Output warning before changing n_jobs value #1114
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Azure Pipelines / lmcinnes.umap
failed
Apr 20, 2024 in 41m 36s
Build #20240420.1 had test failures
Details
- Failed: 14 (0.56%)
- Passed: 1,830 (73.32%)
- Other: 652 (26.12%)
- Total: 2,496
- 3143 of 5011 lines covered (62.72%)
Annotations
Check failure on line 304 in Build log
azure-pipelines / lmcinnes.umap
Build log #L304
1 test(s) failed, 208 test(s) collected.
Check failure on line 396 in Build log
azure-pipelines / lmcinnes.umap
Build log #L396
Cmd.exe exited with code '1'.
Check failure on line 304 in Build log
azure-pipelines / lmcinnes.umap
Build log #L304
1 test(s) failed, 208 test(s) collected.
Check failure on line 393 in Build log
azure-pipelines / lmcinnes.umap
Build log #L393
Bash exited with code '1'.
Check failure on line 1 in umap/tests/test_umap_on_iris.py::test_precomputed_transform_on_iris
azure-pipelines / lmcinnes.umap
umap/tests/test_umap_on_iris.py::test_precomputed_transform_on_iris
iris = {'data': array([[5.1, 3.5, 1.4, 0.2],
[4.9, 3. , 1.4, 0.2],
[4.7, 3.2, 1.3, 0.2],
[4.6, 3.1, 1.5,... width (cm)', 'petal length (cm)', 'petal width (cm)'], 'filename': 'iris.csv', 'data_module': 'sklearn.datasets.data'}
iris_selection = array([ True, True, True, True, True, True, True, True, True,
False, True, False, True, True, True,... True, True, True, True, True, True, True, False, False,
True, True, True, False, True, False])
def test_precomputed_transform_on_iris(iris, iris_selection):
data = iris.data[iris_selection]
distance_matrix = squareform(pdist(data))
fitter = UMAP(
n_neighbors=10,
min_dist=0.01,
random_state=42,
n_epochs=100,
metric="precomputed",
).fit(distance_matrix)
new_data = iris.data[~iris_selection]
new_distance_matrix = cdist(new_data, data)
embedding = fitter.transform(new_distance_matrix)
trust = trustworthiness(new_data, embedding, n_neighbors=10)
> assert (
trust >= 0.85
), "Insufficiently trustworthy transform for" "iris dataset: {}".format(trust)
E AssertionError: Insufficiently trustworthy transform foriris dataset: 0.7944588744588744
E assert 0.7944588744588744 >= 0.85
umap/tests/test_umap_on_iris.py:168: AssertionErrorRaw output
/Users/runner/work/1/s/umap/tests/test_umap_on_iris.py:168: AssertionError: Insufficiently trustworthy transform foriris dataset: 0.7944588744588744
Check failure on line 1 in umap/tests/test_plot.py::test_plot_runs_at_all
azure-pipelines / lmcinnes.umap
umap/tests/test_plot.py::test_plot_runs_at_all
mapper = UMAP(n_epochs=100, tqdm_kwds={'bar_format': '{desc}: {percentage:3.0f}%| {bar} {n_fmt}/{total_fmt} [{elapsed}]', 'desc': 'Epochs completed', 'disable': True})
iris = {'data': array([[5.1, 3.5, 1.4, 0.2],
[4.9, 3. , 1.4, 0.2],
[4.7, 3.2, 1.3, 0.2],
[4.6, 3.1, 1.5,... width (cm)', 'petal length (cm)', 'petal width (cm)'], 'filename': 'iris.csv', 'data_module': 'sklearn.datasets.data'}
iris_selection = array([ True, True, True, True, True, True, True, True, True,
False, True, False, True, True, True,... True, True, True, True, True, True, True, False, False,
True, True, True, False, True, False])
@plot_only
def test_plot_runs_at_all(mapper, iris, iris_selection):
from umap import plot as umap_plot
umap_plot.points(mapper)
umap_plot.points(mapper, labels=iris.target)
umap_plot.points(mapper, values=iris.data[:, 0])
umap_plot.points(mapper, labels=iris.target, subset_points=iris_selection)
umap_plot.points(mapper, values=iris.data[:, 0], subset_points=iris_selection)
umap_plot.points(mapper, theme="fire")
> umap_plot.diagnostic(mapper, diagnostic_type="all")
umap/tests/test_plot.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
umap/plot.py:1202: in diagnostic
diagnostic(
umap/plot.py:1124: in diagnostic
accuracy = _nhood_compare(
../../../hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:468: in _compile_for_args
error_rewrite(e, 'typing')
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
e = TypingError('Failed in nopython mode pipeline (step: nopython frontend)\nNo implementation of function Function(<funct...(indices_left.shape[0]):\n intersection_size = np.intersect1d(indices_left[i], indices_right[i], \n ^\n')
issue_type = 'typing'
def error_rewrite(e, issue_type):
"""
Rewrite and raise Exception `e` with help supplied based on the
specified issue_type.
