests only take a single argument
• Uses a hash-based seed for initializing random values so that tests use the same values whether tests are run individually or all-at-once

This PR add support for cpu/gpu sharding so that that it is no longer necessary to unset REALM_SYNTHETIC_CORE_MAP

Other notes:

• Test stages were refactored and simplified. Most control was moved to base protocol class, with stage implementations responsible only for computing the sharding spec, etc.
• --debug now also includes explicitly modified env vars in printed output
• --fbmem command line option was added for GPU stage
• Some missing docs were added
• Some minimal tests of sharding computations were added, but perhaps more is advised

Tested locally with MPI GASNet conduit, with variations of the following invocations:

GASNET_QUIET=1 ./test.py --use=openmp --omps=2 --ompthreads=1 --launcher=mpirun --debug
GASNET_QUIET=1 ./test.py --use=cpus --cpus 2 --launcher=mpirun --debug 
GASNET_QUIET=1 ./test.py --use=cuda --gpus 2 --launcher=mpirun --debug
GASNET_QUIET=1 ./test.py --use=eager --launcher=mpirun --debug

Problem

Advanced indexing of a relatively huge (e.g., length 10K) 1D array returns UnboundLocalError: local variable 'shardfn' referenced before assignment, rather than NotImplementedError.

I understand that advanced indexing is mostly not yet implemented. Most related routines raise NotImplementedError to let users know about this situation. However, this particular use case raises this different error, which seems to be a bug to me.

To reproduce

1. step 1: prepare test.py:

   from legate import numpy
   a = numpy.arange(10000)
   print(a[(1, 2, 3), ]) 
   

2. step 2: run with, for example

   $ legate --cpus 1 test.py
   

Output

Traceback (most recent call last):
  File "<blahblah>/lib/python3.8/site-packages/legion_top.py", line 394, in legion_python_main
    run_path(args[start], run_name='__main__')
  File "<blahblah>/lib/python3.8/site-packages/legion_top.py", line 193, in run_path
    exec(code, module.__dict__, module.__dict__)
  File "./test.py", line 3, in <module>
    print(a[(1, 2, 3), ])
  File "<blahblah>/lib/python3.8/site-packages/legate/numpy/array.py", line 381, in __getitem__
    shape=None, thunk=self._thunk.get_item(key, stacklevel=2)
  File "<blahblah>/lib/python3.8/site-packages/legate/numpy/deferred.py", line 414, in get_item
    copy = Copy(mapper=self.runtime.mapper_id, tag=shardfn)
UnboundLocalError: local variable 'shardfn' referenced before assignment

Expected results

Either [1, 2, 3] or NotImplementedError.

Notes

• Interestingly, smaller arrays do not have this issue. For example, if a = numpy.arange(100), the code works fine.
• Another way to make it works is to use GPUs instead of CPUs. For example, legate --gpus 1 test.py works fine. This is interesting, as the GPU implementation seems to be more stable than CPU implementation?

This PR convert the existing test modules to use pytest for test discovery and running. Tests were also updated for minor cleanup and to utilize pytest features (e.g. parameterize and fixtures) effectively. The end result is to afford testing options that are more familiar and ergonomic to "standard" python devs.

Overview

Cleanup

A few commits perform some minor cleanup on the existing tests:

• https://github.com/nv-legate/cunumeric/pull/297/commits/572e7f106cffb80df2d0dcd0bb17ff423d2e2b11 — remove old and outdated "universal functions" tests
• https://github.com/nv-legate/cunumeric/pull/297/commits/5e0ff856667234f0bff4d0ff48ab08dcf192ed7c — remove a useless test
• https://github.com/nv-legate/cunumeric/pull/297/commits/5d8a6172caa97501e795688c22d969efbe404056 — remove redundant bare return statements throughout

File movement

• To make it easier to use pytest for test selection, the existing tests were moved and renamed:

• https://github.com/nv-legate/cunumeric/pull/297/commits/3f3c5cb8d3ed05a0981990e9920d851d58dd19a1 — move files to integration subdirectory

• https://github.com/nv-legate/cunumeric/pull/297/commits/9f4f4108449f56f360e90c2f56d30569796b7c0c — prefix all test module filenames with test_

Moving the files to a subdirectory allows this entire group of tests to be easily run by executing pytest with this directory path. The test_ prefix is to conform with pytest expectations for default test discovery.

Pytest updates

• https://github.com/nv-legate/cunumeric/pull/297/commits/571ea075d549da3875550aa0d28f4154af83339d — rename some helper functions to avoid test_ prefix. By default, pytest will interpret anything starting with test or Test as test to run.
• https://github.com/nv-legate/cunumeric/pull/297/commits/76779365e25cff1c9274b17f454145267aee51b8 — a minimal update that adds pytest scaffolding to each test module and the least change to get running. For most tests this was just a couple of lines of boilerplate change. But a few tests required slightly more extensive updates.
• https://github.com/nv-legate/cunumeric/pull/297/commits/bbda5a96336d320ade26e34cd6359acc6da6d0b7 — more in-depth changed to split out tests into sensible smaller jobs, and to utilize parameterization and fixtures.

Notes

• The existing test.py module runs exactly as before. The only change was to update it for the new path to the test files ~~(see note about verbose output, though)~~
• If desired to make this PR smaller, the final commit could be removed and submitted separately.
• There is a legate.core issue that currently required fixtures to avoid cunumeric array re-use in tests
  • https://github.com/nv-legate/legate.core/issues/205
• In the final commit I did try to split up tests and/or use parametrize anywhere it made sense, so that more fine-grained reporting output becomes available:

  tests/integration/test_reduction_complex.py::test_sum PASSED   [ 96%]
  tests/integration/test_reduction_complex.py::test_prod PASSED  [ 96%]
  tests/integration/test_repeat.py::test_basic PASSED            [ 96%]
  tests/integration/test_repeat.py::test_axis PASSED             [ 96%]
  tests/integration/test_repeat.py::test_nd[1] PASSED            [ 96%]
  tests/integration/test_repeat.py::test_nd[2] PASSED            [ 96%]
  tests/integration/test_repeat.py::test_nd[3] PASSED            [ 96%]
  tests/integration/test_repeat.py::test_nd[4] PASSED            [ 97%]
  

Further notes will be inline.

Operation

Running test.py

The existing way to run tests with test.py is unchanged:

./test.py --use=cuda 

This still generates the existing report:

~~(Note: Currently test.py -v only shows stdout from test.py and not from tests. This will be straightforward to restore but I would like to do that in a follow-on PR dedicated to test.py. Test stdout can be observed with either of the methods below with the standard -s flag. cc @magnatelee)~~

Executing individual tests

Individual tests can still be executed by running the module with legate including by passing in runtime command line options:

legate tests/integration/test_nonzero.py --gpus 2 -cunumeric:test

However, now the output is a standard pytest report:

It is also now possible to pass standard pytests options, e.g. -v for a verbose report:

Using pytest for test discovery

Although it is not yet possible to simply run pytest <dir> in the typical way, it is possible to achieve the same operation with a little more explicit invocation:

legate -c "import pytest; pytest.main(['tests/integration'])" --gpus 2 -cunumeric:test 

Note that all the standard pytest options, e.g. incluing -k and -m for test filtering, can be used.

