8000 [chalf] enable testing for multiple ops by kshitij12345 · Pull Request #77405 · pytorch/pytorch · GitHub
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[chalf] enable testing for multiple ops #77405

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[chalf] enable testing for multiple ops #77405

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f9bf972
[chalf] enable testing for multiple ops
kshitij12345 May 13, 2022
16accbf
update skips and meta-data
kshitij12345 May 13, 2022
2d2f24a
add comment for skip
kshitij12345 May 13, 2022
212451a
Merge branch 'master' into develop/chalf/enable-testing-3
kshitij12345 May 13, 2022
59a9c27
Merge branch 'master' of https://github.com/pytorch/pytorch into deve…
kshitij12345 May 13, 2022
79a4574
Merge branch 'develop/chalf/enable-testing-3' of https://github.com/k…
kshitij12345 May 13, 2022
4dd4919
update skip dtype
kshitij12345 May 13, 2022
f22d099
Merge branch 'pytorch:master' into develop/chalf/enable-testing-3
kshitij12345 May 17, 2022
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43 changes: 30 additions & 13 deletions torch/testing/_internal/common_methods_invocations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14161,8 +14161,7 @@ def error_inputs_mean(op_info, device, **kwargs):
)),
OpInfo('permute',
ref=np.transpose,
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypesIfCUDA=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
supports_out=False,
assert_autodiffed=True,
autodiff_fusible_nodes=[], # aliases inputs, shouldn't be fused
Expand Down Expand Up @@ -14479,7 +14478,7 @@ def error_inputs_mean(op_info, device, **kwargs):
dtypes=(torch.chalf,)),
)),
OpInfo('split',
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool),
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool, torch.chalf),
sample_inputs_func=partial(sample_inputs_split, list_args=False),
supports_forward_ad=True,
supports_fwgrad_bwgrad=True,
Expand All @@ -14498,7 +14497,7 @@ def error_inputs_mean(op_info, device, **kwargs):
supports_fwgrad_bwgrad=True,
supports_out=False),
OpInfo('split_with_sizes',
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool),
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool, torch.chalf),
sample_inputs_func=sample_inputs_split_with_sizes,
autodiff_fusible_nodes=[], # aliases inputs, shouldn't be fused
autodiff_nonfusible_nodes=[], # aliases inputs, shouldn't be fused
Expand Down Expand Up @@ -14669,7 +14668,7 @@ def error_inputs_mean(op_info, device, **kwargs):
sample_inputs_func=sample_inputs_add_sub),
OpInfo('select',
aten_backward_name='select_backward',
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool),
dtypes=all_types_and_complex_and(torch.bfloat16, torch.half, torch.bool, torch.chalf),
sample_inputs_func=sample_inputs_select,
assert_jit_shape_analysis=True,
supports_forward_ad=True,
Expand Down Expand Up @@ -15456,14 +15455,14 @@ def error_inputs_mean(op_info, device, **kwargs):
reference_numerics_filter=NumericsFilter(condition=lambda x: x < 0.1, safe_val=1)),
OpInfo('ravel',
ref=np.ravel,
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
supports_out=False,
supports_forward_ad=True,
supports_fwgrad_bwgrad=True,
sample_inputs_func=sample_inputs_ravel,
),
OpInfo('reshape',
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
sample_inputs_func=partial(sample_inputs_view_reshape, transpose_samples=True),
reference_inputs_func=partial(reference_inputs_view_reshape, transpose_samples=True),
error_inputs_func=error_inputs_reshape,
Expand All @@ -15473,7 +15472,7 @@ def error_inputs_mean(op_info, device, **kwargs):
),
OpInfo('reshape_as',
op=lambda x, other: x.reshape_as(other),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
sample_inputs_func=sample_inputs_view_as_reshape_as,
supports_out=False,
supports_forward_ad=True,
Expand Down Expand Up @@ -16247,7 +16246,8 @@ def error_inputs_mean(op_info, device, **kwargs):
),
OpInfo('unfold',
op=lambda x, *args: x.unfold(*args),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
backward_dtypes=floating_and_complex_types_and(torch.float16, torch.bfloat16),
supports_out=False,
supports_forward_ad=True,
supports_fwgrad_bwgrad=True,
Expand Down Expand Up @@ -16290,7 +16290,7 @@ def error_inputs_mean(op_info, device, **kwargs):
DecorateInfo(unittest.expectedFailure, "TestNormalizeOperators", "test_normalize_operator_exhaustive"),
)),
OpInfo('squeeze',
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
supports_out=False,
assert_autodiffed=True,
autodiff_fusible_nodes=[], # aliases inputs, shouldn't be fused
Expand Down Expand Up @@ -16393,7 +16393,7 @@ def error_inputs_mean(op_info, device, **kwargs):
supports_out=False,
sample_inputs_func=sample_cumulative_trapezoid,),
OpInfo('unsqueeze',
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16),
dtypes=all_types_and_complex_and(torch.bool, torch.float16, torch.bfloat16, torch.chalf),
supports_out=False,
supports_forward_ad=True,
supports_fwgrad_bwgrad=True,
Expand Down Expand Up @@ -16492,8 +16492,7 @@ def error_inputs_mean(op_info, device, **kwargs):
ref=_numpy_ref_transpose,
aliases=('swapdims', 'swapaxes'),
assert_jit_shape_analysis=True,
dtypes=all_types_and_complex_and(torch.bool, torch.bfloat16, torch.half),
dtypesIfCUDA=all_types_and_complex_and(torch.bool, torch.bfloat16, torch.half),
dtypes=all_types_and_complex_and(torch.bool, torch.bfloat16, torch.half, torch.chalf),
supports_out=False,
supports_forward_ad=True,
supports_fwgrad_bwgrad=True,
Expand Down Expand Up @@ -18821,10 +18820,28 @@ def __init__(
PythonRefInfo(
"_refs.permute",
torch_opinfo_name="permute",
skips=(
# RuntimeError: "index_select_cuda" not implemented for 'ComplexHalf'
DecorateInfo(unittest.expectedFailure, 'TestCommon',
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What's going on here?

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Oops forgot to add the error as comment

RuntimeError: "index_select_cuda" not implemented for 'ComplexHalf'

'test_python_reference_consistency', dtypes=(torch.chalf,), device_type='cuda'),
# RuntimeError: "index_select_cuda" not implemented for 'ComplexHalf'
DecorateInfo(unittest.expectedFailure, 'TestCommon',
'test_python_reference_meta_functions', dtypes=(torch.chalf,), device_type='cuda'),
),
),
PythonRefInfo(
"_refs.reshape",
torch_opinfo_name="reshape",
skips=(
# RuntimeError: "index_select" not implemented for 'ComplexHalf'
# RuntimeError: "index_select_cuda" not implemented for 'ComplexHalf'
DecorateInfo(unittest.expectedFailure, "TestCommon", "test_python_reference_consistency",
dtypes=(torch.chalf,)),
# RuntimeError: "index_select" not implemented for 'ComplexHalf'
# RuntimeError: "index_select_cuda" not implemented for 'ComplexHalf'
DecorateInfo(unittest.expectedFailure, "TestCommon", "test_python_reference_meta_functions",
dtypes=(torch.chalf,)),
),
),
PythonRefInfo(
"_refs.stack",
Expand Down
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