Skip to content

P
Paddle

PaddlePaddle / Paddle
1 年多 前同步成功

通知 2302
Star 20931
Fork 5422
P
Paddle
未验证 提交 bd1a240b 编写于 作者: C Charles-hit 提交者： GitHub
浏览文件
操作

[cherry-pick]Fix cuda12 test (#54622) 

* [AMP Prim OP]support some prim ops for bf16 dtype part3 (#54368)

* support some prim ops bf16 dtype

* fix cmake

* [AMP Prim OP]support some prim ops for bf16 dtype part5 (#54422)

* support some prim ops for bf16 dtype

* remove useless code

* support some prim ops bf16 dtype (#54399)
上级 37b4d7a2
隐藏空白更改
内联 并排
Showing with 248 addition and 83 deletion
test/legacy_test/CMakeLists.txt
浏览文件 @ bd1a240b
...@@ -1197,7 +1197,12 @@ set(TEST_CINN_OPS ...@@ -1197,7 +1197,12 @@ set(TEST_CINN_OPS
test_scatter_nd_op test_scatter_nd_op
test_strided_slice_op test_strided_slice_op
test_instance_norm_op test_instance_norm_op
test_cumsum_op) test_cumsum_op
test_pad_op
test_split_op
test_erf_op
test_assign_op
test_flatten_contiguous_range_op)
foreach(TEST_CINN_OPS ${TEST_CINN_OPS}) foreach(TEST_CINN_OPS ${TEST_CINN_OPS})
if(WITH_CINN) if(WITH_CINN)
......
test/legacy_test/test_assign_op.py
浏览文件 @ bd1a240b
...@@ -80,7 +80,6 @@ class TestAssignBFP16Op(eager_op_test.OpTest): ...@@ -80,7 +80,6 @@ class TestAssignBFP16Op(eager_op_test.OpTest):
self.public_python_api = paddle.assign self.public_python_api = paddle.assign
self.op_type = "assign" self.op_type = "assign"
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = False
x = np.random.uniform(0, 1, [100, 10]).astype(np.float32) x = np.random.uniform(0, 1, [100, 10]).astype(np.float32)
x = convert_float_to_uint16(x) x = convert_float_to_uint16(x)
self.inputs = {'X': x} self.inputs = {'X': x}
......
test/legacy_test/test_elementwise_min_op.py
浏览文件 @ bd1a240b
...@@ -127,18 +127,12 @@ class TestElementwiseMinOp_ZeroDim1(TestElementwiseOp): ...@@ -127,18 +127,12 @@ class TestElementwiseMinOp_ZeroDim1(TestElementwiseOp):
self.inputs = {'X': x, 'Y': y} self.inputs = {'X': x, 'Y': y}
self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])}
def if_enable_cinn(self):
self.enable_cinn = False
class TestElementwiseMinFP16Op_ZeroDim1(TestElementwiseFP16Op): class TestElementwiseMinFP16Op_ZeroDim1(TestElementwiseFP16Op):
def init_data(self): def init_data(self):
self.x = np.random.uniform(0.1, 1, []).astype(np.float16) self.x = np.random.uniform(0.1, 1, []).astype(np.float16)
self.y = np.random.uniform(0.1, 1, []).astype(np.float16) self.y = np.random.uniform(0.1, 1, []).astype(np.float16)
def if_enable_cinn(self):
self.enable_cinn = False
class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp): class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp):
def setUp(self): def setUp(self):
...@@ -146,24 +140,17 @@ class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp): ...@@ -146,24 +140,17 @@ class TestElementwiseMinOp_ZeroDim2(TestElementwiseOp):
self.python_api = paddle.minimum self.python_api = paddle.minimum
self.public_python_api = paddle.minimum self.public_python_api = paddle.minimum
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.if_enable_cinn()
x = np.random.uniform(0.1, 1, [13, 17]).astype("float64") x = np.random.uniform(0.1, 1, [13, 17]).astype("float64")
y = np.random.uniform(0.1, 1, []).astype("float64") y = np.random.uniform(0.1, 1, []).astype("float64")
self.inputs = {'X': x, 'Y': y} self.inputs = {'X': x, 'Y': y}
self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])}
def if_enable_cinn(self):
self.enable_cinn = False
class TestElementwiseMinFP16Op_ZeroDim2(TestElementwiseFP16Op): class TestElementwiseMinFP16Op_ZeroDim2(TestElementwiseFP16Op):
def init_data(self): def init_data(self):
self.x = np.random.uniform(0.1, 1, [13, 17]).astype("float16") self.x = np.random.uniform(0.1, 1, [13, 17]).astype("float16")
self.y = np.random.uniform(0.1, 1, []).astype("float16") self.y = np.random.uniform(0.1, 1, []).astype("float16")
def if_enable_cinn(self):
self.enable_cinn = False
class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp): class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp):
def setUp(self): def setUp(self):
...@@ -177,18 +164,12 @@ class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp): ...@@ -177,18 +164,12 @@ class TestElementwiseMinOp_ZeroDim3(TestElementwiseOp):
self.inputs = {'X': x, 'Y': y} self.inputs = {'X': x, 'Y': y}
self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])}
def if_enable_cinn(self):
self.enable_cinn = False
class TestElementwiseMinFP16Op_ZeroDim3(TestElementwiseFP16Op): class TestElementwiseMinFP16Op_ZeroDim3(TestElementwiseFP16Op):
def init_data(self): def init_data(self):
self.x = np.random.uniform(0.1, 1, []).astype("float16") self.x = np.random.uniform(0.1, 1, []).astype("float16")
self.y = np.random.uniform(0.1, 1, [13, 17]).astype("float16") self.y = np.random.uniform(0.1, 1, [13, 17]).astype("float16")
def if_enable_cinn(self):
self.enable_cinn = False
@skip_check_grad_ci( @skip_check_grad_ci(
reason="[skip shape check] Use y_shape(1) to test broadcast." reason="[skip shape check] Use y_shape(1) to test broadcast."