The above will run all the tests under tests/integration, and generate a standard combined pytest report:

The full report output text can be seen here:

legate37 ❯ legate -c "import pytest; pytest.main(['tests/integration'])" --gpus 2 -cunumeric:test 

WARNING: Disabling control replication for interactive run
========================================================================================= test session starts ==========================================================================================
platform linux -- Python 3.7.12, pytest-7.1.1, pluggy-1.0.0
rootdir: /home/bryan/work/cunumeric
collected 2860 items                                                                                                                                                                                   

tests/integration/test_2d_reduction.py ...                                                                                                                                                       [  0%]
tests/integration/test_3d_reduction.py .                                                                                                                                                         [  0%]
tests/integration/test_advanced_indexing.py .                                                                                                                                                    [  0%]
tests/integration/test_append.py ........                                                                                                                                                        [  0%]
tests/integration/test_argmin.py ..                                                                                                                                                              [  0%]
tests/integration/test_array_creation.py ..............                                                                                                                                          [  1%]
tests/integration/test_array_split.py .......                                                                                                                                                    [  1%]
tests/integration/test_binary_op.py .....                                                                                                                                                        [  1%]
tests/integration/test_binary_op_2d.py ....                                                                                                                                                      [  1%]
tests/integration/test_binary_op_broadcast.py ....                                                                                                                                               [  1%]
tests/integration/test_binary_op_complex.py .....                                                                                                                                                [  1%]
tests/integration/test_binary_op_typing.py ..................................................................................................................................................... [  7%]
................................................................................................................................................................................................ [ 13%]
................................................................................................................................................................................................ [ 20%]
................................................................................................................................................................................................ [ 27%]
................................................................................................................................................................................................ [ 33%]
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.................................................................................................................................................................................                [ 80%]
tests/integration/test_binary_ufunc.py .                                                                                                                                                         [ 80%]
tests/integration/test_bincount.py ......                                                                                                                                                        [ 80%]
tests/integration/test_block.py ............                                                                                                                                                     [ 81%]
tests/integration/test_cholesky.py .........                                                                                                                                                     [ 81%]
tests/integration/test_compare.py ......                                                                                                                                                         [ 81%]
tests/integration/test_complex_ops.py ....                                                                                                                                                       [ 81%]
tests/integration/test_concatenate_stack.py ................................................                                                                                                     [ 83%]
tests/integration/test_contains.py ..                                                                                                                                                            [ 83%]
tests/integration/test_convolve.py ......                                                                                                                                                        [ 83%]
tests/integration/test_copy.py .                                                                                                                                                                 [ 83%]
tests/integration/test_dot.py .........................                                                                                                                                          [ 84%]
tests/integration/test_einsum.py .......................................................................................................................................................         [ 89%]
tests/integration/test_eye.py ...............                                                                                                                                                    [ 90%]
tests/integration/test_fill.py .                                                                                                                                                                 [ 90%]
tests/integration/test_flatten.py .........                                                                                                                                                      [ 90%]
tests/integration/test_flip.py ..........                                                                                                                                                        [ 91%]
tests/integration/test_get_item.py .                                                                                                                                                             [ 91%]
tests/integration/test_index_routines.py ............                                                                                                                                            [ 91%]
tests/integration/test_ingest.py ....                                                                                                                                                            [ 91%]
tests/integration/test_inlinemap-keeps-region-alive.py .                                                                                                                                         [ 91%]
tests/integration/test_inner.py .........................                                                                                                                                        [ 92%]
tests/integration/test_interop.py .                                                                                                                                                              [ 92%]
tests/integration/test_intra_array_copy.py ....                                                                                                                                                  [ 92%]
tests/integration/test_jacobi.py .                                                                                                                                                               [ 92%]
tests/integration/test_length.py ....                                                                                                                                                            [ 92%]
tests/integration/test_linspace.py ....                                                                                                                                                          [ 93%]
tests/integration/test_logical.py .....s                                                                                                                                                         [ 93%]
tests/integration/test_lstm_backward_test.py .                                                                                                                                                   [ 93%]
tests/integration/test_lstm_simple_forward.py .                                                                                                                                                  [ 93%]
tests/integration/test_map_reduce.py .                                                                                                                                                           [ 93%]
tests/integration/test_mask.py ....                                                                                                                                                              [ 93%]
tests/integration/test_matmul.py ................                                                                                                                                                [ 94%]
tests/integration/test_nonzero.py ........                                                                                                                                                       [ 94%]
tests/integration/test_norm.py .                                                                                                                                                                 [ 94%]
tests/integration/test_numpy_interop.py .                                                                                                                                                        [ 94%]
tests/integration/test_outer.py .................                                                                                                                                                [ 95%]
tests/integration/test_overwrite_slice.py .                                                                                                                                                      [ 95%]
tests/integration/test_randint.py ..                                                                                                                                                             [ 95%]
tests/integration/test_reduction.py .......                                                                                                                                                      [ 95%]
tests/integration/test_reduction_axis.py ..................                                                                                                                                      [ 96%]
tests/integration/test_reduction_complex.py ..                                                                                                                                                   [ 96%]
tests/integration/test_repeat.py ......                                                                                                                                                          [ 96%]
tests/integration/test_reshape.py .................                                                                                                                                              [ 96%]
tests/integration/test_set_item.py .                                                                                                                                                             [ 96%]
tests/integration/test_shape.py .s                                                                                                                                                               [ 97%]
tests/integration/test_singleton_access.py .                                                                                                                                                     [ 97%]
tests/integration/test_slicing.py ..ss                                                                                                                                                           [ 97%]
tests/integration/test_sort.py .                                                                                                                                                                 [ 97%]
tests/integration/test_squeeze.py .                                                                                                                                                              [ 97%]
tests/integration/test_swapaxes.py ....                                                                                                                                                          [ 97%]
tests/integration/test_tensordot.py .........................                                                                                                                                    [ 98%]
tests/integration/test_tile.py ..                                                                                                                                                                [ 98%]
tests/integration/test_transpose.py ..                                                                                                                                                           [ 98%]
tests/integration/test_trilu.py ..........                                                                                                                                                       [ 98%]
tests/integration/test_unary_functions_2d.py ........                                                                                                                                            [ 99%]
tests/integration/test_unary_functions_2d_complex.py .....                                                                                                                                       [ 99%]
tests/integration/test_unary_ufunc.py .                                                                                                                                                          [ 99%]
tests/integration/test_unique.py .....                                                                                                                                                           [ 99%]
tests/integration/test_update.py .                                                                                                                                                               [ 99%]
tests/integration/test_vdot.py ....                                                                                                                                                              [ 99%]
tests/integration/test_view.py .                                                                                                                                                                 [ 99%]
tests/integration/test_vstack.py ...                                                                                                                                                             [ 99%]
tests/integration/test_where.py .....s                                                                                                                                                           [ 99%]
tests/integration/test_window.py .                                                                                                                                                               [100%]

=========================================================================================== warnings summary ===========================================================================================
tests/integration/test_advanced_indexing.py: 124 warnings
  /home/bryan/work/cunumeric/cunumeric/array.py:773: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    if key.dtype != np.bool and not np.issubdtype(

tests/integration/test_advanced_indexing.py: 124 warnings
  /home/bryan/work/cunumeric/cunumeric/array.py:777: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    if key.dtype != np.bool and key.dtype != np.int64:

tests/integration/test_advanced_indexing.py: 30 warnings
  /home/bryan/work/cunumeric/cunumeric/deferred.py:425: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    and key.dtype == np.bool

tests/integration/test_advanced_indexing.py: 120 warnings
  /home/bryan/work/cunumeric/cunumeric/deferred.py:479: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    and k.dtype == np.bool

tests/integration/test_advanced_indexing.py: 120 warnings
  /home/bryan/work/cunumeric/cunumeric/deferred.py:516: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    if k.dtype == np.bool:

