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Paddle
未验证 提交 2cff9839 编写于 作者: V Vvsmile 提交者： GitHub
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[AMP OP&Test] adjust test_elementwise_sub's tolerance, max_relative_error of grad and (#50953) 

* adjust test_elementwise_sub's tolerance, max_relative_error of grad and
atol/rtol of output to 1e-3

* fix the dtype in setUp

* fix the elementwise_sub optest

* modify elementwise_sub optest

* fix and add bf16/fp16 to elementwise_sub

* fix elementwise_sub bugs

* fix bugs

* fix elementwise_sub op

* fix the data type

* fix elementwise_sub

* fix elementwise

* fix elementwise_sub

* fix bugs

* fix elementwise sub

* fix elementwise_sub

* remove scalar and vector
上级 a7070f34
隐藏空白更改
内联 并排
Showing with 460 addition and 71 deletion
python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py
浏览文件 @ 2cff9839
...@@ -21,6 +21,7 @@ from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci ...@@ -21,6 +21,7 @@ from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci
import paddle import paddle
from paddle import fluid from paddle import fluid
from paddle.fluid import core
from paddle.fluid.layer_helper import LayerHelper from paddle.fluid.layer_helper import LayerHelper
...@@ -30,14 +31,18 @@ class TestElementwiseOp(OpTest): ...@@ -30,14 +31,18 @@ class TestElementwiseOp(OpTest):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype),
'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
self.if_enable_cinn() self.if_enable_cinn()
def init_dtype(self):
self.dtype = np.float64
def test_check_output(self): def test_check_output(self):
self.check_output() self.check_output()
...@@ -66,7 +71,55 @@ class TestElementwiseOp(OpTest): ...@@ -66,7 +71,55 @@ class TestElementwiseOp(OpTest):
self.check_prim = True self.check_prim = True
def if_enable_cinn(self): def if_enable_cinn(self):
pass self.enable_cinn = False
class TestElementwiseFP16OP(TestElementwiseOp):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP(TestElementwiseOp):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.inputs = {
'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(np.float32),
'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
self.if_enable_cinn()
def test_check_grad_normal(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['X', 'Y'], 'Out', max_relative_error=0.1
)
def test_check_grad_ingore_x(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['Y'], 'Out', no_grad_set=set("X"), max_relative_error=0.1
)
def test_check_grad_ingore_y(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['X'], 'Out', no_grad_set=set('Y'), max_relative_error=0.1
)
class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp): class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp):
...@@ -75,19 +128,45 @@ class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp): ...@@ -75,19 +128,45 @@ class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.uniform(0.1, 1, []).astype("float64"), 'X': np.random.uniform(0.1, 1, []).astype(self.dtype),
'Y': np.random.uniform(0.1, 1, []).astype("float64"), 'Y': np.random.uniform(0.1, 1, []).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
self.if_enable_cinn() self.if_enable_cinn()
def if_check_prim(self):
self.check_prim = True
def if_enable_cinn(self): class TestElementwiseSubFP16OP_ZeroDim1(TestElementwiseSubOp_ZeroDim1):
self.enable_cinn = False def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseSubBF16OP_ZeroDim1(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.uniform(0.1, 1, []).astype(np.float32),
'Y': np.random.uniform(0.1, 1, []).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
self.if_enable_cinn()
class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp): class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp):
...@@ -96,19 +175,45 @@ class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp): ...@@ -96,19 +175,45 @@ class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype),