...@@ -388,7 +369,7 @@ class TestElementwiseBF16Op(OpTest): ...@@ -388,7 +369,7 @@ class TestElementwiseBF16Op(OpTest):
def test_check_grad_ingore_x(self): def test_check_grad_ingore_x(self):
places = self._get_places() places = self._get_places()
for place in places: for place in places:
if type(place) is paddle.fluid.libpaddle.CPUPlace: if isinstance(place, paddle.fluid.libpaddle.CPUPlace):
check_prim = False check_prim = False
else: else:
check_prim = True check_prim = True
...@@ -413,7 +394,7 @@ class TestElementwiseBF16Op(OpTest): ...@@ -413,7 +394,7 @@ class TestElementwiseBF16Op(OpTest):
def test_check_grad_ingore_y(self): def test_check_grad_ingore_y(self):
places = self._get_places() places = self._get_places()
for place in places: for place in places:
if type(place) is paddle.fluid.libpaddle.CPUPlace: if isinstance(place, paddle.fluid.libpaddle.CPUPlace):
check_prim = False check_prim = False
else: else:
check_prim = True check_prim = True
...@@ -436,7 +417,7 @@ class TestElementwiseBF16Op(OpTest): ...@@ -436,7 +417,7 @@ class TestElementwiseBF16Op(OpTest):
) )
def if_enable_cinn(self): def if_enable_cinn(self):
self.enable_cinn = False pass
class TestElementwiseMinBF16Op_ZeroDim1(TestElementwiseBF16Op): class TestElementwiseMinBF16Op_ZeroDim1(TestElementwiseBF16Op):
......
test/legacy_test/test_erf_op.py
浏览文件 @ bd1a240b
...@@ -57,15 +57,17 @@ class TestErfLayer(unittest.TestCase): ...@@ -57,15 +57,17 @@ class TestErfLayer(unittest.TestCase):
np.testing.assert_allclose(y_ref, y_test, rtol=1e-05) np.testing.assert_allclose(y_ref, y_test, rtol=1e-05)
def test_case(self): def test_case(self):
self._test_case(fluid.CPUPlace()) with paddle.fluid.framework._static_guard():
if fluid.is_compiled_with_cuda(): self._test_case(fluid.CPUPlace())
self._test_case(fluid.CUDAPlace(0)) if fluid.is_compiled_with_cuda():
self._test_case(fluid.CUDAPlace(0))
def test_name(self): def test_name(self):
with fluid.program_guard(fluid.Program()): with paddle.fluid.framework._static_guard():
x = paddle.static.data('x', [3, 4]) with fluid.program_guard(fluid.Program()):
y = paddle.erf(x, name='erf') x = paddle.static.data('x', [3, 4])
self.assertTrue('erf' in y.name) y = paddle.erf(x, name='erf')
self.assertTrue('erf' in y.name)
class TestErfFP16OP(OpTest): class TestErfFP16OP(OpTest):
......
test/legacy_test/test_fill_any_like_op.py
浏览文件 @ bd1a240b
...@@ -88,7 +88,7 @@ class TestFillAnyLikeOpBfloat16(OpTest): ...@@ -88,7 +88,7 @@ class TestFillAnyLikeOpBfloat16(OpTest):
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place, check_prim=True)
def if_enable_cinn(self): def if_enable_cinn(self):
self.enable_cinn = False pass
class TestFillAnyLikeOpValue1(TestFillAnyLikeOp): class TestFillAnyLikeOpValue1(TestFillAnyLikeOp):
......
test/legacy_test/test_flatten_contiguous_range_op.py
浏览文件 @ bd1a240b
...@@ -30,7 +30,7 @@ class TestFlattenOp(OpTest): ...@@ -30,7 +30,7 @@ class TestFlattenOp(OpTest):
self.prim_op_type = "comp" self.prim_op_type = "comp"
self.start_axis = 0 self.start_axis = 0
self.stop_axis = -1 self.stop_axis = -1
self.skip_cinn() self.if_enable_cinn()
self.init_test_case() self.init_test_case()
self.init_test_dtype() self.init_test_dtype()
self.init_input_data() self.init_input_data()
...@@ -40,8 +40,8 @@ class TestFlattenOp(OpTest): ...@@ -40,8 +40,8 @@ class TestFlattenOp(OpTest):
"XShape": np.random.random(self.in_shape).astype("float32"), "XShape": np.random.random(self.in_shape).astype("float32"),
} }
def skip_cinn(self): def if_enable_cinn(self):
self.enable_cinn = True pass
def test_check_output(self): def test_check_output(self):
if str(self.dtype) in {"float16", "uint16"}: if str(self.dtype) in {"float16", "uint16"}:
...@@ -104,6 +104,9 @@ class TestFlattenFP16Op(TestFlattenOp): ...@@ -104,6 +104,9 @@ class TestFlattenFP16Op(TestFlattenOp):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op(TestFlattenOp): class TestFlattenBF16Op(TestFlattenOp):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -142,6 +145,9 @@ class TestFlattenFP16Op_1(TestFlattenOp_1): ...@@ -142,6 +145,9 @@ class TestFlattenFP16Op_1(TestFlattenOp_1):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op_1(TestFlattenOp_1): class TestFlattenBF16Op_1(TestFlattenOp_1):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -180,6 +186,9 @@ class TestFlattenFP16Op_2(TestFlattenOp_2): ...@@ -180,6 +186,9 @@ class TestFlattenFP16Op_2(TestFlattenOp_2):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op_2(TestFlattenOp_2): class TestFlattenBF16Op_2(TestFlattenOp_2):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -218,6 +227,9 @@ class TestFlattenFP16Op_3(TestFlattenOp_3): ...@@ -218,6 +227,9 @@ class TestFlattenFP16Op_3(TestFlattenOp_3):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op_3(TestFlattenOp_3): class TestFlattenBF16Op_3(TestFlattenOp_3):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -256,6 +268,9 @@ class TestFlattenFP16Op_4(TestFlattenOp_4): ...@@ -256,6 +268,9 @@ class TestFlattenFP16Op_4(TestFlattenOp_4):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op_4(TestFlattenOp_4): class TestFlattenBF16Op_4(TestFlattenOp_4):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -294,6 +309,9 @@ class TestFlattenFP16Op_5(TestFlattenOp_5): ...@@ -294,6 +309,9 @@ class TestFlattenFP16Op_5(TestFlattenOp_5):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16Op_5(TestFlattenOp_5): class TestFlattenBF16Op_5(TestFlattenOp_5):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
...@@ -305,7 +323,7 @@ class TestFlattenOp_ZeroDim(TestFlattenOp): ...@@ -305,7 +323,7 @@ class TestFlattenOp_ZeroDim(TestFlattenOp):
self.stop_axis = -1 self.stop_axis = -1
self.new_shape = (1,) self.new_shape = (1,)
def skip_cinn(self): def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
def init_attrs(self): def init_attrs(self):
...@@ -363,6 +381,9 @@ class TestFlattenFP16OpSixDims(TestFlattenOpSixDims): ...@@ -363,6 +381,9 @@ class TestFlattenFP16OpSixDims(TestFlattenOpSixDims):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestFlattenBF16OpSixDims(TestFlattenOpSixDims): class TestFlattenBF16OpSixDims(TestFlattenOpSixDims):
def if_enable_cinn(self):
pass
def init_test_dtype(self): def init_test_dtype(self):
self.dtype = "uint16" self.dtype = "uint16"
......