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:118: RuntimeWarning: converting index array to int64 type
    assert np.array_equal(x[index], x_num[index_num])

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:122: RuntimeWarning: converting index array to int64 type
    x_num[index_num] = 3.5

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:129: UserWarning: cuNumeric performing implicit type conversion from float64 to int64
    x_num[index_num] = b_num

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:129: RuntimeWarning: converting index array to int64 type
    x_num[index_num] = b_num

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:559: UserWarning: cuNumeric performing implicit type conversion from float64 to int64
    z_num[indx_num] = b_num

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:609: RuntimeWarning: converting index array to int64 type
    res_num = x_num[ind_num, ind_num]

tests/integration/test_advanced_indexing.py::test
  /home/bryan/work/cunumeric/tests/integration/test_advanced_indexing.py:627: UserWarning: cuNumeric performing implicit type conversion from int16 to float64
    x_num[ind_num, ind_num] = b_num

tests/integration/test_cholesky.py::test_complex[8]
tests/integration/test_cholesky.py::test_complex[9]
tests/integration/test_cholesky.py::test_complex[255]
tests/integration/test_cholesky.py::test_complex[512]
  /home/bryan/work/cunumeric/tests/integration/test_cholesky.py:48: UserWarning: cuNumeric performing implicit type conversion from complex128 to float64
    d[1] = b

tests/integration/test_dot.py::test_dot[1-1]
tests/integration/test_dot.py::test_dot[1-2]
tests/integration/test_dot.py::test_dot[2-1]
tests/integration/test_dot.py::test_dot[2-2]
  /home/bryan/work/cunumeric/tests/integration/test_dot.py:34: UserWarning: cuNumeric performing implicit type conversion from float16 to float32
    return lib.dot(*args, **kwargs)

tests/integration/test_einsum.py::test_cast[->]
tests/integration/test_einsum.py::test_cast[a->]
tests/integration/test_einsum.py::test_cast[a,->]
tests/integration/test_einsum.py::test_cast[a,a->]
  /home/bryan/work/cunumeric/cunumeric/array.py:123: ComplexWarning: Casting complex values to real discards the imaginary part
    *args, **kwargs

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from float16 to float32
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from float16 to complex64
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from float32 to float16
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from float32 to complex64
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from complex64 to float16
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a->a]
tests/integration/test_einsum.py::test_cast[a,->a]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:235: UserWarning: cuNumeric performing implicit type conversion from complex64 to float32
    cn.einsum(expr, *cn_inputs, out=cn_out)

tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:228: UserWarning: cuNumeric performing implicit type conversion from float16 to float32
    cn_res = cn.einsum(expr, *cn_inputs)

tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:228: UserWarning: cuNumeric performing implicit type conversion from float16 to complex64
    cn_res = cn.einsum(expr, *cn_inputs)

tests/integration/test_einsum.py::test_cast[a,a->]
tests/integration/test_einsum.py::test_cast[a,a->a]
tests/integration/test_einsum.py::test_cast[a,b->ab]
tests/integration/test_einsum.py::test_cast[ab,ca->a]
tests/integration/test_einsum.py::test_cast[ab,ca->b]
  /home/bryan/work/cunumeric/tests/integration/test_einsum.py:228: UserWarning: cuNumeric performing implicit type conversion from float32 to complex64
    cn_res = cn.einsum(expr, *cn_inputs)

tests/integration/test_flatten.py::test_basic[(1, 1)]
tests/integration/test_flatten.py::test_basic[(1, 1, 1)]
tests/integration/test_flatten.py::test_basic[(1, 10)]
tests/integration/test_flatten.py::test_basic[(1, 10, 1)]
tests/integration/test_flatten.py::test_basic[(10, 10)]
tests/integration/test_flatten.py::test_basic[(10, 10, 10)]
  /home/bryan/work/cunumeric/tests/integration/test_flatten.py:26: RuntimeWarning: cuNumeric has not implemented reshape using Fortran-like index order and is falling back to canonical numpy. You may notice significantly decreased performance for this function call.
    c = num_arr.flatten(order)

tests/integration/test_index_routines.py::test_choose_1d
  /home/bryan/work/cunumeric/tests/integration/test_index_routines.py:42: UserWarning: cuNumeric performing implicit type conversion from int64 to float64
    assert np.array_equal(

tests/integration/test_sort.py::test
  /home/bryan/work/cunumeric/tests/integration/test_sort.py:23: UserWarning: cuNumeric performing implicit type conversion from complex64 to complex128
    if not num.allclose(a_np, a_num):

tests/integration/test_vdot.py::test[complex64-complex128]
tests/integration/test_vdot.py::test[complex128-complex64]
  /home/bryan/work/cunumeric/tests/integration/test_vdot.py:28: UserWarning: cuNumeric performing implicit type conversion from complex64 to complex128
    mk_0to1_array(lib, (5,), dtype=b_dtype),

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
============================================================================ 2855 passed, 5 skipped, 601 warnings in 41.34s ============================================================================

There are some warning that show up in the output at the end, mostly about implicit casting. I am not sure if these are expected or not (I expect they would be)

Future work

Things that are not in this PR but are planned for follow-on PRs:

• Using pytest to run the examples
• ~~Restoring previous -v behaviour to test.py~~
• Increased documentation for running tests
• Allowing to run with simpler legate -m pytest

This PR adds some "basic" unit tests to a cubset of cunumeric modules:

• cunumeric.coverage
• cunumeric.patch
• cunumeric.utils

Currently, these tests may be run manually by executing the command

legate -c "import pytest; pytest.main(['tests/unit', '-v'])"

which will result in output similar to:

WARNING: Disabling control replication for interactive run
======================================================== test session starts ========================================================
platform linux -- Python 3.7.12, pytest-7.1.1, pluggy-1.0.0 -- /home/bryan/anaconda3/envs/legate37/bin/python3
cachedir: .pytest_cache
rootdir: /home/bryan/work/cunumeric
collected 66 items                                                                                                                  

