Ejemplo n.º 1
0
def test_pool_with_memmap_array_view(factory, tmpdir):
    """Check that subprocess can access and update shared memory array"""
    assert_array_equal = np.testing.assert_array_equal

    # Fork the subprocess before allocating the objects to be passed
    pool_temp_folder = tmpdir.mkdir('pool').strpath
    p = factory(10, max_nbytes=2, temp_folder=pool_temp_folder)
    try:

        filename = tmpdir.join('test.mmap').strpath
        a = np.memmap(filename, dtype=np.float32, shape=(3, 5), mode='w+')
        a.fill(1.0)

        # Create an ndarray view on the memmap instance
        a_view = np.asarray(a)
        assert not isinstance(a_view, np.memmap)
        assert has_shareable_memory(a_view)

        p.map(inplace_double, [(a_view, (i, j), 1.0) for i in range(a.shape[0])
                               for j in range(a.shape[1])])

        # Both a and the a_view have been updated
        assert_array_equal(a, 2 * np.ones(a.shape))
        assert_array_equal(a_view, 2 * np.ones(a.shape))

        # Passing memmap array view to the pool should not trigger the
        # creation of new files on the FS
        assert os.listdir(pool_temp_folder) == []

    finally:
        p.terminate()
        del p
Ejemplo n.º 2
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def test_pool_with_memmap_array_view(factory, tmpdir):
    """Check that subprocess can access and update shared memory array"""
    assert_array_equal = np.testing.assert_array_equal

    # Fork the subprocess before allocating the objects to be passed
    pool_temp_folder = tmpdir.mkdir('pool').strpath
    p = factory(10, max_nbytes=2, temp_folder=pool_temp_folder)
    try:

        filename = tmpdir.join('test.mmap').strpath
        a = np.memmap(filename, dtype=np.float32, shape=(3, 5), mode='w+')
        a.fill(1.0)

        # Create an ndarray view on the memmap instance
        a_view = np.asarray(a)
        assert not isinstance(a_view, np.memmap)
        assert has_shareable_memory(a_view)

        p.map(inplace_double, [(a_view, (i, j), 1.0)
                               for i in range(a.shape[0])
                               for j in range(a.shape[1])])

        # Both a and the a_view have been updated
        assert_array_equal(a, 2 * np.ones(a.shape))
        assert_array_equal(a_view, 2 * np.ones(a.shape))

        # Passing memmap array view to the pool should not trigger the
        # creation of new files on the FS
        assert os.listdir(pool_temp_folder) == []

    finally:
        p.terminate()
        del p
Ejemplo n.º 3
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def test_high_dimension_memmap_array_reducing(tmpdir):
    assert_array_equal = np.testing.assert_array_equal

    filename = tmpdir.join('test.mmap').strpath

    # Create a high dimensional memmap
    a = np.memmap(filename,
                  dtype=np.float64,
                  shape=(100, 15, 15, 3),
                  mode='w+')
    a[:] = np.arange(100 * 15 * 15 * 3).reshape(a.shape)

    # Create some slices/indices at various dimensions
    b = a[0:10]
    c = a[:, 5:10]
    d = a[:, :, :, 0]
    e = a[1:3:4]

    # Array reducer with auto dumping disabled
    reducer = ArrayMemmapForwardReducer(None, tmpdir.strpath, 'c', True)

    def reconstruct_array_or_memmap(x):
        cons, args = reducer(x)
        return cons(*args)

    a_reconstructed = reconstruct_array_or_memmap(a)
    assert has_shareable_memory(a_reconstructed)
    assert isinstance(a_reconstructed, np.memmap)
    assert_array_equal(a_reconstructed, a)

    b_reconstructed = reconstruct_array_or_memmap(b)
    assert has_shareable_memory(b_reconstructed)
    assert_array_equal(b_reconstructed, b)

    c_reconstructed = reconstruct_array_or_memmap(c)
    assert has_shareable_memory(c_reconstructed)
    assert_array_equal(c_reconstructed, c)

