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conbine some hyperbolic trigo fucntion diopi test into hyperbolic_tri…
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…go_function
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@DoorKickers
DoorKickers committed Aug 14, 2024
1 parent 89168cd commit 56b3150
Showing 1 changed file with 4 additions and 156 deletions.
160 changes: 4 additions & 156 deletions diopi_test/python/configs/diopi_configs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1192,8 +1192,8 @@
),
),

'sinh': dict(
name=['sinh'],
'hyperbolic_trigo_function_without_backward': dict(
name=['sinh', 'cosh', 'asinh', 'acosh', 'atanh'],
interface=['torch'],
is_inplace=True,
saved_args=dict(output=0),
Expand All @@ -1212,46 +1212,8 @@
),
),

'sinh_not_float': dict(
name=['sinh'],
interface=['torch'],
dtype=[np.int16, np.int32, np.int64, np.uint8, np.int8, np.bool_],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'cosh': dict(
name=['cosh'],
interface=['torch'],
is_inplace=True,
saved_args=dict(output=0),
dtype=[np.float16, np.float32, np.float64],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'cosh_not_float': dict(
name=['cosh'],
'hyperbolic_trigo_function_without_backward_not_float': dict(
name=['sinh', 'cosh', 'asinh', 'acosh', 'atanh'],
interface=['torch'],
dtype=[np.int16, np.int32, np.int64, np.uint8, np.int8, np.bool_],
tensor_para=dict(
Expand Down Expand Up @@ -1307,120 +1269,6 @@
),
),

'asinh': dict(
name=['asinh'],
interface=['torch'],
is_inplace=True,
saved_args=dict(output=0),
dtype=[np.float16, np.float32, np.float64],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'asinh_not_float': dict(
name=['asinh'],
interface=['torch'],
dtype=[np.int16, np.int32, np.int64, np.uint8, np.int8, np.bool_],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'acosh': dict(
name=['acosh'],
interface=['torch'],
is_inplace=True,
saved_args=dict(output=0),
dtype=[np.float16, np.float32, np.float64],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'acosh_not_float': dict(
name=['acosh'],
interface=['torch'],
dtype=[np.int16, np.int32, np.int64, np.uint8, np.int8, np.bool_],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'atanh': dict(
name=['atanh'],
interface=['torch'],
is_inplace=True,
saved_args=dict(output=0),
dtype=[np.float16, np.float32, np.float64],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'atanh_not_float': dict(
name=['atanh'],
interface=['torch'],
dtype=[np.int16, np.int32, np.int64, np.uint8, np.int8, np.bool_],
tensor_para=dict(
gen_fn='Genfunc.randn',
args=[
{
"ins": ['input'],
"shape": ((), (1, ), (1024,), (364800, 4), (2, 128, 3072),
(256, 128, 3, 3),
(2, 31, 512, 6, 40),
(0,), (16, 0), (1, 0, 6)),
},
],
),
),

'sign': dict(
name=['sign'],
interface=['torch'],
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