tests/unit/cunumeric/test_coverage.py::test_FALLBACK_WARNING PASSED                                                           [  1%]
tests/unit/cunumeric/test_coverage.py::test_MOD_INTERNAL PASSED                                                               [  3%]
tests/unit/cunumeric/test_coverage.py::test_NDARRAY_INTERNAL PASSED                                                           [  4%]
tests/unit/cunumeric/test_coverage.py::Test_filter_namespace::test_empty PASSED                                               [  6%]
tests/unit/cunumeric/test_coverage.py::Test_filter_namespace::test_no_filters PASSED                                          [  7%]
tests/unit/cunumeric/test_coverage.py::Test_filter_namespace::test_name_filters PASSED                                        [  9%]
tests/unit/cunumeric/test_coverage.py::Test_filter_namespace::test_type_filters PASSED                                        [ 10%]
tests/unit/cunumeric/test_coverage.py::test_implemented PASSED                                                                [ 12%]
tests/unit/cunumeric/test_coverage.py::Test_unimplemented::test_reporting_True PASSED                                         [ 13%]
tests/unit/cunumeric/test_coverage.py::Test_unimplemented::test_reporting_False PASSED                                        [ 15%]
tests/unit/cunumeric/test_coverage.py::Test_clone_module::test_report_coverage_True PASSED                                    [ 16%]
tests/unit/cunumeric/test_coverage.py::Test_clone_module::test_report_coverage_False PASSED                                   [ 18%]
tests/unit/cunumeric/test_coverage.py::Test_clone_class::test_report_coverage_True PASSED                                     [ 19%]
tests/unit/cunumeric/test_coverage.py::Test_clone_class::test_report_coverage_False PASSED                                    [ 21%]
tests/unit/cunumeric/test_patch.py::test_no_patch PASSED                                                                      [ 22%]
tests/unit/cunumeric/test_patch.py::test_patch PASSED                                                                         [ 24%]
tests/unit/cunumeric/test_utils.py::test_find_last_user_stacklevel PASSED                                                     [ 25%]
tests/unit/cunumeric/test_utils.py::test_get_line_number_from_frame PASSED                                                    [ 27%]
tests/unit/cunumeric/test_utils.py::Test_find_last_user_frames::test_default_top_only PASSED                                  [ 28%]
tests/unit/cunumeric/test_utils.py::Test_find_last_user_frames::test_top_only_True PASSED                                     [ 30%]
tests/unit/cunumeric/test_utils.py::Test_find_last_user_frames::test_top_only_False PASSED                                    [ 31%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[foo] PASSED                                        [ 33%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[10] PASSED                                         [ 34%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[10.2] PASSED                                       [ 36%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[value3] PASSED                                     [ 37%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[value4] PASSED                                     [ 39%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[value5] PASSED                                     [ 40%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[value6] PASSED                                     [ 42%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_type_bad[None] PASSED                                       [ 43%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[float16] PASSED                                   [ 45%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[float32] PASSED                                   [ 46%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[float64] PASSED                                   [ 48%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[float] PASSED                                     [ 50%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[int16] PASSED                                     [ 51%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[int32] PASSED                                     [ 53%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[int64] PASSED                                     [ 54%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[int] PASSED                                       [ 56%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[uint16] PASSED                                    [ 57%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[uint32] PASSED                                    [ 59%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[uint64] PASSED                                    [ 60%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[bool_] PASSED                                     [ 62%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_supported[bool] PASSED                                      [ 63%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_unsupported[float128] PASSED                                [ 65%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_unsupported[complex64] PASSED                               [ 66%]
tests/unit/cunumeric/test_utils.py::Test_is_supported_dtype::test_unsupported[datetime64] PASSED                              [ 68%]
tests/unit/cunumeric/test_utils.py::test_calculate_volume[shape0-0] PASSED                                                    [ 69%]
tests/unit/cunumeric/test_utils.py::test_calculate_volume[shape1-10] PASSED                                                   [ 71%]
tests/unit/cunumeric/test_utils.py::test_calculate_volume[shape2-6] PASSED                                                    [ 72%]
tests/unit/cunumeric/test_utils.py::test_get_arg_dtype PASSED                                                                 [ 74%]
tests/unit/cunumeric/test_utils.py::test_get_arg_value_dtype PASSED                                                           [ 75%]
tests/unit/cunumeric/test_utils.py::test_dot_modes PASSED                                                                     [ 77%]
tests/unit/cunumeric/test_utils.py::test_inner_modes PASSED                                                                   [ 78%]
tests/unit/cunumeric/test_utils.py::test_matmul_modes_bad[0-0] PASSED                                                         [ 80%]
tests/unit/cunumeric/test_utils.py::test_matmul_modes_bad[0-1] PASSED                                                         [ 81%]
tests/unit/cunumeric/test_utils.py::test_matmul_modes_bad[1-0] PASSED                                                         [ 83%]
tests/unit/cunumeric/test_utils.py::test_matmul_modes PASSED                                                                  [ 84%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_single_axis[1-3-2] PASSED                                  [ 86%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_single_axis[3-1-2] PASSED                                  [ 87%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_single_axis[1-1-2] PASSED                                  [ 89%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_axes_length PASSED                                         [ 90%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_negative_axes PASSED                                       [ 92%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_mismatched_axes PASSED                                     [ 93%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_bad_axes_oob PASSED                                            [ 95%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_single_axis PASSED                                             [ 96%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_tuple_axis PASSED                                              [ 98%]
tests/unit/cunumeric/test_utils.py::Test_tensordot_modes::test_explicit_axis PASSED                                           [100%]

======================================================== 66 passed in 2.71s =========================================================

Notes

• The mock packages was added to the conda environment file. It needs to be installed (manually in an existing env, otherwise) to run the tests.
• I haven't thought about contracting differential forms in ~20 years, so the product mode tests record a snapshot of current behavior as-is, while trying to cover error paths explicitly. I did not separately try to verify correctness.
• Slots were removed from Runtime. They were interfering with the ability to mock Runtime methods and attributes, but also are not really appropriate in this situation. The intended purpose of __slots__ is a space-optimization in the case of many small objects.
• I added a flag to the wrappers returned by implemented / unimplemented just to greatly streamline testing.
• The last deprecated uses of np.bool etc, were removed.

This bug happens in the conda environment (confirmed on at least 2 different machines):