test/legacy_test/test_index_select_op.py
浏览文件 @ bd1a240b
...@@ -19,7 +19,7 @@ from eager_op_test import OpTest, convert_float_to_uint16 ...@@ -19,7 +19,7 @@ from eager_op_test import OpTest, convert_float_to_uint16
import paddle import paddle
from paddle import fluid from paddle import fluid
from paddle.fluid import Program, program_guard from paddle.fluid import Program, core, program_guard
np.random.seed(1024) np.random.seed(1024)
...@@ -102,8 +102,11 @@ class TestIndexSelectFP16OP(TestIndexSelectOp): ...@@ -102,8 +102,11 @@ class TestIndexSelectFP16OP(TestIndexSelectOp):
class TestIndexSelectBF16Op(OpTest): class TestIndexSelectBF16Op(OpTest):
def setUp(self): def setUp(self):
self.python_api = paddle.index_select self.python_api = paddle.index_select
self.public_python_api = paddle.index_select
self.prim_op_type = "comp"
self.op_type = "index_select" self.op_type = "index_select"
self.init_dtype_type() self.init_dtype_type()
self.if_skip_cinn()
index_np = np.random.randint( index_np = np.random.randint(
low=0, high=self.x_shape[self.dim], size=self.index_size low=0, high=self.x_shape[self.dim], size=self.index_size
) )
...@@ -124,6 +127,9 @@ class TestIndexSelectBF16Op(OpTest): ...@@ -124,6 +127,9 @@ class TestIndexSelectBF16Op(OpTest):
out = np.reshape(out_list, self.out_shape) out = np.reshape(out_list, self.out_shape)
self.outputs = {'Out': convert_float_to_uint16(out)} self.outputs = {'Out': convert_float_to_uint16(out)}
def if_skip_cinn(self):
self.enable_cinn = False
def init_dtype_type(self): def init_dtype_type(self):
self.dim = 1 self.dim = 1
self.x_type = np.uint16 self.x_type = np.uint16
...@@ -132,10 +138,12 @@ class TestIndexSelectBF16Op(OpTest): ...@@ -132,10 +138,12 @@ class TestIndexSelectBF16Op(OpTest):
self.index_size = 100 self.index_size = 100
def test_check_output(self): def test_check_output(self):
self.check_output() place = core.CUDAPlace(0)
self.check_output_with_place(place)
def test_check_grad_normal(self): def test_check_grad_normal(self):
self.check_grad(['X'], 'Out') place = core.CUDAPlace(0)
self.check_grad_with_place(place, ['X'], 'Out', check_prim=True)
class TestIndexSelectAPI(unittest.TestCase): class TestIndexSelectAPI(unittest.TestCase):
......
test/legacy_test/test_pad_op.py
浏览文件 @ bd1a240b
...@@ -100,7 +100,7 @@ def create_test_fp16(parent): ...@@ -100,7 +100,7 @@ def create_test_fp16(parent):
return np.float16 return np.float16
def test_check_grad_normal(self): def test_check_grad_normal(self):
self.check_grad(['X'], 'Out') self.check_grad(['X'], 'Out', check_prim=True)
cls_name = "{}_{}".format(parent.__name__, "Fp16") cls_name = "{}_{}".format(parent.__name__, "Fp16")
TestPadFp16.__name__ = cls_name TestPadFp16.__name__ = cls_name
...@@ -238,9 +238,12 @@ class TestPadBP16Op(OpTest): ...@@ -238,9 +238,12 @@ class TestPadBP16Op(OpTest):
) )
self.inputs = {'X': convert_float_to_uint16(x)} self.inputs = {'X': convert_float_to_uint16(x)}
self.outputs = {'Out': convert_float_to_uint16(out)} self.outputs = {'Out': convert_float_to_uint16(out)}
self.enable_cinn = False
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.public_python_api = pad_wrapper self.public_python_api = pad_wrapper
self.if_enable_cinn()
def if_enable_cinn(self):
pass
def initTestCase(self): def initTestCase(self):
self.shape = (16, 16) self.shape = (16, 16)
......
test/legacy_test/test_roll_op.py
浏览文件 @ bd1a240b
...@@ -53,9 +53,6 @@ class TestRollOp(OpTest): ...@@ -53,9 +53,6 @@ class TestRollOp(OpTest):
def test_check_grad_normal(self): def test_check_grad_normal(self):
self.check_grad(['X'], 'Out', check_prim=True) self.check_grad(['X'], 'Out', check_prim=True)
def test_check_grad(self):
self.check_grad(['X'], 'Out', check_prim=True)
class TestRollOpCase2(TestRollOp): class TestRollOpCase2(TestRollOp):
def init_dtype_type(self): def init_dtype_type(self):
......