    d_reconstructed = reconstruct_array_or_memmap(d)
    assert has_shareable_memory(d_reconstructed)
    assert_array_equal(d_reconstructed, d)

    e_reconstructed = reconstruct_array_or_memmap(e)
    assert has_shareable_memory(e_reconstructed)
    assert_array_equal(e_reconstructed, e)
Ejemplo n.º 4
0
def test_high_dimension_memmap_array_reducing(tmpdir):
    assert_array_equal = np.testing.assert_array_equal

    filename = tmpdir.join('test.mmap').strpath

    # Create a high dimensional memmap
    a = np.memmap(filename, dtype=np.float64, shape=(100, 15, 15, 3),
                  mode='w+')
    a[:] = np.arange(100 * 15 * 15 * 3).reshape(a.shape)

    # Create some slices/indices at various dimensions
    b = a[0:10]
    c = a[:, 5:10]
    d = a[:, :, :, 0]
    e = a[1:3:4]

    def reconstruct_memmap(x):
        cons, args = reduce_memmap(x)
        res = cons(*args)
        return res

    a_reconstructed = reconstruct_memmap(a)
    assert has_shareable_memory(a_reconstructed)
    assert isinstance(a_reconstructed, np.memmap)
    assert_array_equal(a_reconstructed, a)

    b_reconstructed = reconstruct_memmap(b)
    assert has_shareable_memory(b_reconstructed)
    assert_array_equal(b_reconstructed, b)

    c_reconstructed = reconstruct_memmap(c)
    assert has_shareable_memory(c_reconstructed)
    assert_array_equal(c_reconstructed, c)

    d_reconstructed = reconstruct_memmap(d)
    assert has_shareable_memory(d_reconstructed)
    assert_array_equal(d_reconstructed, d)

    e_reconstructed = reconstruct_memmap(e)
    assert has_shareable_memory(e_reconstructed)
    assert_array_equal(e_reconstructed, e)
Ejemplo n.º 5
0
def test_memmapping_pool_for_large_arrays_in_return(factory, tmpdir):
    """Check that large arrays are not copied in memory in return"""
    assert_array_equal = np.testing.assert_array_equal

    # Build an array reducers that automaticaly dump large array content
    # but check that the returned datastructure are regular arrays to avoid
    # passing a memmap array pointing to a pool controlled temp folder that
    # might be confusing to the user

    # The MemmappingPool user can always return numpy.memmap object explicitly
    # to avoid memory copy
    p = factory(3, max_nbytes=10, temp_folder=tmpdir.strpath)
    try:
        res = p.apply_async(np.ones, args=(1000, ))
        large = res.get()
        assert not has_shareable_memory(large)
        assert_array_equal(large, np.ones(1000))
    finally:
        p.terminate()
        del p
Ejemplo n.º 6
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def test_memmapping_pool_for_large_arrays_in_return(factory, tmpdir):
    """Check that large arrays are not copied in memory in return"""
    assert_array_equal = np.testing.assert_array_equal

    # Build an array reducers that automaticaly dump large array content
    # but check that the returned datastructure are regular arrays to avoid
    # passing a memmap array pointing to a pool controlled temp folder that
    # might be confusing to the user

    # The MemmappingPool user can always return numpy.memmap object explicitly
    # to avoid memory copy
    p = factory(3, max_nbytes=10, temp_folder=tmpdir.strpath)
    try:
        res = p.apply_async(np.ones, args=(1000,))
        large = res.get()
        assert not has_shareable_memory(large)
        assert_array_equal(large, np.ones(1000))
    finally:
        p.terminate()
        del p
Ejemplo n.º 7
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def test_workaround_against_bad_memmap_with_copied_buffers(factory, tmpdir):
    """Check that memmaps with a bad buffer are returned as regular arrays

    Unary operations and ufuncs on memmap instances return a new memmap
    instance with an in-memory buffer (probably a numpy bug).
    """
    assert_array_equal = np.testing.assert_array_equal

    p = factory(3, max_nbytes=10, temp_folder=tmpdir.strpath)
    try:
        # Send a complex, large-ish view on a array that will be converted to
        # a memmap in the worker process
        a = np.asarray(np.arange(6000).reshape((1000, 2, 3)),
                       order='F')[:, :1, :]