[0 - 7ffec1256700]    7.756864 {2}{python}: destroying interpreter
^C
Thread 1 "legion_python" received signal SIGINT, Interrupt.
syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
38	../sysdeps/unix/sysv/linux/x86_64/syscall.S: No such file or directory.
(gdb) info threads
  Id   Target Id         Frame
* 1    Thread 0x7ffff11c6000 (LWP 24267) "legion_python" syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
  2    Thread 0x7fffeb062700 (LWP 24293) "legion_python" 0x00007ffff36450c7 in accept4 (fd=29, addr=..., addr_len=0x7fffeb05ebb4, flags=524288) at ../sysdeps/unix/sysv/linux/accept4.c:32
  3    Thread 0x7fffea761700 (LWP 24295) "legion_python" syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
  4    Thread 0x7fffea65b700 (LWP 24296) "legion_python" syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
  9    Thread 0x7ffec1fff700 (LWP 24301) "jemalloc_bg_thd" 0x00007ffff13daad3 in futex_wait_cancelable (private=<optimized out>, expected=0, futex_word=0x7ffec260a5f4) at ../sysdeps/unix/sysv/linux/futex-internal.h:88
  10   Thread 0x7ffec1256700 (LWP 24302) "legion_python" 0x00007ffff13dd7c6 in futex_abstimed_wait_cancelable (private=0, abstime=0x0, expected=0, futex_word=0x7ffecc070b10) at ../sysdeps/unix/sysv/linux/futex-internal.h:205
(gdb) bt
#0  syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
#1  0x00007ffff3c37317 in Realm::Doorbell::wait_slow (this=0x7ffff11c5f30) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:241
#2  0x00007ffff3af145f in Realm::Doorbell::wait (this=0x7ffff11c5f30) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/utils.h:81
#3  0x00007ffff3c37f8d in Realm::UnfairCondVar::wait (this=0x555555662130) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:874
#4  0x00007ffff3c63a6e in Realm::KernelThreadTaskScheduler::shutdown (this=0x555555661e10) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/runtime_impl.h:1291
#5  0x00007ffff3fc6ca9 in Realm::LocalPythonProcessor::shutdown (this=0x555555661bf0) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/runtime_impl.h:736
#6  0x00007ffff3abe104 in Realm::RuntimeImpl::wait_for_shutdown (this=0x555555607860) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/runtime_impl.h:2310
#7  0x00007ffff3ab63fe in Realm::Runtime::wait_for_shutdown (this=0x7fffffff92b8) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/runtime_impl.h:636
#8  0x00007ffff6cbe2a3 in Legion::Internal::Runtime::start (argc=3, argv=0x7fffffff9478, background=false, supply_default_mapper=true) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/cmdline.inl:29262
#9  0x00007ffff666e257 in Legion::Runtime::start (argc=3, argv=0x7fffffff9478, background=false, default_mapper=true) at /gpfs/fs1/mzalewski/repos/quickstart-collection/legate.core/legion/runtime/realm/legion_context.h:7371
#10 0x00005555555961bb in main (argc=3, argv=0x7fffffff9478) at /gpfs/fs1/mzalewski/repos/quickstart-collection/legate.core/legion/runtime/realm/legion_mapping.inl:217
(gdb) thread 2
[Switching to thread 2 (Thread 0x7fffeb062700 (LWP 24293))]
#0  0x00007ffff36450c7 in accept4 (fd=29, addr=..., addr_len=0x7fffeb05ebb4, flags=524288) at ../sysdeps/unix/sysv/linux/accept4.c:32
32	../sysdeps/unix/sysv/linux/accept4.c: No such file or directory.
(gdb) bt
#0  0x00007ffff36450c7 in accept4 (fd=29, addr=..., addr_len=0x7fffeb05ebb4, flags=524288) at ../sysdeps/unix/sysv/linux/accept4.c:32
#1  0x00007ffff1d76cd3 in ?? () from /usr/lib/x86_64-linux-gnu/libcuda.so.1
#2  0x00007ffff1e18bd6 in ?? () from /usr/lib/x86_64-linux-gnu/libcuda.so.1
#3  0x00007ffff13d46db in start_thread (arg=0x7fffeb062700) at pthread_create.c:463
#4  0x00007ffff364371f in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95
(gdb) thread 3
[Switching to thread 3 (Thread 0x7fffea761700 (LWP 24295))]
#0  syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
38	../sysdeps/unix/sysv/linux/x86_64/syscall.S: No such file or directory.
(gdb) bt
#0  syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
#1  0x00007ffff3c37317 in Realm::Doorbell::wait_slow (this=0x7fffea761630) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:241
#2  0x00007ffff3af145f in Realm::Doorbell::wait (this=0x7fffea761630) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/utils.h:81
#3  0x00007ffff3aeef74 in Realm::BackgroundWorkThread::main_loop (this=0x55555566dc00) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:166
#4  0x00007ffff3af2a26 in Realm::Thread::thread_entry_wrapper<Realm::BackgroundWorkThread, &Realm::BackgroundWorkThread::main_loop> (obj=0x55555566dc00) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/mutex.inl:97
#5  0x00007ffff3c3d9a8 in Realm::KernelThread::pthread_entry (data=0x55555566df90) at /gpfs/fs1/mzalewski/repos/quickstart-collection/legate.core/legion/bindings/python/stl_map.h:774
#6  0x00007ffff13d46db in start_thread (arg=0x7fffea761700) at pthread_create.c:463
#7  0x00007ffff364371f in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95
(gdb) thread 4
[Switching to thread 4 (Thread 0x7fffea65b700 (LWP 24296))]
#0  syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
38	in ../sysdeps/unix/sysv/linux/x86_64/syscall.S
(gdb) bt
#0  syscall () at ../sysdeps/unix/sysv/linux/x86_64/syscall.S:38
#1  0x00007ffff3c37317 in Realm::Doorbell::wait_slow (this=0x7fffea65b630) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:241
#2  0x00007ffff3af145f in Realm::Doorbell::wait (this=0x7fffea65b630) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/utils.h:81
#3  0x00007ffff3aeef74 in Realm::BackgroundWorkThread::main_loop (this=0x5555556762f0) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/timers.inl:166
#4  0x00007ffff3af2a26 in Realm::Thread::thread_entry_wrapper<Realm::BackgroundWorkThread, &Realm::BackgroundWorkThread::main_loop> (obj=0x5555556762f0) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/mutex.inl:97
#5  0x00007ffff3c3d9a8 in Realm::KernelThread::pthread_entry (data=0x55555566e6b0) at /gpfs/fs1/mzalewski/repos/quickstart-collection/legate.core/legion/bindings/python/stl_map.h:774
#6  0x00007ffff13d46db in start_thread (arg=0x7fffea65b700) at pthread_create.c:463
#7  0x00007ffff364371f in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95
(gdb) thread 9
[Switching to thread 9 (Thread 0x7ffec1fff700 (LWP 24301))]