'Y': np.random.uniform(0.1, 1, []).astype("float64"), 'Y': np.random.uniform(0.1, 1, []).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
self.if_enable_cinn() self.if_enable_cinn()
def if_check_prim(self):
self.check_prim = True
def if_enable_cinn(self): class TestElementwiseSubFP16OP_ZeroDim2(TestElementwiseSubOp_ZeroDim2):
self.enable_cinn = False def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseSubBF16OP_ZeroDim2(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(np.float32),
'Y': np.random.uniform(0.1, 1, []).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
self.if_enable_cinn()
class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp): class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp):
...@@ -117,21 +222,52 @@ class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp): ...@@ -117,21 +222,52 @@ class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.uniform(0.1, 1, []).astype("float64"), 'X': np.random.uniform(0.1, 1, []).astype(self.dtype),
'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
self.if_enable_cinn() self.if_enable_cinn()
def if_check_prim(self):
self.check_prim = True
def if_enable_cinn(self): class TestElementwiseSubFP16OP_ZeroDim3(TestElementwiseSubOp_ZeroDim3):
self.enable_cinn = False def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_ZeroDim3(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.uniform(0.1, 1, []).astype(np.float32),
'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
self.if_enable_cinn()
@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 TestBF16ElementwiseOp(OpTest): class TestBF16ElementwiseOp(OpTest):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
...@@ -151,6 +287,12 @@ class TestBF16ElementwiseOp(OpTest): ...@@ -151,6 +287,12 @@ class TestBF16ElementwiseOp(OpTest):
self.if_check_prim() self.if_check_prim()
self.if_enable_cinn() self.if_enable_cinn()
def if_check_prim(self):
self.check_prim = True
def if_enable_cinn(self):
self.enable_cinn = False
def test_check_output(self): def test_check_output(self):
self.check_output() self.check_output()
...@@ -162,17 +304,6 @@ class TestBF16ElementwiseOp(OpTest): ...@@ -162,17 +304,6 @@ class TestBF16ElementwiseOp(OpTest):
['Y'], 'Out', no_grad_set=set("X"), check_prim=self.check_prim ['Y'], 'Out', no_grad_set=set("X"), check_prim=self.check_prim
) )
def test_check_grad_ingore_y(self):
self.check_grad(
['X'], 'Out', no_grad_set=set('Y'), check_prim=self.check_prim
)
def if_check_prim(self):
self.check_prim = True
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."
...@@ -183,9 +314,10 @@ class TestElementwiseSubOp_scalar(TestElementwiseOp): ...@@ -183,9 +314,10 @@ class TestElementwiseSubOp_scalar(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(10, 3, 4).astype(np.float64), 'X': np.random.rand(10, 3, 4).astype(self.dtype),
'Y': np.random.rand(1).astype(np.float64), 'Y': np.random.rand(1).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
...@@ -197,21 +329,23 @@ class TestElementwiseSubOp_Vector(TestElementwiseOp): ...@@ -197,21 +329,23 @@ class TestElementwiseSubOp_Vector(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.random((100,)).astype("float64"), 'X': np.random.random((100,)).astype(self.dtype),
'Y': np.random.random((100,)).astype("float64"), 'Y': np.random.random((100,)).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
class TestElementwiseSubOp_broadcast_O(TestElementwiseOp): class TestElementwiseSubOp_broadcast_0(TestElementwiseOp):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(100, 3, 2).astype(np.float64), 'X': np.random.rand(100, 3, 2).astype(self.dtype),
'Y': np.random.rand(100).astype(np.float64), 'Y': np.random.rand(100).astype(self.dtype),
} }
self.attrs = {'axis': 0} self.attrs = {'axis': 0}