"""
if config.SHOW_HELP:
help_msg = errors.error_extras[issue_type]
e.patch_message('\n'.join((str(e).rstrip(), help_msg)))
if config.FULL_TRACEBACKS:
raise e
else:
> raise e.with_traceback(None)
E numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
E No implementation of function Function(<function intersect1d at 0x1084ca170>) found for signature:
E
E >>> intersect1d(array(int32, 1d, C), array(int32, 1d, C), assume_unique=Literal[bool](True))
E
E There are 2 candidate implementations:
E - Of which 2 did not match due to:
E Overload in function 'jit_np_intersect1d': File: numba/np/arraymath.py: Line 3586.
E With argument(s): '(array(int32, 1d, C), array(int32, 1d, C), assume_unique=bool)':
E Rejected as the implementation raised a specific error:
E TypingError: got an unexpected keyword argument 'assume_unique'
E raised from /Users/runner/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/typing/templates.py:784
E
E During: resolving callee type: Function(<function intersect1d at 0x1084ca170>)
E During: typing of call at /Users/runner/work/1/s/umap/plot.py (209)
E
E
E File "umap/plot.py", line 209:
E def _nhood_compare(indices_left, indices_right):
E <source elided>
E for i in range(indices_left.shape[0]):
E intersection_size = np.intersect1d(indices_left[i], indices_right[i],
E ^
../../../hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:409: TypingErrorRaw output
/Users/runner/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:409: numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Check failure on line 1 in umap/tests/test_plot.py::test_plot_runs_at_all
azure-pipelines / lmcinnes.umap
umap/tests/test_plot.py::test_plot_runs_at_all
mapper = UMAP(n_epochs=100, tqdm_kwds={'bar_format': '{desc}: {percentage:3.0f}%| {bar} {n_fmt}/{total_fmt} [{elapsed}]', 'desc': 'Epochs completed', 'disable': True})
iris = {'data': array([[5.1, 3.5, 1.4, 0.2],
[4.9, 3. , 1.4, 0.2],
[4.7, 3.2, 1.3, 0.2],
[4.6, 3.1, 1.5,... width (cm)', 'petal length (cm)', 'petal width (cm)'], 'filename': 'iris.csv', 'data_module': 'sklearn.datasets.data'}
iris_selection = array([ True, True, True, True, True, True, True, True, True,
False, True, False, True, True, True,... True, True, True, True, True, True, True, False, False,
True, True, True, False, True, False])
@plot_only
def test_plot_runs_at_all(mapper, iris, iris_selection):
from umap import plot as umap_plot
umap_plot.points(mapper)
umap_plot.points(mapper, labels=iris.target)
umap_plot.points(mapper, values=iris.data[:, 0])
umap_plot.points(mapper, labels=iris.target, subset_points=iris_selection)
umap_plot.points(mapper, values=iris.data[:, 0], subset_points=iris_selection)
umap_plot.points(mapper, theme="fire")
> umap_plot.diagnostic(mapper, diagnostic_type="all")
umap/tests/test_plot.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
umap/plot.py:1202: in diagnostic
diagnostic(
umap/plot.py:1124: in diagnostic
accuracy = _nhood_compare(
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:468: in _compile_for_args
error_rewrite(e, 'typing')
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
e = TypingError('Failed in nopython mode pipeline (step: nopython frontend)\nNo implementation of function Function(<funct...(indices_left.shape[0]):\n intersection_size = np.intersect1d(indices_left[i], indices_right[i], \n ^\n')
issue_type = 'typing'
def error_rewrite(e, issue_type):
"""
Rewrite and raise Exception `e` with help supplied based on the
specified issue_type.
"""
if config.SHOW_HELP:
help_msg = errors.error_extras[issue_type]
e.patch_message('\n'.join((str(e).rstrip(), help_msg)))
if config.FULL_TRACEBACKS:
raise e
else:
> raise e.with_traceback(None)
E numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
E No implementation of function Function(<function intersect1d at 0x7faae498c160>) found for signature:
E
E >>> intersect1d(array(int32, 1d, C), array(int32, 1d, C), assume_unique=Literal[bool](True))
E
E There are 2 candidate implementations:
E - Of which 2 did not match due to:
E Overload in function 'jit_np_intersect1d': File: numba/np/arraymath.py: Line 3586.