test/legacy_test/test_scatter_op.py
浏览文件 @ bd1a240b
...@@ -31,6 +31,7 @@ class TestScatterOp(OpTest): ...@@ -31,6 +31,7 @@ class TestScatterOp(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 50)).astype(target_dtype) ref_np = np.ones((3, 50)).astype(target_dtype)
index_np = np.array([1, 2]).astype("int32") index_np = np.array([1, 2]).astype("int32")
...@@ -44,11 +45,14 @@ class TestScatterOp(OpTest): ...@@ -44,11 +45,14 @@ class TestScatterOp(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
self.check_output(check_prim=True) self.check_output()
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X", "Updates"], "Out", check_prim=True) self.check_grad(["X", "Updates"], "Out", check_prim=True)
...@@ -67,12 +71,14 @@ class TestScatterFP16Op(TestScatterOp): ...@@ -67,12 +71,14 @@ class TestScatterFP16Op(TestScatterOp):
class TestScatterBF16Op(TestScatterOp): class TestScatterBF16Op(TestScatterOp):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -91,6 +97,7 @@ class TestScatterOp0(OpTest): ...@@ -91,6 +97,7 @@ class TestScatterOp0(OpTest):
self.python_api = paddle.scatter self.python_api = paddle.scatter
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.if_enable_cinn()
self._set_dtype() self._set_dtype()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
...@@ -106,11 +113,14 @@ class TestScatterOp0(OpTest): ...@@ -106,11 +113,14 @@ class TestScatterOp0(OpTest):
self.attrs = {'overwrite': True} self.attrs = {'overwrite': True}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
self.check_output(check_prim=True) self.check_output()
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X", "Updates"], "Out", check_prim=True) self.check_grad(["X", "Updates"], "Out", check_prim=True)
...@@ -129,12 +139,14 @@ class TestScatterFP16Op0(TestScatterOp0): ...@@ -129,12 +139,14 @@ class TestScatterFP16Op0(TestScatterOp0):
class TestScatterBF16Op0(TestScatterOp0): class TestScatterBF16Op0(TestScatterOp0):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -154,6 +166,7 @@ class TestScatterOp1(OpTest): ...@@ -154,6 +166,7 @@ class TestScatterOp1(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
zeros_np = np.zeros([2, 3]).astype(target_dtype) zeros_np = np.zeros([2, 3]).astype(target_dtype)
...@@ -171,11 +184,14 @@ class TestScatterOp1(OpTest): ...@@ -171,11 +184,14 @@ class TestScatterOp1(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
self.check_output(check_prim=True) self.check_output()
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X", "Updates"], "Out", check_prim=True) self.check_grad(["X", "Updates"], "Out", check_prim=True)
...@@ -194,12 +210,14 @@ class TestScatterFP16Op1(TestScatterOp1): ...@@ -194,12 +210,14 @@ class TestScatterFP16Op1(TestScatterOp1):
class TestScatterBF16Op1(TestScatterOp1): class TestScatterBF16Op1(TestScatterOp1):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -222,6 +240,7 @@ class TestScatterOp2(OpTest): ...@@ -222,6 +240,7 @@ class TestScatterOp2(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
index_np = np.array([1, 2]).astype("int32") index_np = np.array([1, 2]).astype("int32")
...@@ -235,13 +254,16 @@ class TestScatterOp2(OpTest): ...@@ -235,13 +254,16 @@ class TestScatterOp2(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, atol=1e-3, check_prim=True) self.check_output_with_place(place, atol=1e-3)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -270,6 +292,8 @@ class TestScatterFP16Op2(TestScatterOp2): ...@@ -270,6 +292,8 @@ class TestScatterFP16Op2(TestScatterOp2):
class TestScatterBF16Op2(TestScatterOp2): class TestScatterBF16Op2(TestScatterOp2):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
...@@ -283,6 +307,7 @@ class TestScatterOp3(OpTest): ...@@ -283,6 +307,7 @@ class TestScatterOp3(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
zeros_np = np.zeros([2, 3]).astype(target_dtype) zeros_np = np.zeros([2, 3]).astype(target_dtype)
...@@ -300,13 +325,16 @@ class TestScatterOp3(OpTest): ...@@ -300,13 +325,16 @@ class TestScatterOp3(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, atol=1e-3, check_prim=True) self.check_output_with_place(place, atol=1e-3)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -335,6 +363,8 @@ class TestScatterFP16Op3(TestScatterOp3): ...@@ -335,6 +363,8 @@ class TestScatterFP16Op3(TestScatterOp3):
class TestScatterBF16Op3(TestScatterOp3): class TestScatterBF16Op3(TestScatterOp3):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
...@@ -345,6 +375,7 @@ class TestScatterOp4(OpTest): ...@@ -345,6 +375,7 @@ class TestScatterOp4(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
index_np = np.array([1, 2]).astype("int64") index_np = np.array([1, 2]).astype("int64")
...@@ -358,11 +389,14 @@ class TestScatterOp4(OpTest): ...@@ -358,11 +389,14 @@ class TestScatterOp4(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
self.check_output(check_prim=True) self.check_output()
def test_check_grad(self): def test_check_grad(self):
self.check_grad(['X', 'Updates'], 'Out', check_prim=True) self.check_grad(['X', 'Updates'], 'Out', check_prim=True)
...@@ -381,12 +415,14 @@ class TestScatterFP16Op4(TestScatterOp4): ...@@ -381,12 +415,14 @@ class TestScatterFP16Op4(TestScatterOp4):
class TestScatterBF16Op4(TestScatterOp4): class TestScatterBF16Op4(TestScatterOp4):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -409,6 +445,7 @@ class TestScatterOp5(OpTest): ...@@ -409,6 +445,7 @@ class TestScatterOp5(OpTest):
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self._set_dtype() self._set_dtype()
self.if_enable_cinn()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 3)).astype(target_dtype) ref_np = np.ones((3, 3)).astype(target_dtype)
index_np = np.array([1, 2]).astype("int64") index_np = np.array([1, 2]).astype("int64")
