mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
92c49e2168
1. Inherit from TestCase
2. Use pytorch parametrization
3. Use unittest.expectedFailure to mark xfails
All this to make pytest-less invocation work:
$ python test/torch_np/test_basic.py
Furthermor, tests can now be run under dynamo, and we see first errors:
```
$ PYTORCH_TEST_WITH_DYNAMO=1 python test/torch_np/test_basic.py -k test_toscalar_list_func
.E.
======================================================================
ERROR: test_toscalar_list_func_<function shape at 0x7f9b83a4fc10>_np_func_<function shape at 0x7f9a8dd38af0> (__main__.TestOneArrToScalar)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/ev-br/repos/pytorch/torch/testing/_internal/common_utils.py", line 356, in instantiated_test
test(self, **param_kwargs)
File "test/torch_np/test_basic.py", line 232, in test_toscalar_list
@parametrize("func, np_func", one_arg_scalar_funcs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1519, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1528, in _call_impl
return forward_call(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/_dynamo/eval_frame.py", line 406, in _fn
return fn(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 726, in call_wrapped
return self._wrapped_call(self, *args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 305, in __call__
raise e
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 292, in __call__
return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc]
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1519, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1528, in _call_impl
return forward_call(*args, **kwargs)
File "<eval_with_key>.2", line 5, in forward
shape = torch._numpy._funcs_impl.shape([[1, 2, 3], [4, 5, 6]])
File "/home/ev-br/repos/pytorch/torch/_numpy/_funcs_impl.py", line 655, in shape
return tuple(a.shape)
AttributeError: 'list' object has no attribute 'shape'
----------------------------------------------------------------------
Ran 3 tests in 0.915s
FAILED (errors=1)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/109593
Approved by: https://github.com/lezcano
108 lines
3.6 KiB
Python
108 lines
3.6 KiB
Python
# Owner(s): ["module: dynamo"]
|
|
|
|
from unittest import expectedFailure as xfail
|
|
|
|
import pytest
|
|
|
|
import torch._numpy as np
|
|
from pytest import raises as assert_raises
|
|
from torch._numpy.testing import assert_array_equal, assert_equal
|
|
|
|
from torch.testing._internal.common_utils import (
|
|
instantiate_parametrized_tests,
|
|
parametrize,
|
|
run_tests,
|
|
TestCase,
|
|
)
|
|
|
|
|
|
@instantiate_parametrized_tests
|
|
class TestArange(TestCase):
|
|
def test_infinite(self):
|
|
assert_raises(
|
|
(RuntimeError, ValueError), np.arange, 0, np.inf
|
|
) # "size exceeded",
|
|
|
|
def test_nan_step(self):
|
|
assert_raises(
|
|
(RuntimeError, ValueError), np.arange, 0, 1, np.nan
|
|
) # "cannot compute length",
|
|
|
|
def test_zero_step(self):
|
|
assert_raises(ZeroDivisionError, np.arange, 0, 10, 0)
|
|
assert_raises(ZeroDivisionError, np.arange, 0.0, 10.0, 0.0)
|
|
|
|
# empty range
|
|
assert_raises(ZeroDivisionError, np.arange, 0, 0, 0)
|
|
assert_raises(ZeroDivisionError, np.arange, 0.0, 0.0, 0.0)
|
|
|
|
def test_require_range(self):
|
|
assert_raises(TypeError, np.arange)
|
|
assert_raises(TypeError, np.arange, step=3)
|
|
assert_raises(TypeError, np.arange, dtype="int64")
|
|
|
|
@xfail # (reason="XXX: arange(start=0, stop, step=1)")
|
|
def test_require_range_2(self):
|
|
assert_raises(TypeError, np.arange, start=4)
|
|
|
|
def test_start_stop_kwarg(self):
|
|
keyword_stop = np.arange(stop=3)
|
|
keyword_zerotostop = np.arange(start=0, stop=3)
|
|
keyword_start_stop = np.arange(start=3, stop=9)
|
|
|
|
assert len(keyword_stop) == 3
|
|
assert len(keyword_zerotostop) == 3
|
|
assert len(keyword_start_stop) == 6
|
|
assert_array_equal(keyword_stop, keyword_zerotostop)
|
|
|
|
@xfail # (reason="XXX: arange(..., dtype=bool)")
|
|
def test_arange_booleans(self):
|
|
# Arange makes some sense for booleans and works up to length 2.
|
|
# But it is weird since `arange(2, 4, dtype=bool)` works.
|
|
# Arguably, much or all of this could be deprecated/removed.
|
|
res = np.arange(False, dtype=bool)
|
|
assert_array_equal(res, np.array([], dtype="bool"))
|
|
|
|
res = np.arange(True, dtype="bool")
|
|
assert_array_equal(res, [False])
|
|
|
|
res = np.arange(2, dtype="bool")
|
|
assert_array_equal(res, [False, True])
|
|
|
|
# This case is especially weird, but drops out without special case:
|
|
res = np.arange(6, 8, dtype="bool")
|
|
assert_array_equal(res, [True, True])
|
|
|
|
with pytest.raises(TypeError):
|
|
np.arange(3, dtype="bool")
|
|
|
|
@parametrize("which", [0, 1, 2])
|
|
def test_error_paths_and_promotion(self, which):
|
|
args = [0, 10, 2] # start, stop, and step
|
|
args[which] = np.float64(2.0) # should ensure float64 output
|
|
assert np.arange(*args).dtype == np.float64
|
|
|
|
# Cover stranger error path, test only to achieve code coverage!
|
|
args[which] = [None, []]
|
|
with pytest.raises((ValueError, RuntimeError)):
|
|
# Fails discovering start dtype
|
|
np.arange(*args)
|
|
|
|
|
|
class TestAppend(TestCase):
|
|
# tests taken from np.append docstring
|
|
def test_basic(self):
|
|
result = np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
|
|
assert_equal(result, np.arange(1, 10, dtype=int))
|
|
|
|
# When `axis` is specified, `values` must have the correct shape.
|
|
result = np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9]], axis=0)
|
|
assert_equal(result, np.arange(1, 10, dtype=int).reshape((3, 3)))
|
|
|
|
with pytest.raises((RuntimeError, ValueError)):
|
|
np.append([[1, 2, 3], [4, 5, 6]], [7, 8, 9], axis=0)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
run_tests()
|