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[functorch] classify some more test failures (#83520)
Classifies test failures for test_vmapvjp and test_vmapjvpall Test Plan: - tests Pull Request resolved: https://github.com/pytorch/pytorch/pull/83520 Approved by: https://github.com/samdow
This commit is contained in:
Richard Zou
PyTorch MergeBot
parent
52b8a58197
commit
7e7afcabe7
1 changed files with 35 additions and 36 deletions
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@ -342,26 +342,16 @@ class TestOperators(TestCase):
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@ops(op_db + additional_op_db, allowed_dtypes=(torch.float,))
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@skipOps('TestOperators', 'test_jvp', set({
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skip('nn.functional.max_pool1d'), # fails on cpu, runs okay on cuda
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skip('pca_lowrank', ''), # fails on cuda, runs okay on cpu
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skip('svd_lowrank', ''), # fails on cuda, runs okay on cpu
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# =============================================
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# NB: The above failures also fail using PyTorch core's
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# forward-mode AD and vmap.
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# The failures below are functorch-specific issues
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# =============================================
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# Composite ops that do bad things. Need to be fixed in PyTorch core.
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# RuntimeError: Cannot access data pointer of Tensor that doesn't have storage
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xfail('tensor_split'),
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# BUG: runs and produces numerical differences
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# BUG: silent incorrectness: runs and produces numerical differences
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skip('nn.functional.max_unpool1d'), # fails everywhere except on mac
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skip('nn.functional.max_unpool2d'), # fails everywhere except on windows
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skip('nn.functional.max_unpool3d'), # fails everywhere except on mac
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xfail('nn.functional.rrelu') # in-place test fails
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xfail('nn.functional.rrelu') # in-place test errors out with no formula implemented
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}))
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@opsToleranceOverride('TestOperators', 'test_jvp', (
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tol1('nn.functional.conv_transpose3d',
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@ -570,6 +560,7 @@ class TestOperators(TestCase):
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self.assertEqual(loop_out, batched_out)
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vmapvjp_fail = vjp_fail.union({
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# -------------------- ALLOWED FAILURES --------------------------------
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# The following are not bugs and are expected behavior
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xfail('masked_select'), # Not possible due to dynamic shapes
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skip('bernoulli'), # randomness
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@ -580,6 +571,7 @@ class TestOperators(TestCase):
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skip('nn.functional.feature_alpha_dropout', 'without_train'), # randomness
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skip('nn.functional.dropout'), # randomness
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skip('nn.functional.dropout2d'), # randomness
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skip('nn.functional.dropout3d', ''), # randomness
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xfail('as_strided'), # as_strided is too wild for us to support, wontfix
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xfail('index_put', ''), # not possible due to dynamic shapes; we support a subset
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xfail('masked_scatter'), # dynamic
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@ -588,7 +580,9 @@ class TestOperators(TestCase):
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xfail('take'), # dynamic
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xfail('pca_lowrank', ''), # randomness
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xfail('svd_lowrank', ''), # randomness
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# ----------------------------------------------------------------------
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# ---------------------------- BUGS ------------------------------------
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# All of the following are bugs and need to be fixed
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skip('linalg.svdvals'), # # really annoying thing where it passes correctness check but not has_batch_rule
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xfail('__getitem__', ''), # dynamic error
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@ -600,14 +594,15 @@ class TestOperators(TestCase):
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xfail('nn.functional.gaussian_nll_loss'), # checks var for if any value < 0
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xfail('prod'), # calls nonzero
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xfail('quantile', device_type='cpu'), # checks q via a .item() call
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xfail('stft'),
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xfail('view_as_complex'),
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xfail('stft'), # calls as_strided
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xfail('view_as_complex'), # Tensor must have a last dimension with stride 1
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# required rank 4 tensor to use channels_last format
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xfail('bfloat16'),
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xfail('double'),
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xfail('float'),
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xfail('half'),
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xfail('chalf', ''),
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xfail('scatter_reduce', 'prod'), # item call
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@ -615,11 +610,10 @@ class TestOperators(TestCase):
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xfail('nn.functional.max_unpool2d'),
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xfail('nn.functional.max_unpool2d', 'grad'),
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xfail('chalf', ''),
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xfail('sparse.sampled_addmm', ''),