...@@ -422,13 +459,16 @@ class TestScatterOp5(OpTest): ...@@ -422,13 +459,16 @@ class TestScatterOp5(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, atol=1e-3, check_prim=True) self.check_output_with_place(place, atol=1e-3)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
...@@ -457,6 +497,8 @@ class TestScatterFP16Op5(TestScatterOp5): ...@@ -457,6 +497,8 @@ class TestScatterFP16Op5(TestScatterOp5):
class TestScatterBF16Op5(TestScatterOp5): class TestScatterBF16Op5(TestScatterOp5):
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def if_enable_cinn(self):
self.enable_cinn = False self.enable_cinn = False
...@@ -466,7 +508,7 @@ class TestScatterOp6(OpTest): ...@@ -466,7 +508,7 @@ class TestScatterOp6(OpTest):
self.python_api = paddle.scatter self.python_api = paddle.scatter
self.public_python_api = paddle.scatter self.public_python_api = paddle.scatter
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = False self.if_enable_cinn()
self._set_dtype() self._set_dtype()
target_dtype = "float16" if self.dtype == np.float16 else "float32" target_dtype = "float16" if self.dtype == np.float16 else "float32"
ref_np = np.ones((3, 50)).astype(target_dtype) ref_np = np.ones((3, 50)).astype(target_dtype)
...@@ -481,11 +523,14 @@ class TestScatterOp6(OpTest): ...@@ -481,11 +523,14 @@ class TestScatterOp6(OpTest):
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np} self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np} self.outputs = {'Out': output_np}
def if_enable_cinn(self):
pass
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def test_check_output(self): def test_check_output(self):
self.check_output(check_prim=True) self.check_output()
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X", "Updates"], "Out", check_prim=True) self.check_grad(["X", "Updates"], "Out", check_prim=True)
...@@ -502,13 +547,16 @@ class TestScatterFP16Op6(TestScatterOp6): ...@@ -502,13 +547,16 @@ class TestScatterFP16Op6(TestScatterOp6):
"core is not complied with CUDA and not support the bfloat16", "core is not complied with CUDA and not support the bfloat16",
) )
class TestScatterBF16Op6(TestScatterOp6): class TestScatterBF16Op6(TestScatterOp6):
def if_enable_cinn(self):
self.enable_cinn = False
def _set_dtype(self): def _set_dtype(self):
self.dtype = np.uint16 self.dtype = np.uint16
def test_check_output(self): def test_check_output(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_prim=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
if core.is_compiled_with_cuda(): if core.is_compiled_with_cuda():
......
test/legacy_test/test_split_op.py
浏览文件 @ bd1a240b
...@@ -32,7 +32,6 @@ class TestSplitOp(OpTest): ...@@ -32,7 +32,6 @@ class TestSplitOp(OpTest):
self.dtype = self.get_dtype() self.dtype = self.get_dtype()
axis = 1 axis = 1
if self.dtype == np.uint16: if self.dtype == np.uint16:
self.enable_cinn = False
x = np.random.random((4, 5, 6)).astype(np.float32) x = np.random.random((4, 5, 6)).astype(np.float32)
out = np.split(x, [2, 3], axis) out = np.split(x, [2, 3], axis)
self.inputs = {'X': convert_float_to_uint16(x)} self.inputs = {'X': convert_float_to_uint16(x)}
...@@ -285,7 +284,7 @@ def create_test_bf16(parent): ...@@ -285,7 +284,7 @@ def create_test_bf16(parent):
def test_check_grad(self): def test_check_grad(self):
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_grad_with_place(place, ['X'], 'out2') self.check_grad_with_place(place, ['X'], 'out2', check_prim=True)
cls_name = "{}_{}".format(parent.__name__, "BF16Op") cls_name = "{}_{}".format(parent.__name__, "BF16Op")
TestSplitBF16Op.__name__ = cls_name TestSplitBF16Op.__name__ = cls_name
......
test/legacy_test/test_squeeze2_op.py
浏览文件 @ bd1a240b
...@@ -16,10 +16,11 @@ import os ...@@ -16,10 +16,11 @@ import os
import unittest import unittest
import numpy as np import numpy as np
from eager_op_test import OpTest from eager_op_test import OpTest, convert_float_to_uint16
from test_attribute_var import UnittestBase from test_attribute_var import UnittestBase
import paddle import paddle
from paddle.fluid import core
from paddle.fluid.framework import Program, program_guard from paddle.fluid.framework import Program, program_guard
paddle.enable_static() paddle.enable_static()
...@@ -36,19 +37,32 @@ class TestSqueezeOp(OpTest): ...@@ -36,19 +37,32 @@ class TestSqueezeOp(OpTest):
"Out" "Out"
] # python out sig is customized output signature. ] # python out sig is customized output signature.
self.init_test_case() self.init_test_case()
self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")} self.init_dtype()
self.if_enable_cinn()
x = np.random.random(self.ori_shape).astype("float64")
xshape = np.random.random(self.ori_shape).astype("float64")
if hasattr(self, "dtype") and self.dtype == np.uint16:
x = convert_float_to_uint16(x.astype(np.float32))
xshape = convert_float_to_uint16(xshape.astype(np.float32))
self.inputs = {"X": x}
self.init_attrs() self.init_attrs()
self.outputs = { self.outputs = {
"Out": self.inputs["X"].reshape(self.new_shape), "Out": self.inputs["X"].reshape(self.new_shape),
"XShape": np.random.random(self.ori_shape).astype("float64"), "XShape": xshape,
} }
def if_enable_cinn(self):
pass
def test_check_output(self): def test_check_output(self):
self.check_output(no_check_set=['XShape'], check_prim=True) self.check_output(no_check_set=['XShape'], check_prim=True)
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X"], "Out", check_prim=True) self.check_grad(["X"], "Out", check_prim=True)
def init_dtype(self):
self.dtype = np.float64
def init_test_case(self): def init_test_case(self):
self.ori_shape = (1, 3, 1, 40) self.ori_shape = (1, 3, 1, 40)
self.axes = (0, 2) self.axes = (0, 2)
...@@ -58,6 +72,16 @@ class TestSqueezeOp(OpTest): ...@@ -58,6 +72,16 @@ class TestSqueezeOp(OpTest):
self.attrs = {"axes": self.axes} self.attrs = {"axes": self.axes}
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA and do not support bfloat16",
)
class TestSqueezeOpBF16OP(TestSqueezeOp):
def init_dtype(self):