...@@ -244,13 +378,66 @@ class TestElementwiseSubOp_broadcast_O(TestElementwiseOp): ...@@ -244,13 +378,66 @@ class TestElementwiseSubOp_broadcast_O(TestElementwiseOp):
) )
class TestElementwiseSubOp_broadcast_1(TestElementwiseSubOp_broadcast_O): class TestElementwiseSubFP16OP_broadcast_0(TestElementwiseSubOp_broadcast_0):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_broadcast_0(TestElementwiseBF16OP):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.inputs = { self.inputs = {
'X': np.random.rand(2, 100, 3).astype(np.float64), 'X': np.random.rand(100, 3, 2).astype(np.float32),
'Y': np.random.rand(100).astype(np.float64), 'Y': np.random.rand(100).astype(np.float32),
}
self.outputs = {
'Out': self.inputs['X'] - self.inputs['Y'].reshape(100, 1, 1)
}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.attrs = {'axis': 0}
def test_check_output(self):
place = core.CUDAPlace(0)
self.check_output_with_place(place, check_dygraph=False)
def test_check_grad_normal(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['X', 'Y'], 'Out', check_dygraph=False
)
def test_check_grad_ingore_x(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['Y'], 'Out', no_grad_set=set("X"), check_dygraph=False
)
def test_check_grad_ingore_y(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['X'], 'Out', no_grad_set=set('Y'), check_dygraph=False
)
class TestElementwiseSubOp_broadcast_1(TestElementwiseSubOp_broadcast_0):
def setUp(self):
self.op_type = "elementwise_sub"
self.python_api = paddle.subtract
self.init_dtype()
self.inputs = {
'X': np.random.rand(2, 100, 3).astype(self.dtype),
'Y': np.random.rand(100).astype(self.dtype),
} }
self.attrs = {'axis': 1} self.attrs = {'axis': 1}
...@@ -259,15 +446,46 @@ class TestElementwiseSubOp_broadcast_1(TestElementwiseSubOp_broadcast_O): ...@@ -259,15 +446,46 @@ class TestElementwiseSubOp_broadcast_1(TestElementwiseSubOp_broadcast_O):
} }
class TestElementwiseSubFP16OP_broadcast_1(TestElementwiseSubOp_broadcast_1):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_broadcast_1(TestElementwiseBF16OP_broadcast_0):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.inputs = {
'X': np.random.rand(2, 100, 3).astype(np.float32),
'Y': np.random.rand(100).astype(np.float32),
}
self.outputs = {
'Out': self.inputs['X'] - self.inputs['Y'].reshape(1, 100, 1)
}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.attrs = {'axis': 1}
class TestElementwiseSubOp_broadcast_2(TestElementwiseOp): class TestElementwiseSubOp_broadcast_2(TestElementwiseOp):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(2, 3, 100).astype(np.float64), 'X': np.random.rand(2, 3, 100).astype(self.dtype),
'Y': np.random.rand(100).astype(np.float64), 'Y': np.random.rand(100).astype(self.dtype),
} }
self.outputs = { self.outputs = {
...@@ -275,17 +493,70 @@ class TestElementwiseSubOp_broadcast_2(TestElementwiseOp): ...@@ -275,17 +493,70 @@ class TestElementwiseSubOp_broadcast_2(TestElementwiseOp):
} }
self.if_check_prim() self.if_check_prim()
def if_check_prim(self):
self.check_prim = True class TestElementwiseSubFP16OP_broadcast_2(TestElementwiseSubOp_broadcast_2):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_broadcast_2(TestElementwiseBF16OP_broadcast_0):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.inputs = {
'X': np.random.rand(2, 3, 100).astype(np.float32),
'Y': np.random.rand(100).astype(np.float32),
}
self.outputs = {
'Out': self.inputs['X'] - self.inputs['Y'].reshape(1, 1, 100)
}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
@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 TestElementwiseBF16OP_broadcast_3(TestElementwiseBF16OP_broadcast_0):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.inputs = {
'X': np.random.rand(2, 10, 12, 3).astype(np.float32),
'Y': np.random.rand(10, 12).astype(np.float32),
}
self.outputs = {
'Out': self.inputs['X'] - self.inputs['Y'].reshape(1, 10, 12, 1)
}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.attrs = {'axis': 1}