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xfail('as_strided_scatter', ''),
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xfail('index_reduce', ''),
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xfail('nn.functional.dropout3d', ''),
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xfail('as_strided_scatter', ''), # calls as_strided
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xfail('index_reduce', ''), # .item() call
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# ---------------------------------------------------------------------
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})
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@ops(op_db + additional_op_db, allowed_dtypes=(torch.float,))
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@ -653,6 +647,7 @@ class TestOperators(TestCase):
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self.assertEqual(loop_out, batched_out)
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vmapjvpall_fail = {
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# -------------------- ALLOWED FAILURES --------------------------------
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# The following are expected (not a bug)
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skip('bernoulli', ''), # randomness
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skip('nn.functional.dropout'), # randomness
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@ -663,34 +658,37 @@ class TestOperators(TestCase):
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skip('nn.functional.feature_alpha_dropout', 'with_train'),
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xfail('nn.functional.fractional_max_pool2d'), # Cannot access data pointer of Tensor that doesn't have storage
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xfail('nn.functional.fractional_max_pool3d'), # Cannot access data pointer of Tensor that doesn't have storage
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# The following are bugs that we should fix
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skip('nn.functional.max_pool1d'), # fails on cpu, runs on cuda
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xfail('_masked.mean'),
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xfail('_masked.prod'),
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# Not actually a problem: embedding with max_norm mutates the weight
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# and causes different runs to produce different results.
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# skip because this is flaky depending on what the max_norm is!
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skip('nn.functional.embedding', ''),
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xfail('nn.functional.soft_margin_loss', ''),
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xfail('linalg.householder_product'),
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xfail('tensor_split'),
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xfail('quantile'),
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xfail('as_strided'),
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xfail('nn.functional.gaussian_nll_loss'),
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xfail('scatter'),
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xfail('nanquantile'),
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xfail('view_as_complex'),
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xfail('prod'),
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# ----------------------------------------------------------------------
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skip('pca_lowrank', ''),
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skip('svd_lowrank', ''),
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# ---------------------------- BUGS ------------------------------------
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# The following are bugs that we should fix
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skip('nn.functional.max_pool1d'), # fails on cpu, runs on cuda
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xfail('_masked.mean'), # silent incorrectness (nan difference)
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xfail('_masked.prod'), # .item or data-dependent control flow
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xfail('nn.functional.soft_margin_loss', ''), # soft_margin_loss_backward does not support forward-ad
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xfail('linalg.householder_product'), # output with shape [5, 5] doesn't match the broadcast shape [2, 5, 5]
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xfail('tensor_split'), # data_ptr composite compliance
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xfail('quantile'), # at::equal batching rule (cpu), also, in-place vmap (cuda)
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xfail('as_strided'), # as_strided too weird
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xfail('nn.functional.gaussian_nll_loss'), # .item or data-dependent control flow
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xfail('scatter'), # forward-mode AD does not support at::scatter
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xfail('nanquantile'), # at::equal batching rule (cpu), also, in-place vmap (cuda)
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xfail('view_as_complex'), # Tensor must have a last dimension with stride 1
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xfail('prod'), # .item or data-dependent control flow
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skip('pca_lowrank', ''), # randomness
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skip('svd_lowrank', ''), # randomness
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xfail('stft'), # transpose_ fallback
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xfail('double'), # required rank 4 tensor to use channels_last format
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# potential silent incorrectness
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skip('nn.functional.max_unpool1d'), # Flaky, seems to sometimes his max_unpool2d
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skip('nn.functional.max_unpool2d'), # fails everywhere except on mac
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skip('nn.functional.max_unpool3d'), # fails everywhere except on mac
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@ -700,6 +698,7 @@ class TestOperators(TestCase):
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# erroring because running_mean and running_var aren't differentiable
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xfail('nn.functional.batch_norm'),
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xfail('nn.functional.batch_norm', 'without_cudnn'),
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# ----------------------------------------------------------------------
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}
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@ops(op_db + additional_op_db, allowed_dtypes=(torch.float,))
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