self.dtype = np.uint16
# Correct: There is mins axis. # Correct: There is mins axis.
class TestSqueezeOp1(TestSqueezeOp): class TestSqueezeOp1(TestSqueezeOp):
def init_test_case(self): def init_test_case(self):
...@@ -66,6 +90,16 @@ class TestSqueezeOp1(TestSqueezeOp): ...@@ -66,6 +90,16 @@ class TestSqueezeOp1(TestSqueezeOp):
self.new_shape = (20, 5) self.new_shape = (20, 5)
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA and do not support bfloat16",
)
class TestSqueezeOp1BF16Op(TestSqueezeOp):
def init_dtype(self):
self.dtype = np.uint16
# Correct: No axes input. # Correct: No axes input.
class TestSqueezeOp2(TestSqueezeOp): class TestSqueezeOp2(TestSqueezeOp):
def setUp(self): def setUp(self):
...@@ -77,19 +111,42 @@ class TestSqueezeOp2(TestSqueezeOp): ...@@ -77,19 +111,42 @@ class TestSqueezeOp2(TestSqueezeOp):
"Out" "Out"
] # python out sig is customized output signature. ] # python out sig is customized output signature.
self.init_test_case() self.init_test_case()
self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")} self.init_dtype()
self.if_enable_cinn()
x = np.random.random(self.ori_shape).astype("float64")
xshape = np.random.random(self.ori_shape).astype("float64")
if hasattr(self, "dtype") and self.dtype == np.uint16:
x = convert_float_to_uint16(x.astype(np.float32))
xshape = convert_float_to_uint16(xshape.astype(np.float32))
self.inputs = {"X": x}
self.init_attrs() self.init_attrs()
self.outputs = { self.outputs = {
"Out": self.inputs["X"].reshape(self.new_shape), "Out": self.inputs["X"].reshape(self.new_shape),
"XShape": np.random.random(self.ori_shape).astype("float64"), "XShape": xshape,
} }
def if_enable_cinn(self):
pass
def init_dtype(self):
self.dtype = np.float64
def init_test_case(self): def init_test_case(self):
self.ori_shape = (1, 20, 1, 5) self.ori_shape = (1, 20, 1, 5)
self.axes = () self.axes = ()
self.new_shape = (20, 5) self.new_shape = (20, 5)
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA and do not support bfloat16",
)
class TestSqueezeOp2BF16Op(TestSqueezeOp):
def init_dtype(self):
self.dtype = np.uint16
# Correct: Just part of axes be squeezed. # Correct: Just part of axes be squeezed.
class TestSqueezeOp3(TestSqueezeOp): class TestSqueezeOp3(TestSqueezeOp):
def init_test_case(self): def init_test_case(self):
...@@ -98,6 +155,16 @@ class TestSqueezeOp3(TestSqueezeOp): ...@@ -98,6 +155,16 @@ class TestSqueezeOp3(TestSqueezeOp):
self.new_shape = (6, 5, 1, 4) self.new_shape = (6, 5, 1, 4)
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA and do not support bfloat16",
)
class TestSqueezeOp3BF16Op(TestSqueezeOp):
def init_dtype(self):
self.dtype = np.uint16
class TestSqueeze2AxesTensor(UnittestBase): class TestSqueeze2AxesTensor(UnittestBase):
def init_info(self): def init_info(self):
self.shapes = [[2, 3, 4]] self.shapes = [[2, 3, 4]]
......
test/legacy_test/test_stack_op.py
浏览文件 @ bd1a240b
...@@ -167,7 +167,6 @@ class TestStackBF16Op(OpTest): ...@@ -167,7 +167,6 @@ class TestStackBF16Op(OpTest):
self.initParameters() self.initParameters()
self.op_type = 'stack' self.op_type = 'stack'
self.prim_op_type = "comp" self.prim_op_type = "comp"
self.enable_cinn = False
self.python_api = paddle.stack self.python_api = paddle.stack
self.public_python_api = paddle.stack self.public_python_api = paddle.stack
self.x = [] self.x = []
...@@ -191,8 +190,7 @@ class TestStackBF16Op(OpTest): ...@@ -191,8 +190,7 @@ class TestStackBF16Op(OpTest):
self.check_output(check_prim=True) self.check_output(check_prim=True)
def test_check_grad(self): def test_check_grad(self):
# concat_grad unspport bfloat16 dtype, skip check_prim self.check_grad(self.get_x_names(), 'Y', check_prim=True)
self.check_grad(self.get_x_names(), 'Y')
class TestStackAPIWithLoDTensorArray(unittest.TestCase): class TestStackAPIWithLoDTensorArray(unittest.TestCase):
......