class TestElementwiseSubOp_broadcast_3(TestElementwiseSubOp_broadcast_O): class TestElementwiseSubOp_broadcast_3(TestElementwiseSubOp_broadcast_0):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(2, 10, 12, 3).astype(np.float64), 'X': np.random.rand(2, 10, 12, 3).astype(self.dtype),
'Y': np.random.rand(10, 12).astype(np.float64), 'Y': np.random.rand(10, 12).astype(self.dtype),
} }
self.attrs = {'axis': 1} self.attrs = {'axis': 1}
...@@ -294,21 +565,52 @@ class TestElementwiseSubOp_broadcast_3(TestElementwiseSubOp_broadcast_O): ...@@ -294,21 +565,52 @@ class TestElementwiseSubOp_broadcast_3(TestElementwiseSubOp_broadcast_O):
} }
class TestElementwiseSubFP16OP_broadcast_3(TestElementwiseSubOp_broadcast_3):
def init_dtype(self):
self.dtype = np.float16
class TestElementwiseSubOp_broadcast_4(TestElementwiseOp): class TestElementwiseSubOp_broadcast_4(TestElementwiseOp):
def setUp(self): def setUp(self):
self.op_type = "elementwise_sub" self.op_type = "elementwise_sub"
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(2, 5, 3, 12).astype(np.float64), 'X': np.random.rand(2, 5, 3, 12).astype(self.dtype),
'Y': np.random.rand(2, 5, 1, 12).astype(np.float64), 'Y': np.random.rand(2, 5, 1, 12).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
def if_check_prim(self):
self.check_prim = True @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 TestElementwiseBF16OP_broadcast_4(TestElementwiseBF16OP_broadcast_0):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.inputs = {
'X': np.random.rand(2, 5, 3, 12).astype(np.float32),
'Y': np.random.rand(2, 5, 1, 12).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
class TestElementwiseSubFP16OP_broadcast_4(TestElementwiseSubOp_broadcast_4):
def init_dtype(self):
self.dtype = np.float16
class TestElementwiseSubOp_commonuse_1(TestElementwiseOp): class TestElementwiseSubOp_commonuse_1(TestElementwiseOp):
...@@ -317,15 +619,43 @@ class TestElementwiseSubOp_commonuse_1(TestElementwiseOp): ...@@ -317,15 +619,43 @@ class TestElementwiseSubOp_commonuse_1(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(2, 3, 100).astype(np.float64), 'X': np.random.rand(2, 3, 100).astype(self.dtype),
'Y': np.random.rand(1, 1, 100).astype(np.float64), 'Y': np.random.rand(1, 1, 100).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
def if_check_prim(self):
self.check_prim = True class TestElementwiseSubFP16OP_commonuse_1(TestElementwiseSubOp_commonuse_1):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_commonuse_1(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.rand(2, 3, 100).astype(np.float32),
'Y': np.random.rand(1, 1, 100).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
class TestElementwiseSubOp_commonuse_2(TestElementwiseOp): class TestElementwiseSubOp_commonuse_2(TestElementwiseOp):
...@@ -334,15 +664,43 @@ class TestElementwiseSubOp_commonuse_2(TestElementwiseOp): ...@@ -334,15 +664,43 @@ class TestElementwiseSubOp_commonuse_2(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(10, 3, 1, 4).astype(np.float64), 'X': np.random.rand(10, 3, 1, 4).astype(self.dtype),
'Y': np.random.rand(10, 1, 12, 1).astype(np.float64), 'Y': np.random.rand(10, 1, 12, 1).astype(self.dtype),
} }
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.if_check_prim() self.if_check_prim()
def if_check_prim(self):
self.check_prim = True class TestElementwiseSubFP16OP_commonuse_2(TestElementwiseSubOp_commonuse_2):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_commonuse_2(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.rand(10, 3, 1, 4).astype(np.float32),
'Y': np.random.rand(10, 1, 12, 1).astype(np.float32),
}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp):
...@@ -351,9 +709,10 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): ...@@ -351,9 +709,10 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp):