#0  0x00007ffff13daad3 in futex_wait_cancelable (private=<optimized out>, expected=0, futex_word=0x7ffec260a5f4) at ../sysdeps/unix/sysv/linux/futex-internal.h:88
88	../sysdeps/unix/sysv/linux/futex-internal.h: No such file or directory.
(gdb) bt
#0  0x00007ffff13daad3 in futex_wait_cancelable (private=<optimized out>, expected=0, futex_word=0x7ffec260a5f4) at ../sysdeps/unix/sysv/linux/futex-internal.h:88
#1  __pthread_cond_wait_common (abstime=0x0, mutex=0x7ffec260a638, cond=0x7ffec260a5c8) at pthread_cond_wait.c:502
#2  __pthread_cond_wait (cond=0x7ffec260a5c8, mutex=0x7ffec260a638) at pthread_cond_wait.c:655
#3  0x00007ffec3a9ef6b in background_thread_sleep (tsdn=<optimized out>, interval=<optimized out>, info=<optimized out>) at src/background_thread.c:232
#4  background_work_sleep_once (ind=0, info=<optimized out>, tsdn=<optimized out>) at src/background_thread.c:307
#5  background_thread0_work (tsd=<optimized out>) at src/background_thread.c:452
#6  background_work (ind=<optimized out>, tsd=<optimized out>) at src/background_thread.c:490
#7  background_thread_entry () at src/background_thread.c:522
#8  0x00007ffff13d46db in start_thread (arg=0x7ffec1fff700) at pthread_create.c:463
#9  0x00007ffff364371f in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95
(gdb) thread 10
[Switching to thread 10 (Thread 0x7ffec1256700 (LWP 24302))]
#0  0x00007ffff13dd7c6 in futex_abstimed_wait_cancelable (private=0, abstime=0x0, expected=0, futex_word=0x7ffecc070b10) at ../sysdeps/unix/sysv/linux/futex-internal.h:205
205	../sysdeps/unix/sysv/linux/futex-internal.h: No such file or directory.
(gdb) bt
#0  0x00007ffff13dd7c6 in futex_abstimed_wait_cancelable (private=0, abstime=0x0, expected=0, futex_word=0x7ffecc070b10) at ../sysdeps/unix/sysv/linux/futex-internal.h:205
#1  do_futex_wait ([email protected]=0x7ffecc070b10, abstime=0x0) at sem_waitcommon.c:111
#2  0x00007ffff13dd8b8 in __new_sem_wait_slow ([email protected]=0x7ffecc070b10, abstime=0x0) at sem_waitcommon.c:181
#3  0x00007ffff13dd929 in __new_sem_wait ([email protected]=0x7ffecc070b10) at sem_wait.c:42
#4  0x00007fffe374d6a2 in PyThread_acquire_lock_timed.localalias () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/thread_pthread.h:486
#5  0x00007fffe3888e71 in acquire_timed () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Modules/_threadmodule.c:102
#6  0x00007fffe3888f7b in lock_PyThread_acquire_lock () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Modules/_threadmodule.c:183
#7  0x00007fffe37c4e57 in method_vectorcall_VARARGS_KEYWORDS () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Objects/unicodeobject.c:1404
#8  0x00007fffe37e50ff in _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimized out>, args=0x7ffeb7078ef0, callable=0x7fffe3201e40, tstate=0x7ffeb0000bc0) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Include/cpython/abstract.h:123
#9  PyObject_Vectorcall (kwnames=0x0, nargsf=<optimized out>, args=0x7ffeb7078ef0, callable=0x7fffe3201e40) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Include/cpython/abstract.h:123
#10 call_function (kwnames=0x0, oparg=<optimized out>, pp_stack=<synthetic pointer>, trace_info=0x7ffec1251f40, tstate=<optimized out>) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/ceval.c:5867
#11 _PyEval_EvalFrameDefault () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/ceval.c:4198
#12 0x00007fffe37a6f95 in _PyEval_EvalFrame (throwflag=0, f=0x7ffeb7078d60, tstate=0x7ffeb0000bc0) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/ceval.c:4995
#13 _PyEval_Vector (kwnames=<optimized out>, argcount=<optimized out>, args=<optimized out>, locals=0x0, con=<optimized out>, tstate=<optimized out>) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/ceval.c:5065
#14 _PyFunction_Vectorcall.localalias () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Objects/call.c:342
#15 0x00007fffe3738233 in _PyObject_VectorcallTstate (kwnames=<optimized out>, nargsf=9223372036854775808, args=0x7ffec1252168, callable=0x7fffe2f5b7f0, tstate=0x7ffeb0000bc0) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Include/cpython/abstract.h:114
#16 PyObject_VectorcallMethod.localalias () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Objects/call.c:770
#17 0x00007fffe387a8cc in _PyObject_CallMethodIdNoArgs (name=0x7fffe39c3970 <PyId__shutdown.15474>, self=<optimized out>) at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Include/cpython/abstract.h:239
#18 wait_for_thread_shutdown () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/pylifecycle.c:2823
#19 0x00007fffe38a4670 in Py_FinalizeEx.localalias () at /home/conda/feedstock_root/build_artifacts/python-split_1642146689888/work/Python/pylifecycle.c:1719
#20 0x00007ffff3fc543f in Realm::PythonInterpreter::~PythonInterpreter (this=0x7ffecc000b20, __in_chrg=<optimized out>) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/runtime_impl.h:196
#21 0x00007ffff3fc7062 in Realm::LocalPythonProcessor::destroy_interpreter (this=0x555555661bf0) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/runtime_impl.h:801
#22 0x00007ffff3fc65a8 in Realm::PythonThreadTaskScheduler::worker_terminate (this=0x555555661e10, switch_to=0x0) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/runtime_impl.h:662
#23 0x00007ffff3c6333c in Realm::ThreadedTaskScheduler::scheduler_loop (this=0x555555661e10) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/runtime_impl.h:1152
#24 0x00007ffff3fc5e77 in Realm::PythonThreadTaskScheduler::python_scheduler_loop (this=0x555555661e10) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/runtime_impl.h:395
#25 0x00007ffff3fcb10c in Realm::Thread::thread_entry_wrapper<Realm::PythonThreadTaskScheduler, &Realm::PythonThreadTaskScheduler::python_scheduler_loop> (obj=0x555555661e10) at /gpfs/fs1/mzalewski/.pyenv/versions/anaconda3-2021.11/envs/legate-dev/x86_64-conda-linux-gnu/include/c++/11.2.0/bits/threads.h:97
#26 0x00007ffff3c3d9a8 in Realm::KernelThread::pthread_entry (data=0x7ffeccaff9c0) at /gpfs/fs1/mzalewski/repos/quickstart-collection/legate.core/legion/bindings/python/stl_map.h:774
#27 0x00007ffff13d46db in start_thread (arg=0x7ffec1256700) at pthread_create.c:463
#28 0x00007ffff364371f in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95