test/legacy_test/test_tile_op.py
浏览文件 @ bd1a240b
...@@ -30,15 +30,18 @@ class TestTileOpRank1(OpTest): ...@@ -30,15 +30,18 @@ class TestTileOpRank1(OpTest):
self.op_type = "tile" self.op_type = "tile"
self.python_api = paddle.tile self.python_api = paddle.tile
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = True
self.public_python_api = paddle.tile self.public_python_api = paddle.tile
self.init_data() self.init_data()
self.if_enable_cinn()
self.inputs = {'X': np.random.random(self.ori_shape).astype("float64")} self.inputs = {'X': np.random.random(self.ori_shape).astype("float64")}
self.attrs = {'repeat_times': self.repeat_times} self.attrs = {'repeat_times': self.repeat_times}
output = np.tile(self.inputs['X'], self.repeat_times) output = np.tile(self.inputs['X'], self.repeat_times)
self.outputs = {'Out': output} self.outputs = {'Out': output}
def if_enable_cinn(self):
pass
def init_data(self): def init_data(self):
self.ori_shape = [100] self.ori_shape = [100]
self.repeat_times = [2] self.repeat_times = [2]
...@@ -52,24 +55,30 @@ class TestTileOpRank1(OpTest): ...@@ -52,24 +55,30 @@ class TestTileOpRank1(OpTest):
class TestTileOpRank_ZeroDim1(TestTileOpRank1): class TestTileOpRank_ZeroDim1(TestTileOpRank1):
def init_data(self): def init_data(self):
self.enable_cinn = False
self.ori_shape = [] self.ori_shape = []
self.repeat_times = [] self.repeat_times = []
def if_enable_cinn(self):
self.enable_cinn = False
class TestTileOpRank_ZeroDim2(TestTileOpRank1): class TestTileOpRank_ZeroDim2(TestTileOpRank1):
def init_data(self): def init_data(self):
self.enable_cinn = False
self.ori_shape = [] self.ori_shape = []
self.repeat_times = [2] self.repeat_times = [2]
def if_enable_cinn(self):
self.enable_cinn = False
class TestTileOpRank_ZeroDim3(TestTileOpRank1): class TestTileOpRank_ZeroDim3(TestTileOpRank1):
def init_data(self): def init_data(self):
self.enable_cinn = False
self.ori_shape = [] self.ori_shape = []
self.repeat_times = [2, 3] self.repeat_times = [2, 3]
def if_enable_cinn(self):
self.enable_cinn = False
# with dimension expanding # with dimension expanding
class TestTileOpRank2Expanding(TestTileOpRank1): class TestTileOpRank2Expanding(TestTileOpRank1):
...@@ -240,7 +249,6 @@ class TestTileBF16OP(OpTest): ...@@ -240,7 +249,6 @@ class TestTileBF16OP(OpTest):
self.__class__.op_type = self.op_type self.__class__.op_type = self.op_type
self.python_api = paddle.tile self.python_api = paddle.tile
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = False
self.public_python_api = paddle.tile self.public_python_api = paddle.tile
self.init_data() self.init_data()
x = np.random.uniform(10, size=self.ori_shape).astype(np.float32) x = np.random.uniform(10, size=self.ori_shape).astype(np.float32)
......
test/legacy_test/test_top_k_v2_op.py
浏览文件 @ bd1a240b
...@@ -15,7 +15,11 @@ ...@@ -15,7 +15,11 @@
import unittest import unittest
import numpy as np import numpy as np
from eager_op_test import OpTest, convert_float_to_uint16 from eager_op_test import (
OpTest,
convert_float_to_uint16,
convert_uint16_to_float,
)
import paddle import paddle
from paddle.fluid import core from paddle.fluid import core
...@@ -51,6 +55,7 @@ class TestTopkOp(OpTest): ...@@ -51,6 +55,7 @@ class TestTopkOp(OpTest):
self.dtype = np.float64 self.dtype = np.float64
self.input_data = np.random.rand(10, 20) self.input_data = np.random.rand(10, 20)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -58,6 +63,9 @@ class TestTopkOp(OpTest): ...@@ -58,6 +63,9 @@ class TestTopkOp(OpTest):
) )
self.outputs = {'Out': output, 'Indices': indices} self.outputs = {'Out': output, 'Indices': indices}
def if_enable_cinn(self):
pass
def test_check_output(self): def test_check_output(self):
self.check_output() self.check_output()
...@@ -115,6 +123,7 @@ class TestTopkOp4(TestTopkOp): ...@@ -115,6 +123,7 @@ class TestTopkOp4(TestTopkOp):
self.dtype = np.float64 self.dtype = np.float64
self.input_data = np.random.rand(10, 10, 5) self.input_data = np.random.rand(10, 10, 5)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -137,6 +146,7 @@ class TestTopkOp5(TestTopkOp): ...@@ -137,6 +146,7 @@ class TestTopkOp5(TestTopkOp):
self.dtype = np.float64 self.dtype = np.float64
self.input_data = np.random.rand(10, 10, 5) self.input_data = np.random.rand(10, 10, 5)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -159,6 +169,7 @@ class TestTopkOp6(TestTopkOp): ...@@ -159,6 +169,7 @@ class TestTopkOp6(TestTopkOp):
self.dtype = np.float32 self.dtype = np.float32
self.input_data = np.random.rand(10, 10, 5) self.input_data = np.random.rand(10, 10, 5)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -181,6 +192,7 @@ class TestTopkOp7(TestTopkOp): ...@@ -181,6 +192,7 @@ class TestTopkOp7(TestTopkOp):
self.dtype = np.float16 self.dtype = np.float16
self.input_data = np.random.rand(10, 20, 10) self.input_data = np.random.rand(10, 20, 10)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -198,6 +210,7 @@ class TestTopkFP16Op(TestTopkOp): ...@@ -198,6 +210,7 @@ class TestTopkFP16Op(TestTopkOp):
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.input_data = np.random.rand(10, 20).astype(self.dtype) self.input_data = np.random.rand(10, 20).astype(self.dtype)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': self.input_data} self.inputs = {'X': self.input_data}
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
...@@ -218,9 +231,11 @@ class TestTopkBF16Op(TestTopkOp): ...@@ -218,9 +231,11 @@ class TestTopkBF16Op(TestTopkOp):
self.public_python_api = paddle.topk self.public_python_api = paddle.topk
self.dtype = np.uint16 self.dtype = np.uint16
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.input_data = np.random.rand(10, 20).astype(np.float32) self.input_data = np.random.random([10, 20]).astype(np.float32)
self.init_args() self.init_args()
self.if_enable_cinn()
self.inputs = {'X': convert_float_to_uint16(self.input_data)} self.inputs = {'X': convert_float_to_uint16(self.input_data)}
self.input_data = convert_uint16_to_float(self.inputs['X'])
self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest} self.attrs = {'k': self.k, 'axis': self.axis, 'largest': self.largest}
output, indices = numpy_topk( output, indices = numpy_topk(
self.input_data, axis=self.axis, k=self.k, largest=self.largest self.input_data, axis=self.axis, k=self.k, largest=self.largest
...@@ -230,13 +245,16 @@ class TestTopkBF16Op(TestTopkOp): ...@@ -230,13 +245,16 @@ class TestTopkBF16Op(TestTopkOp):
'Indices': indices, 'Indices': indices,
} }
def if_enable_cinn(self):
self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_output_with_place(place, check_eager=True) self.check_output_with_place(place)
def test_check_grad(self): def test_check_grad(self):
place = core.CUDAPlace(0) place = core.CUDAPlace(0)
self.check_grad_with_place(place, {'X'}, 'Out', check_eager=True) self.check_grad_with_place(place, ['X'], 'Out', check_prim=True)
class TestTopKAPI(unittest.TestCase): class TestTopKAPI(unittest.TestCase):
......