        # Call a non-inplace multiply operation on the worker and memmap and
        # send it back to the parent.
        b = p.apply_async(_worker_multiply, args=(a, 3)).get()
        assert not has_shareable_memory(b)
        assert_array_equal(b, 3 * a)
    finally:
        p.terminate()
        del p
Ejemplo n.º 8
0
def test_workaround_against_bad_memmap_with_copied_buffers(factory, tmpdir):
    """Check that memmaps with a bad buffer are returned as regular arrays

    Unary operations and ufuncs on memmap instances return a new memmap
    instance with an in-memory buffer (probably a numpy bug).
    """
    assert_array_equal = np.testing.assert_array_equal

    p = factory(3, max_nbytes=10, temp_folder=tmpdir.strpath)
    try:
        # Send a complex, large-ish view on a array that will be converted to
        # a memmap in the worker process
        a = np.asarray(np.arange(6000).reshape((1000, 2, 3)),
                       order='F')[:, :1, :]

        # Call a non-inplace multiply operation on the worker and memmap and
        # send it back to the parent.
        b = p.apply_async(_worker_multiply, args=(a, 3)).get()
        assert not has_shareable_memory(b)
        assert_array_equal(b, 3 * a)
    finally:
        p.terminate()
        del p
Ejemplo n.º 9
0
def test_memmap_based_array_reducing(tmpdir):
    """Check that it is possible to reduce a memmap backed array"""
    assert_array_equal = np.testing.assert_array_equal
    filename = tmpdir.join('test.mmap').strpath

    # Create a file larger than what will be used by a
    buffer = np.memmap(filename, dtype=np.float64, shape=500, mode='w+')

    # Fill the original buffer with negative markers to detect over of
    # underflow in case of test failures
    buffer[:] = -1.0 * np.arange(buffer.shape[0], dtype=buffer.dtype)
    buffer.flush()

    # Memmap a 2D fortran array on a offseted subsection of the previous
    # buffer
    a = np.memmap(filename,
                  dtype=np.float64,
                  shape=(3, 5, 4),
                  mode='r+',
                  order='F',
                  offset=4)
    a[:] = np.arange(60).reshape(a.shape)

    # Build various views that share the buffer with the original memmap

    # b is an memmap sliced view on an memmap instance
    b = a[1:-1, 2:-1, 2:4]

    # c and d are array views
    c = np.asarray(b)
    d = c.T

    # Array reducer with auto dumping disabled
    reducer = ArrayMemmapReducer(None, tmpdir.strpath, 'c')

    def reconstruct_array(x):
        cons, args = reducer(x)
        return cons(*args)

    def reconstruct_memmap(x):
        cons, args = reduce_memmap(x)
        return cons(*args)

    # Reconstruct original memmap
    a_reconstructed = reconstruct_memmap(a)
    assert has_shareable_memory(a_reconstructed)
    assert isinstance(a_reconstructed, np.memmap)
    assert_array_equal(a_reconstructed, a)

    # Reconstruct strided memmap view
    b_reconstructed = reconstruct_memmap(b)
    assert has_shareable_memory(b_reconstructed)
    assert_array_equal(b_reconstructed, b)

    # Reconstruct arrays views on memmap base
    c_reconstructed = reconstruct_array(c)
    assert not isinstance(c_reconstructed, np.memmap)
    assert has_shareable_memory(c_reconstructed)
    assert_array_equal(c_reconstructed, c)

    d_reconstructed = reconstruct_array(d)
    assert not isinstance(d_reconstructed, np.memmap)
    assert has_shareable_memory(d_reconstructed)
    assert_array_equal(d_reconstructed, d)

    # Test graceful degradation on fake memmap instances with in-memory
    # buffers
    a3 = a * 3
    assert not has_shareable_memory(a3)
    a3_reconstructed = reconstruct_memmap(a3)
    assert not has_shareable_memory(a3_reconstructed)
    assert not isinstance(a3_reconstructed, np.memmap)
    assert_array_equal(a3_reconstructed, a * 3)

