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Remove tests
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@justinchuby
justinchuby committed Sep 16, 2024
1 parent 2c2437d commit 624ee7e
Showing 1 changed file with 0 additions and 113 deletions.
113 changes: 0 additions & 113 deletions tests/function_libs/torch_lib/ops_test_data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1497,33 +1497,6 @@ def _where_input_wrangler(
),
TorchLibOpInfo("stack", core_ops.aten_stack),
TorchLibOpInfo("stack", core_ops.aten_stack_complex, complex=True),
TorchLibOpInfo(
"std_mean",
core_ops.aten_std_mean,
).xfail(
# kwargs is empty
matcher=lambda sample: len(sample.kwargs) > 0,
reason="this Aten overload only support input[0]=tensor and input[1]=bool as input without any kwargs",
),
TorchLibOpInfo(
"std_mean_dim",
core_ops.aten_std_mean_dim,
).xfail(
# kwargs["dim"] must exist, kwargs["correction"] must not exist
matcher=lambda sample: not (
sample.kwargs.get("dim", None) is not None
and sample.kwargs.get("correction", None) is None
),
reason="this Aten overload only support with 'dim' argument and without 'correction' argument",
),
TorchLibOpInfo(
"std_mean_correction",
core_ops.aten_std_mean_correction,
).skip(
# Don't accept input[1]=bool and 'correction' must be in kwargs
matcher=lambda sample: len(sample.args) > 0 or "correction" not in sample.kwargs,
reason="this Aten overload only support when correction attribute exists",
),
TorchLibOpInfo("sub", core_ops.aten_sub),
TorchLibOpInfo("sub", core_ops.aten_sub_complex, complex=True),
# TorchLibOpInfo("sym_size", core_ops.aten_sym_size), # no test case in OPS_DB
Expand Down Expand Up @@ -2191,33 +2164,6 @@ def _where_input_wrangler(
dtypes=(torch.float16,),
reason="RuntimeError: MKL FFT doesn't support tensors of type: Half",
),
TorchLibOpInfo(
"std",
core_ops.aten_std,
).xfail(
# kwargs must be empty
matcher=lambda sample: len(sample.kwargs) > 0,
reason="this Aten overload only support input[0]=tensor and input[1]=bool as input without any kwargs",
),
TorchLibOpInfo(
"std_dim",
core_ops.aten_std_dim,
).xfail(
# kwargs["dim"] must exist, kwargs["correction"] must not exist
matcher=lambda sample: not (
sample.kwargs.get("dim", None) is not None
and sample.kwargs.get("correction", None) is None
),
reason="this Aten overload only support with 'dim' argument and without 'correction' argument",
),
TorchLibOpInfo(
"std_correction",
core_ops.aten_std_correction,
).skip(
# Don't accept input[1]=bool and 'correction' must be in kwargs
matcher=lambda sample: len(sample.args) > 0 or "correction" not in sample.kwargs,
reason="this Aten overload only support when correction attribute exists",
),
TorchLibOpInfo(
"sum",
core_ops.aten_sum_dim_IntList,
Expand All @@ -2238,60 +2184,6 @@ def _where_input_wrangler(
), # Custom from extra_opinfo
TorchLibOpInfo("transpose", core_ops.aten_transpose),
TorchLibOpInfo("transpose", core_ops.aten_transpose_complex, complex=True),
TorchLibOpInfo(
"var_mean",
core_ops.aten_var_mean,
).xfail(
# kwargs is empty
matcher=lambda sample: len(sample.kwargs) > 0,
reason="this Aten overload only support input[0]=tensor and input[1]=bool as input without any kwargs",
),
TorchLibOpInfo(
"var_mean_dim",
core_ops.aten_var_mean_dim,
).xfail(
# kwargs["dim"] must exist, kwargs["correction"] must not exist
matcher=lambda sample: not (
sample.kwargs.get("dim", None) is not None
and sample.kwargs.get("correction", None) is None
),
reason="this Aten overload only support with 'dim' argument and without 'correction' argument",
),
TorchLibOpInfo(
"var_mean_correction",
core_ops.aten_var_mean_correction,
).skip(
# Don't accept input[1]=bool and 'correction' must be in kwargs
matcher=lambda sample: len(sample.args) > 0 or "correction" not in sample.kwargs,
reason="this Aten overload only support when correction attribute exists",
),
TorchLibOpInfo(
"var",
core_ops.aten_var,
).xfail(
# kwargs must be empty
matcher=lambda sample: len(sample.kwargs) > 0,
reason="this Aten overload only support input[0]=tensor and input[1]=bool as input without any kwargs",
),
TorchLibOpInfo(
"var_dim",
core_ops.aten_var_dim,
).xfail(
# kwargs["dim"] must exist, kwargs["correction"] must not exist
matcher=lambda sample: not (
sample.kwargs.get("dim", None) is not None
and sample.kwargs.get("correction", None) is None
),
reason="this Aten overload only support with 'dim' argument and without 'correction' argument",
),
TorchLibOpInfo(
"var_correction",
core_ops.aten_var_correction,
).skip(
# Don't accept input[1]=bool and 'correction' must be in kwargs
matcher=lambda sample: len(sample.args) > 0 or "correction" not in sample.kwargs,
reason="this Aten overload only support when correction attribute exists",
),
TorchLibOpInfo("zeros_like", core_ops.aten_zeros_like),
TorchLibOpInfo("torchvision.ops.nms", vision_ops.torchvision_nms),
)
Expand Down Expand Up @@ -2364,10 +2256,6 @@ def _where_input_wrangler(
ops_test_common.duplicate_opinfo(OPS_DB, "ops.aten._softmax", ("ops.aten._softmax_half",))
ops_test_common.duplicate_opinfo(OPS_DB, "round", ("round_decimals",))
ops_test_common.duplicate_opinfo(OPS_DB, "squeeze", ("squeeze_dim",))
ops_test_common.duplicate_opinfo(OPS_DB, "std_mean", ("std_mean_dim", "std_mean_correction"))
ops_test_common.duplicate_opinfo(OPS_DB, "std", ("std_dim", "std_correction"))
ops_test_common.duplicate_opinfo(OPS_DB, "var_mean", ("var_mean_dim", "var_mean_correction"))
ops_test_common.duplicate_opinfo(OPS_DB, "var", ("var_dim", "var_correction"))
ops_test_common.duplicate_opinfo(OPS_DB, "view_as_complex", ("view_as_complex_copy",))
ops_test_common.duplicate_opinfo(OPS_DB, "view_as_real", ("view_as_real_copy",))

Expand Down Expand Up @@ -2510,7 +2398,6 @@ def _where_input_wrangler(
"transpose",
"trunc",
"uniform",
"var",
"where",
)

Expand Down

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