test/legacy_test/test_transpose_op.py
浏览文件 @ bd1a240b
...@@ -244,7 +244,7 @@ class TestAutoTuneTransposeBF16Op(OpTest): ...@@ -244,7 +244,7 @@ class TestAutoTuneTransposeBF16Op(OpTest):
self.python_api = paddle.transpose self.python_api = paddle.transpose
self.public_python_api = paddle.transpose self.public_python_api = paddle.transpose
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = False self.if_enable_cinn()
x = np.random.random(self.shape).astype("float32") x = np.random.random(self.shape).astype("float32")
self.inputs = {'X': convert_float_to_uint16(x)} self.inputs = {'X': convert_float_to_uint16(x)}
self.attrs = { self.attrs = {
...@@ -258,6 +258,9 @@ class TestAutoTuneTransposeBF16Op(OpTest): ...@@ -258,6 +258,9 @@ class TestAutoTuneTransposeBF16Op(OpTest):
'Out': self.inputs['X'].transpose(self.axis), 'Out': self.inputs['X'].transpose(self.axis),
} }
def if_enable_cinn(self):
self.enable_cinn = False
def initTestCase(self): def initTestCase(self):
fluid.core.set_autotune_range(0, 3) fluid.core.set_autotune_range(0, 3)
fluid.core.update_autotune_status() fluid.core.update_autotune_status()
...@@ -283,7 +286,7 @@ class TestTransposeFP16Op(OpTest): ...@@ -283,7 +286,7 @@ class TestTransposeFP16Op(OpTest):
self.initTestCase() self.initTestCase()
self.dtype = np.float16 self.dtype = np.float16
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.enable_cinn = False self.if_enable_cinn()
self.python_api = paddle.transpose self.python_api = paddle.transpose
self.public_python_api = paddle.transpose self.public_python_api = paddle.transpose
x = np.random.random(self.shape).astype(self.dtype) x = np.random.random(self.shape).astype(self.dtype)
...@@ -298,6 +301,9 @@ class TestTransposeFP16Op(OpTest): ...@@ -298,6 +301,9 @@ class TestTransposeFP16Op(OpTest):
'Out': self.inputs['X'].transpose(self.axis), 'Out': self.inputs['X'].transpose(self.axis),
} }
def if_enable_cinn(self):
pass
def init_op_type(self): def init_op_type(self):
self.op_type = "transpose2" self.op_type = "transpose2"
self.use_mkldnn = False self.use_mkldnn = False
...@@ -323,6 +329,7 @@ class TestTransposeBF16Op(OpTest): ...@@ -323,6 +329,7 @@ class TestTransposeBF16Op(OpTest):
self.python_api = paddle.transpose self.python_api = paddle.transpose
self.public_python_api = paddle.transpose self.public_python_api = paddle.transpose
x = np.random.random(self.shape).astype("float32") x = np.random.random(self.shape).astype("float32")
self.if_enable_cinn()
self.inputs = {'X': convert_float_to_uint16(x)} self.inputs = {'X': convert_float_to_uint16(x)}
self.attrs = { self.attrs = {
...@@ -336,6 +343,9 @@ class TestTransposeBF16Op(OpTest): ...@@ -336,6 +343,9 @@ class TestTransposeBF16Op(OpTest):
'Out': self.inputs['X'].transpose(self.axis), 'Out': self.inputs['X'].transpose(self.axis),
} }
def if_enable_cinn(self):
self.enable_cinn = False
def init_op_type(self): def init_op_type(self):
self.op_type = "transpose2" self.op_type = "transpose2"
self.use_mkldnn = False self.use_mkldnn = False
......
test/legacy_test/test_unsqueeze2_op.py
浏览文件 @ bd1a240b
...@@ -37,12 +37,16 @@ class TestUnsqueezeOp(OpTest): ...@@ -37,12 +37,16 @@ class TestUnsqueezeOp(OpTest):
"XShape": np.random.random(self.ori_shape).astype("float64"), "XShape": np.random.random(self.ori_shape).astype("float64"),
} }
self.prim_op_type = "comp" self.prim_op_type = "comp"
self.if_enable_cinn()
def if_enable_cinn(self):
pass
def test_check_output(self): def test_check_output(self):
self.check_output(no_check_set=["XShape"], check_prim=True) self.check_output(no_check_set=["XShape"], check_prim=True)
def test_check_grad(self): def test_check_grad(self):
self.check_grad(["X"], "Out") self.check_grad(["X"], "Out", check_prim=True)
def init_test_case(self): def init_test_case(self):
self.ori_shape = (3, 40) self.ori_shape = (3, 40)
...@@ -90,7 +94,6 @@ class TestUnsqueezeOp_ZeroDim1(TestUnsqueezeOp): ...@@ -90,7 +94,6 @@ class TestUnsqueezeOp_ZeroDim1(TestUnsqueezeOp):
self.ori_shape = () self.ori_shape = ()
self.axes = (-1,) self.axes = (-1,)
self.new_shape = 1 self.new_shape = 1
self.enable_cinn = False
class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp): class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp):
...@@ -98,7 +101,6 @@ class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp): ...@@ -98,7 +101,6 @@ class TestUnsqueezeOp_ZeroDim2(TestUnsqueezeOp):
self.ori_shape = () self.ori_shape = ()
self.axes = (-1, 1) self.axes = (-1, 1)
self.new_shape = (1, 1) self.new_shape = (1, 1)
self.enable_cinn = False
class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp): class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp):
...@@ -106,7 +108,6 @@ class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp): ...@@ -106,7 +108,6 @@ class TestUnsqueezeOp_ZeroDim3(TestUnsqueezeOp):
self.ori_shape = () self.ori_shape = ()
self.axes = (0, 1, 2) self.axes = (0, 1, 2)
self.new_shape = (1, 1, 1) self.new_shape = (1, 1, 1)
self.enable_cinn = False
# axes is a list(with tensor) # axes is a list(with tensor)
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或