The conda environment:

_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       1_gnu    conda-forge
_sysroot_linux-64_curr_repodata_hack 3                   h5bd9786_13    conda-forge
abseil-cpp                20210324.2           h9c3ff4c_0    conda-forge
arrow-cpp                 6.0.1           py310h500f8fe_8_cpu    conda-forge
aws-c-cal                 0.5.11               h95a6274_0    conda-forge
aws-c-common              0.6.2                h7f98852_0    conda-forge
aws-c-event-stream        0.2.7               h3541f99_13    conda-forge
aws-c-io                  0.10.5               hfb6a706_0    conda-forge
aws-checksums             0.1.11               ha31a3da_7    conda-forge
aws-sdk-cpp               1.8.186              hb4091e7_3    conda-forge
binutils_impl_linux-64    2.36.1               h193b22a_2    conda-forge
binutils_linux-64         2.36                 hf3e587d_4    conda-forge
bzip2                     1.0.8                h7f98852_4    conda-forge
c-ares                    1.18.1               h7f98852_0    conda-forge
ca-certificates           2021.10.8            ha878542_0    conda-forge
cffi                      1.15.0          py310h0fdd8cc_0    conda-forge
cuda-cccl                 11.6.55              hdc25635_0    nvidia
cuda-compiler             11.6.0               hde35cc3_0    nvidia
cuda-cudart               11.6.55              he381448_0    nvidia
cuda-cudart-dev           11.6.55              h42ad0f4_0    nvidia
cuda-cuobjdump            11.6.55              h9dd2d0c_0    nvidia
cuda-cuxxfilt             11.6.55              h69de05d_0    nvidia
cuda-driver-dev           11.6.55                       0    nvidia
cuda-libraries-dev        11.6.0               hde35cc3_0    nvidia
cuda-nvcc                 11.6.55              h5758ece_0    nvidia
cuda-nvprune              11.6.55              h3791f62_0    nvidia
cuda-nvrtc                11.6.55              hc54fff9_0    nvidia
cuda-nvrtc-dev            11.6.55              h42ad0f4_0    nvidia
cudatoolkit               11.6.0              habf752d_10    conda-forge
cutensor                  1.4.0.6              h7537e88_1    conda-forge
gcc                       11.2.0               h702ea55_4    conda-forge
gcc_impl_linux-64         11.2.0              h82a94d6_12    conda-forge
gcc_linux-64              11.2.0               h39a9532_4    conda-forge
gflags                    2.2.2             he1b5a44_1004    conda-forge
gfortran                  11.2.0               h8811e0c_4    conda-forge
gfortran_impl_linux-64    11.2.0              h7a446d4_12    conda-forge
gfortran_linux-64         11.2.0               h777b47f_4    conda-forge
glog                      0.5.0                h48cff8f_0    conda-forge
grpc-cpp                  1.42.0               ha1441d3_1    conda-forge
gxx                       11.2.0               h702ea55_4    conda-forge
gxx_impl_linux-64         11.2.0              h82a94d6_12    conda-forge
kernel-headers_linux-64   3.10.0              h4a8ded7_13    conda-forge
krb5                      1.19.2               hcc1bbae_3    conda-forge
ld_impl_linux-64          2.36.1               hea4e1c9_2    conda-forge
libblas                   3.9.0           13_linux64_openblas    conda-forge
libbrotlicommon           1.0.9                h7f98852_6    conda-forge
libbrotlidec              1.0.9                h7f98852_6    conda-forge
libbrotlienc              1.0.9                h7f98852_6    conda-forge
libcblas                  3.9.0           13_linux64_openblas    conda-forge
libcublas                 11.8.1.74            h1e58c10_0    nvidia
libcublas-dev             11.8.1.74            h7a51e1f_0    nvidia
libcufft                  10.7.0.55            h563f203_0    nvidia
libcufft-dev              10.7.0.55            h05eb8d0_0    nvidia
libcurand                 10.2.9.55            h7c349da_0    nvidia
libcurand-dev             10.2.9.55            hd2e71f0_0    nvidia
libcurl                   7.81.0               h2574ce0_0    conda-forge
libcusolver               11.3.2.107           hc875929_0    nvidia
libcusolver-dev           11.3.2.107           h78cb71c_0    nvidia
libcusparse               11.7.1.55            h9a152cf_0    nvidia
libcusparse-dev           11.7.1.55            h02e612c_0    nvidia
libedit                   3.1.20191231         he28a2e2_2    conda-forge
libev                     4.33                 h516909a_1    conda-forge
libevent                  2.1.10               h9b69904_4    conda-forge
libffi                    3.4.2                h7f98852_5    conda-forge
libgcc-devel_linux-64     11.2.0              h0952999_12    conda-forge
libgcc-ng                 11.2.0              h1d223b6_12    conda-forge
libgfortran-ng            11.2.0              h69a702a_11    conda-forge
libgfortran5              11.2.0              h5c6108e_11    conda-forge
libgomp                   11.2.0              h1d223b6_12    conda-forge
liblapack                 3.9.0           13_linux64_openblas    conda-forge
libnghttp2                1.46.0               h812cca2_0    conda-forge
libnpp                    11.6.0.55            hdb0c674_0    nvidia
libnpp-dev                11.6.0.55            h0163868_0    nvidia
libnsl                    2.0.0                h7f98852_0    conda-forge
libnvjpeg                 11.6.0.55            h6f17e28_0    nvidia
libnvjpeg-dev             11.6.0.55            h0163868_0    nvidia
libopenblas               0.3.18          pthreads_h8fe5266_0    conda-forge
libprotobuf               3.19.3               h780b84a_0    conda-forge
libsanitizer              11.2.0              he4da1e4_12    conda-forge
libssh2                   1.10.0               ha56f1ee_2    conda-forge
libstdcxx-devel_linux-64  11.2.0              h0952999_12    conda-forge
libstdcxx-ng              11.2.0              he4da1e4_12    conda-forge
libthrift                 0.15.0               he6d91bd_1    conda-forge
libutf8proc               2.7.0                h7f98852_0    conda-forge
libuuid                   2.32.1            h7f98852_1000    conda-forge
libzlib                   1.2.11            h36c2ea0_1013    conda-forge
lz4-c                     1.9.3                h9c3ff4c_1    conda-forge
ncurses                   6.2                  h58526e2_4    conda-forge
numpy                     1.22.1          py310h454958d_0    conda-forge
openssl                   1.1.1l               h7f98852_0    conda-forge
opt_einsum                3.3.0              pyhd8ed1ab_1    conda-forge
orc                       1.7.2                h1be678f_0    conda-forge
parquet-cpp               1.5.1                         2    conda-forge
pip                       21.3.1             pyhd8ed1ab_0    conda-forge
pyarrow                   6.0.1           py310h1a3fb3d_8_cpu    conda-forge
pycparser                 2.21               pyhd8ed1ab_0    conda-forge
python                    3.10.2          h62f1059_0_cpython    conda-forge
python_abi                3.10                    2_cp310    conda-forge
re2                       2021.11.01           h9c3ff4c_0    conda-forge
readline                  8.1                  h46c0cb4_0    conda-forge
s2n                       1.0.10               h9b69904_0    conda-forge
setuptools                60.5.0          py310hff52083_0    conda-forge
snappy                    1.1.8                he1b5a44_3    conda-forge
sqlite                    3.37.0               h9cd32fc_0    conda-forge
sysroot_linux-64          2.17                h4a8ded7_13    conda-forge
tk                        8.6.11               h27826a3_1    conda-forge
tzdata                    2021e                he74cb21_0    conda-forge
wheel                     0.37.1             pyhd8ed1ab_0    conda-forge
xz                        5.2.5                h516909a_1    conda-forge
zlib                      1.2.11            h36c2ea0_1013    conda-forge
zstd                      1.5.2                ha95c52a_0    conda-forge

@m3vaz tried it with a slightly different but quite similar environment, and he observed the same issue.

Problem

Using a scalar in allclose raises AttributeError: PROJ_1D_1D_.

To reproduce

1. step 1: create test.py

   from legate import numpy as lnp
   import numpy as realnp
   
   # vanilla numpy works
   a = realnp.full(10, 1e-1)
   print(realnp.allclose(a, 1e-1))
   
   # legate numpy not working
   la = lnp.full(10, 1e-1)
   print(lnp.allclose(la, 1e-1))
   

2. step 2: run test.py with legate --cpus 1 ./test.py -lg:numpy:test

Output

The first part that uses vanilla NumPy prints True.

The second part that uses Legate NumPy raises:

Traceback (most recent call last):
  File "<prefix>/lib/python3.8/site-packages/legion_top.py", line 408, in legion_python_main
    run_path(args[start], run_name='__main__')
  File "<prefix>/lib/python3.8/site-packages/legion_top.py", line 200, in run_path
    exec(code, module.__dict__, module.__dict__)
  File "./test.py", line 10, in <module>
    print(lnp.allclose(la, 1e-1))
  File "<prefix>/lib/python3.8/site-packages/legate/numpy/module.py", line 459, in allclose
    return ndarray.perform_binary_reduction(
  File "<prefix>/lib/python3.8/site-packages/legate/numpy/array.py", line 2068, in perform_binary_reduction
    dst._thunk.binary_reduction(
  File "<prefix>/lib/python3.8/site-packages/legate/numpy/deferred.py", line 5167, in binary_reduction
    ) = self.runtime.compute_broadcast_transform(
  File "<prefix>/lib/python3.8/site-packages/legate/numpy/runtime.py", line 2500, in compute_broadcast_transform
    self.first_proj_id + getattr(NumPyProjCode, proj_name),
  File "<prefix>/lib/python3.8/enum.py", line 384, in __getattr__
    raise AttributeError(name) from None
AttributeError: PROJ_1D_1D_

Expected behavior

Working like vanilla NumPy, or raising an exception with a clear message of what is not supported.

Documenting a difficult day of fighting with Apple compilers after an OS upgrade. The high level bit is look here if you are experiencing hangs during cuNumeric builds, specifically as part of the TBLIS sub-build.