self.python_api = paddle.subtract self.python_api = paddle.subtract
self.public_python_api = paddle.subtract self.public_python_api = paddle.subtract
self.prim_op_type = "prim" self.prim_op_type = "prim"
self.init_dtype()
self.inputs = { self.inputs = {
'X': np.random.rand(10, 12).astype(np.float64), 'X': np.random.rand(10, 12).astype(self.dtype),
'Y': np.random.rand(2, 3, 10, 12).astype(np.float64), 'Y': np.random.rand(2, 3, 10, 12).astype(self.dtype),
} }
self.attrs = {'axis': 2} self.attrs = {'axis': 2}
...@@ -362,8 +721,38 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): ...@@ -362,8 +721,38 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp):
} }
self.if_check_prim() self.if_check_prim()
def if_check_prim(self):
self.check_prim = True class TestElementwiseSubFP16OP_xsize_lessthan_ysize(
TestElementwiseSubOp_xsize_lessthan_ysize
):
def init_dtype(self):
self.dtype = np.float16
@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 TestElementwiseBF16OP_xsize_lessthan_ysize(TestElementwiseBF16OP):
def setUp(self):
self.op_type = "elementwise_sub"
self.dtype = np.uint16
self.python_api = paddle.subtract
self.public_python_api = paddle.subtract
self.prim_op_type = "prim"
self.inputs = {
'X': np.random.rand(10, 12).astype(np.float32),
'Y': np.random.rand(2, 3, 10, 12).astype(np.float32),
}
self.attrs = {'axis': 2}
self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
self.inputs = {
'X': convert_float_to_uint16(self.inputs['X']),
'Y': convert_float_to_uint16(self.inputs['Y']),
}
self.outputs = {'Out': convert_float_to_uint16(self.outputs['Out'])}
self.if_check_prim()
class TestComplexElementwiseSubOp(OpTest): class TestComplexElementwiseSubOp(OpTest):
...@@ -473,7 +862,7 @@ class TestSubtractApi(unittest.TestCase): ...@@ -473,7 +862,7 @@ class TestSubtractApi(unittest.TestCase):
def test_name(self): def test_name(self):
with fluid.program_guard(fluid.Program()): with fluid.program_guard(fluid.Program()):
x = paddle.static.data(name="x", shape=[2, 3], dtype="float32") x = paddle.static.data(name="x", shape=[2, 3], dtype="float32")
y = paddle.static.data(name='y', shape=[2, 3], dtype='float32') y = paddle.static.data(name='y', shape=[2, 3], dtype=np.float32)
y_1 = self._executed_api(x, y, name='subtract_res') y_1 = self._executed_api(x, y, name='subtract_res')
self.assertEqual(('subtract_res' in y_1.name), True) self.assertEqual(('subtract_res' in y_1.name), True)
...@@ -483,12 +872,12 @@ class TestSubtractApi(unittest.TestCase): ...@@ -483,12 +872,12 @@ class TestSubtractApi(unittest.TestCase):
def gen_data(): def gen_data():
return { return {
"x": np.array([2, 3, 4]).astype('float32'), "x": np.array([2, 3, 4]).astype(np.float32),
"y": np.array([1, 5, 2]).astype('float32'), "y": np.array([1, 5, 2]).astype(np.float32),
} }
x = paddle.static.data(name="x", shape=[3], dtype='float32') x = paddle.static.data(name="x", shape=[3], dtype=np.float32)
y = paddle.static.data(name="y", shape=[3], dtype='float32') y = paddle.static.data(name="y", shape=[3], dtype=np.float32)
z = self._executed_api(x, y) z = self._executed_api(x, y)
place = fluid.CPUPlace() place = fluid.CPUPlace()
exe = fluid.Executor(place) exe = fluid.Executor(place)
...@@ -640,7 +1029,7 @@ class TestTensorSubAPIWarnings(unittest.TestCase): ...@@ -640,7 +1029,7 @@ class TestTensorSubAPIWarnings(unittest.TestCase):
paddle.enable_static() paddle.enable_static()
helper = LayerHelper("elementwise_sub") helper = LayerHelper("elementwise_sub")
data = paddle.static.data( data = paddle.static.data(
name='data', shape=[None, 3, 32, 32], dtype='float32' name='data', shape=[None, 3, 32, 32], dtype=np.float32
) )
out = helper.create_variable_for_type_inference(dtype=data.dtype) out = helper.create_variable_for_type_inference(dtype=data.dtype)
os.environ['FLAGS_print_extra_attrs'] = "1" os.environ['FLAGS_print_extra_attrs'] = "1"
......
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