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Remove unactivated test (#146233)
Fixes #ISSUE_NUMBER Pull Request resolved: https://github.com/pytorch/pytorch/pull/146233 Approved by: https://github.com/rec, https://github.com/albanD
This commit is contained in:
cyy
PyTorch MergeBot
parent
e68f5087d8
commit
71e3575525
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@ -1,35 +1,26 @@
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# mypy: ignore-errors
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# ruff: noqa: F841
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# Owner(s): ["module: dataloader"]
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import copy
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import itertools
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import importlib.util
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import os
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import os.path
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import pickle
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import pydoc
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import random
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import sys
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import tempfile
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import warnings
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from functools import partial
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from typing import (
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Any,
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Generic,
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Optional,
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TYPE_CHECKING,
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TypeVar,
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Union,
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)
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from collections.abc import Awaitable, Iterator
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if not TYPE_CHECKING:
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# pyre isn't treating this the same as a typing.NamedTuple
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from typing_extensions import NamedTuple
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else:
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from typing import NamedTuple
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import operator
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from unittest import skipIf
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@ -74,12 +65,7 @@ from torch.utils.data.graph import traverse_dps
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dill = import_dill()
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HAS_DILL = TEST_DILL
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try:
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import pandas # type: ignore[import] # noqa: F401 F403
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HAS_PANDAS = True
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except ImportError:
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HAS_PANDAS = False
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HAS_PANDAS: bool = importlib.util.find_spec("pandas") is not None
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skipIfNoDataFrames = skipIf(not HAS_PANDAS, "no dataframes (pandas)")
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skipTyping = skipIf(True, "TODO: Fix typing bug")
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@ -418,13 +404,13 @@ class TestIterableDataPipeBasic(TestCase):
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self.assertTrue(inp[1].closed)
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cached = list(datapipe2)
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with warnings.catch_warnings(record=True) as wa:
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with warnings.catch_warnings(record=True):
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datapipe3 = dp.iter.RoutedDecoder(cached, _png_decoder)
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datapipe3.add_handler(decoder_basichandlers)
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_helper(cached, datapipe3)
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cached = list(datapipe2)
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with warnings.catch_warnings(record=True) as wa:
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with warnings.catch_warnings(record=True):
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datapipe4 = dp.iter.RoutedDecoder(cached, decoder_basichandlers)
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datapipe4.add_handler(_png_decoder)
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_helper(cached, datapipe4, channel_first=True)
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@ -779,7 +765,7 @@ class TestFunctionalIterDataPipe(TestCase):
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it1, it2 = iter(dp1), iter(dp2)
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_, _ = next(it1), next(it2)
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# Catch `fork`, `demux` "some child DataPipes are not exhausted" warning
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with warnings.catch_warnings(record=True) as wa:
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with warnings.catch_warnings(record=True):
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self._serialization_test_helper(dp1, use_dill)
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self._serialization_test_helper(dp2, use_dill)
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@ -788,7 +774,7 @@ class TestFunctionalIterDataPipe(TestCase):
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it1 = iter(dp1)
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_ = list(it1) # fully read one child
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# Catch `fork`, `demux` "some child DataPipes are not exhausted" warning
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with warnings.catch_warnings(record=True) as wa:
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with warnings.catch_warnings(record=True):
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self._serialization_test_helper(dp1, use_dill)
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self._serialization_test_helper(dp2, use_dill)
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@ -1319,7 +1305,7 @@ class TestFunctionalIterDataPipe(TestCase):
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if n1 == 4:
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break
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with warnings.catch_warnings(record=True) as wa:
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i1 = iter(dp1) # Reset all child DataPipes
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iter(dp1) # Reset all child DataPipes
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self.assertEqual(len(wa), 1)
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self.assertRegex(
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str(wa[0].message), r"Some child DataPipes are not exhausted"
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@ -1899,7 +1885,7 @@ class TestFunctionalIterDataPipe(TestCase):
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# Functional Test: filter function must return bool
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filter_dp = input_ds.filter(filter_fn=_non_bool_fn)
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with self.assertRaises(ValueError):
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temp = list(filter_dp)
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list(filter_dp)
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# Funtional Test: Specify input_col
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tuple_input_ds = dp.iter.IterableWrapper([(d - 1, d, d + 1) for d in range(10)])
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@ -1965,9 +1951,9 @@ class TestFunctionalIterDataPipe(TestCase):
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self.assertEqual(x, i)
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# RandomSampler
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random_sampled_dp = dp.iter.Sampler(
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dp.iter.Sampler(
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input_dp, sampler=RandomSampler, sampler_kwargs={"replacement": True}
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) # type: ignore[var-annotated] # noqa: B950
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)
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# Requires `__len__` to build SamplerDataPipe
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input_dp_nolen = IDP_NoLen(range(10))
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@ -1998,7 +1984,7 @@ class TestFunctionalIterDataPipe(TestCase):
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input_dp = dp.iter.IterableWrapper(list(range(10)))
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with self.assertRaises(AssertionError):
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shuffle_dp = input_dp.shuffle(buffer_size=0)
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input_dp.shuffle(buffer_size=0)
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# Functional Test: No seed
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shuffler_dp = input_dp.shuffle()
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@ -2035,7 +2021,6 @@ class TestFunctionalIterDataPipe(TestCase):
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# __len__ Test: returns the length of the input DataPipe
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shuffler_dp = input_dp.shuffle()
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self.assertEqual(10, len(shuffler_dp))
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exp = list(range(100))
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# Serialization Test
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from torch.utils.data.datapipes._hook_iterator import _SnapshotState
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@ -2403,16 +2388,6 @@ class TestFunctionalMapDataPipe(TestCase):
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self.assertEqual(2, len(batch_dp_2))
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# Metaclass conflict for Python 3.6
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# Multiple inheritance with NamedTuple is not supported for Python 3.9
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_generic_namedtuple_allowed = sys.version_info >= (3, 7) and sys.version_info < (3, 9)
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if _generic_namedtuple_allowed:
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class InvalidData(NamedTuple, Generic[T_co]):
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name: str
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data: T_co
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class TestTyping(TestCase):
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def test_isinstance(self):
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class A(IterDataPipe):
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@ -2548,14 +2523,6 @@ class TestTyping(TestCase):
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def __iter__(self) -> Iterator[tuple]: # type: ignore[override]
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yield (0,)
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if _generic_namedtuple_allowed:
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with self.assertRaisesRegex(
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TypeError, r"is not supported by Python typing"
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):
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class InvalidDP4(IterDataPipe["InvalidData[int]"]): # type: ignore[type-arg, misc]
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pass
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class DP1(IterDataPipe[tuple[int, str]]):
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def __init__(self, length):
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self.length = length
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@ -2679,7 +2646,7 @@ class TestTyping(TestCase):
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with self.assertRaisesRegex(
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TypeError, r"Expected type of argument 'dp' as a subtype"
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):
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dp1 = DP1(dp0)
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DP1(dp0)
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@skipTyping
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def test_runtime(self):
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@ -2740,13 +2707,13 @@ class TestTyping(TestCase):
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# Invalid type
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with self.assertRaisesRegex(TypeError, r"'expected_type' must be a type"):
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dp1 = DP(ds).reinforce_type(1)
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DP(ds).reinforce_type(1)
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# Type is not subtype
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with self.assertRaisesRegex(
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TypeError, r"Expected 'expected_type' as subtype of"
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):
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dp2 = DP(ds).reinforce_type(float)
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DP(ds).reinforce_type(float)
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# Invalid data at runtime
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dp3 = DP(ds).reinforce_type(str)
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