Symptoms:

I noticed various parts of the TBLIS build would get stuck, such as after this line:

    -- cunumeric: ENV{CC}="/usr/local/opt/llvm/bin/clang"
    -- cunumeric: ENV{CXX}="/usr/local/opt/llvm/bin/clang++"

or this line:

   -- Build files have been written to: /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build
    [0/56] Building tblis
    Making install in src/external/tci
    make[1]: Entering directory '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-src/src/external/tci'
      CC       tci/barrier.lo
      CC       tci/context.lo
      CC       tci/mutex.lo
      CC       tci/parallel.lo
      CC       tci/slot.lo
      CC       tci/work_item.lo
      CC       tci/communicator.lo
      CC       tci/task_set.lo
      CXXLD    lib/libtci.la
    make[2]: Entering directory '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-src/src/external/tci'
     ./install-sh -c -d '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib'
     ./install-sh -c -d '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/include'
     /bin/sh ./libtool   --mode=install /usr/bin/install -c   lib/libtci.la '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib'
     ./install-sh -c -d '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/include/tci'
    libtool: install: /usr/bin/install -c lib/.libs/libtci.0.dylib /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib/libtci.0.dylib
    libtool: install: (cd /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib && { ln -s -f libtci.0.dylib libtci.dylib || { rm -f libtci.dylib && ln -s libtci.0.dylib libtci.dylib; }; })
     /usr/bin/install -c -m 644  tci/tci_config.h tci/tci_global.h tci/barrier.h tci/communicator.h tci/context.h tci/mutex.h tci/parallel.h tci/pipeline.h tci/slot.h tci/task_set.h tci/work_item.h tci/yield.h '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/include/tci'
    libtool: install: /usr/bin/install -c lib/.libs/libtci.lai /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib/libtci.la
     /usr/bin/install -c -m 644  tci.h '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/include/.'
    libtool: install: /usr/bin/install -c lib/.libs/libtci.a /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib/libtci.a
    libtool: install: chmod 644 /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib/libtci.a
    libtool: install: ranlib /Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-build/lib/libtci.a
    make[2]: Leaving directory '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-src/src/external/tci'
    make[1]: Leaving directory '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-src/src/external/tci'
    make[1]: Entering directory '/Users/rohany/Documents/nvidia/cunumeric/_skbuild/macosx-13.0-x86_64-3.9/cmake-build/_deps/tblis-src'

At this point, things started to act strange in my laptop. Commands like gcc --version would hang. Interestingly then, clang could generate valid executables -- running clang on a just int main() { return 0; } would generate a binary that would hang before entering main. This weirdness would then go away once I restarted my computer. However, the build would get stuck in the same place.

I lucked onto the following solution, which is really a workaround because the cuNumeric build still runs into the above problem for me.

• First, I reinstalled x-code command line tools (there are several resources about how to do this).
• After this, a build of TBLIS outside of the cuNumeric build did in fact complete (using the same configure that cuNumeric emits, followed by make -j; make install.
• Then, I pointed cunumeric at this build with --with-tblis ... to install.py.

Even though the external TBLIS build completed, running the cuNumeric build that compiles its own TBLIS results in putting my laptop back in this broken state.

NumPy and cuNumeric behave differently for the following cases. Some of the cases need to be fixed while the others are expected divergences.

Case-1

NEGATIVE_DTYPE = ["h", "i", "H", "I", "?", "b", "B"]
for dtype in NEGATIVE_DTYPE：
        size = (5, 5, 5)
        arr = np.random.random(size) * 10 + 2
        arr_np = np.array(arr, dtype=dtype)
        arr_num = num.array(arr_np)
        out_np = np.prod(arr_np)      # Numpy return product of all datas
        out_num = num.prod(arr_num)   # cuNumeric return an array with a different data

Case-2

        arr = (num.random.rand(5, 5) * 10 + 2) + (num.random.rand(5, 5) * 10 * 1.0j + 0.2j)
        arr_np = np.array(arr, dtype=complex128)
        arr_num = num.array(arr_np)
        out_np = np.prod(arr_np)
        out_num = num.prod(arr_num)

They have diffrent output data.

Case-3

        arr = [[1, 2], [3, 4]]
        initial_value = [3]

        out_num = num.prod(arr, initial=initial_value)  
        out_np = np.prod(arr, initial=initial_value)

cuNumeric returns array(72). Numpy raises ValueError: Input object to FillWithScalar is not a scalar

Case-4

SIZE_E = [
    (1, 1),
    (1, DIM),
    (DIM, 1),
    (1, 1, 1),
    (DIM, 1, 1),
    (1, DIM, 1),
    (1, 1, DIM)
]
for size in SIZE_E:
        arr_np = np.random.random(size)
        arr_num = num.array(arr_np)
        ndim = arr_np.ndim
        for axis in range(-ndim + 1, ndim, 1):
            out_np = np.prod(arr_np, axis=axis, keepdims=True)
            out_num = num.prod(arr_num, axis=axis, keepdims=True)

Error is :

  # in cunumeric/deferred/unary_reduction:
  # if lhs_array.size == 1:
  #     > assert axes is None or len(axes) == rhs_array.ndim - (
  #         0 if keepdims else lhs_array.ndim
  #     )
  # E    AssertionError

NumPy and cuNumeric behave differently for the following cases. Some of the cases need to be fixed while the others are expected divergences.

Case-1 A = mk_0to1_array(num, (2, 2)) B = mk_0to1_array(num, (2, 2)) C = mk_0to1_array(num, (2, 2)) arrays = [A, B, C] out = num.zeros((2, 1)) num.linalg.multi_dot(self.arrays, out=out)

In Numpy, it raises ValueError In cuNumeric, it raises AssertionError

Case-2 A = mk_0to1_array(num, (2, 2)) B = mk_0to1_array(num, (2, 2)) C = mk_0to1_array(num, (2, 2)) arrays = [A, B, C] out = num.zeros((2, 2), dtype=np.float32)

In Numpy, it raises ValueError In cuNumeric, it pass

Case-3 A = mk_0to1_array(num, (2, 2)) B = mk_0to1_array(num, (2, 2)) C = mk_0to1_array(num, (2, 2)) arrays = [A, B, C] out = num.zeros((2, 2), dtype=np.int64)

In Numpy, it raises ValueError In cuNumeric, it raises TypeError: Unsupported type: int64

Case-4 A = mk_0to1_array(num, (5, 3)) B = mk_0to1_array(num, (3, 2)) out = np.zeros((5, 2), dtype=np.float32) np.dot(A, B, out=out)

In Numpy, it raises ValueError In cuNumeric, it pass

Case-5 A = mk_0to1_array(num, (5, 3)) B = mk_0to1_array(num, (3, 2)) out = np.zeros((5, 2), dtype=np.int64) np.dot(A, B, out=out)

In Numpy, it raises ValueError In cuNumeric, it raises TypeError: Unsupported type: int64

test command: +LEGATE_TEST=1 /opt/conda/envs/legate/bin/legate /legate/test/tests/integration/test_dot.py -cunumeric:test --fbmem 4096 --gpus 1 --gpu-bind 0 -v [PASS] (GPU) tests/integration/test_dot.py

Below test trigger runtime Error. If we remove this test, the runtime Error goes aways. tests/integration/test_dot.py::TestDotErrors::test_out_invalid_dtype[(dtype=<class 'numpy.int64'>)] XFAIL [100%] Error message:
======================== 31 passed, 2 xfailed in 3.18s ========================= Exception ignored in: <function RegionField.del at 0x7fc08c0e01f0> Traceback (most recent call last): File "/opt/conda/envs/legate/lib/python3.9/site-packages/legate/core/store.py", line 126, in del File "/opt/conda/envs/legate/lib/python3.9/site-packages/legate/core/store.py", line 251, in detach_external_allocation File "/opt/conda/envs/legate/lib/python3.9/site-packages/legate/core/runtime.py", line 570, in detach_external_allocation File "/opt/conda/envs/legate/lib/python3.9/site-packages/legate/core/runtime.py", line 555, in _remove_allocation File "/opt/conda/envs/legate/lib/python3.9/site-packages/legate/core/runtime.py", line 550, in _remove_attachment RuntimeError: Unable to find attachment to remove

This PR is a re-factorization of the cufft wrapper task in order to

remove the 3D-FFT limit
allow for data parallel execution if feasible

NOTE: This is a new PR based on #700 which had trouble with the CI due to the branch name.