E With argument(s): '(array(int32, 1d, C), array(int32, 1d, C), assume_unique=bool)':
E Rejected as the implementation raised a specific error:
E TypingError: got an unexpected keyword argument 'assume_unique'
E raised from /opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/typing/templates.py:784
E
E During: resolving callee type: Function(<function intersect1d at 0x7faae498c160>)
E During: typing of call at /home/vsts/work/1/s/umap/plot.py (209)
E
E
E File "umap/plot.py", line 209:
E def _nhood_compare(indices_left, indices_right):
E <source elided>
E for i in range(indices_left.shape[0]):
E intersection_size = np.intersect1d(indices_left[i], indices_right[i],
E ^
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:409: TypingErrorRaw output
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/numba/core/dispatcher.py:409: numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Check failure on line 1 in umap/tests/test_plot.py::test_plot_runs_at_all
azure-pipelines / lmcinnes.umap
umap/tests/test_plot.py::test_plot_runs_at_all
mapper = UMAP(n_epochs=100, tqdm_kwds={'bar_format': '{desc}: {percentage:3.0f}%| {bar} {n_fmt}/{total_fmt} [{elapsed}]', 'desc': 'Epochs completed', 'disable': True})
iris = {'data': array([[5.1, 3.5, 1.4, 0.2],
[4.9, 3. , 1.4, 0.2],
[4.7, 3.2, 1.3, 0.2],
[4.6, 3.1, 1.5,... width (cm)', 'petal length (cm)', 'petal width (cm)'], 'filename': 'iris.csv', 'data_module': 'sklearn.datasets.data'}
iris_selection = array([ True, True, True, True, True, True, True, True, True,
False, True, False, True, True, True,... True, True, True, True, True, True, True, False, False,
True, True, True, False, True, False])
@plot_only
def test_plot_runs_at_all(mapper, iris, iris_selection):
from umap import plot as umap_plot
umap_plot.points(mapper)
umap_plot.points(mapper, labels=iris.target)
umap_plot.points(mapper, values=iris.data[:, 0])
umap_plot.points(mapper, labels=iris.target, subset_points=iris_selection)
umap_plot.points(mapper, values=iris.data[:, 0], subset_points=iris_selection)
umap_plot.points(mapper, theme="fire")
> umap_plot.diagnostic(mapper, diagnostic_type="all")
umap/tests/test_plot.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
umap/plot.py:1202: in diagnostic
diagnostic(
umap/plot.py:1124: in diagnostic
accuracy = _nhood_compare(
/opt/hostedtoolcache/Python/3.9.19/x64/lib/python3.9/site-packages/numba/core/dispatcher.py:468: in _compile_for_args
error_rewrite(e, 'typing')
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
e = TypingError('Failed in nopython mode pipeline (step: nopython frontend)\nNo implementation of function Function(<funct...(indices_left.shape[0]):\n intersection_size = np.intersect1d(indices_left[i], indices_right[i], \n ^\n')
issue_type = 'typing'
def error_rewrite(e, issue_type):
"""
Rewrite and raise Exception `e` with help supplied based on the
specified issue_type.
"""
if config.SHOW_HELP:
help_msg = errors.error_extras[issue_type]
e.patch_message('\n'.join((str(e).rstrip(), help_msg)))
if config.FULL_TRACEBACKS:
raise e
else:
> raise e.with_traceback(None)
E numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
E No implementation of function Function(<function intersect1d at 0x7f17781a75e0>) found for signature:
E
E >>> intersect1d(array(int32, 1d, C), array(int32, 1d, C), assume_unique=Literal[bool](True))
E
E There are 2 candidate implementations:
E - Of which 2 did not match due to:
E Overload in function 'jit_np_intersect1d': File: numba/np/arraymath.py: Line 3586.
E With argument(s): '(array(int32, 1d, C), array(int32, 1d, C), assume_unique=bool)':
E Rejected as the implementation raised a specific error:
E TypingError: got an unexpected keyword argument 'assume_unique'
E raised from /opt/hostedtoolcache/Python/3.9.19/x64/lib/python3.9/site-packages/numba/core/typing/templates.py:784
E
E During: resolving callee type: Function(<function intersect1d at 0x7f17781a75e0>)
E During: typing of call at /home/vsts/work/1/s/umap/plot.py (209)
E
E
E File "umap/plot.py", line 209:
E def _nhood_compare(indices_left, indices_right):
E <source elided>
E for i in range(indices_left.shape[0]):
E intersection_size = np.intersect1d(indices_left[i], indices_right[i],
E ^
/opt/hostedtoolcache/Python/3.9.19/x64/lib/python3.9/site-packages/numba/core/dispatcher.py:409: TypingErrorRaw output
/opt/hostedtoolcache/Python/3.9.19/x64/lib/python3.9/site-packages/numba/core/dispatcher.py:409: numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
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