    # Test graceful degradation on arrays derived from fake memmap instances
    b3 = np.asarray(a3)
    assert not has_shareable_memory(b3)

    b3_reconstructed = reconstruct_array(b3)
    assert isinstance(b3_reconstructed, np.ndarray)
    assert not has_shareable_memory(b3_reconstructed)
    assert_array_equal(b3_reconstructed, b3)
Ejemplo n.º 10
0
def _worker_multiply(a, n_times):
    """Multiplication function to be executed by subprocess"""
    assert has_shareable_memory(a)
    return a * n_times
Ejemplo n.º 11
0
def test_memmap_based_array_reducing(tmpdir):
    """Check that it is possible to reduce a memmap backed array"""
    assert_array_equal = np.testing.assert_array_equal
    filename = tmpdir.join('test.mmap').strpath

    # Create a file larger than what will be used by a
    buffer = np.memmap(filename, dtype=np.float64, shape=500, mode='w+')

    # Fill the original buffer with negative markers to detect over of
    # underflow in case of test failures
    buffer[:] = - 1.0 * np.arange(buffer.shape[0], dtype=buffer.dtype)
    buffer.flush()

    # Memmap a 2D fortran array on a offseted subsection of the previous
    # buffer
    a = np.memmap(filename, dtype=np.float64, shape=(3, 5, 4),
                  mode='r+', order='F', offset=4)
    a[:] = np.arange(60).reshape(a.shape)

    # Build various views that share the buffer with the original memmap

    # b is an memmap sliced view on an memmap instance
    b = a[1:-1, 2:-1, 2:4]

    # c and d are array views
    c = np.asarray(b)
    d = c.T

    # Array reducer with auto dumping disabled
    reducer = ArrayMemmapReducer(None, tmpdir.strpath, 'c')

    def reconstruct_array(x):
        cons, args = reducer(x)
        return cons(*args)

    def reconstruct_memmap(x):
        cons, args = reduce_memmap(x)
        return cons(*args)

    # Reconstruct original memmap
    a_reconstructed = reconstruct_memmap(a)
    assert has_shareable_memory(a_reconstructed)
    assert isinstance(a_reconstructed, np.memmap)
    assert_array_equal(a_reconstructed, a)

    # Reconstruct strided memmap view
    b_reconstructed = reconstruct_memmap(b)
    assert has_shareable_memory(b_reconstructed)
    assert_array_equal(b_reconstructed, b)

    # Reconstruct arrays views on memmap base
    c_reconstructed = reconstruct_array(c)
    assert not isinstance(c_reconstructed, np.memmap)
    assert has_shareable_memory(c_reconstructed)
    assert_array_equal(c_reconstructed, c)

    d_reconstructed = reconstruct_array(d)
    assert not isinstance(d_reconstructed, np.memmap)
    assert has_shareable_memory(d_reconstructed)
    assert_array_equal(d_reconstructed, d)

    # Test graceful degradation on fake memmap instances with in-memory
    # buffers
    a3 = a * 3
    assert not has_shareable_memory(a3)
    a3_reconstructed = reconstruct_memmap(a3)
    assert not has_shareable_memory(a3_reconstructed)
    assert not isinstance(a3_reconstructed, np.memmap)
    assert_array_equal(a3_reconstructed, a * 3)

    # Test graceful degradation on arrays derived from fake memmap instances
    b3 = np.asarray(a3)
    assert not has_shareable_memory(b3)

    b3_reconstructed = reconstruct_array(b3)
    assert isinstance(b3_reconstructed, np.ndarray)
    assert not has_shareable_memory(b3_reconstructed)
    assert_array_equal(b3_reconstructed, b3)
Ejemplo n.º 12
0
def _worker_multiply(a, n_times):
    """Multiplication function to be executed by subprocess"""
    assert has_shareable_memory(a)
    return a * n_times