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【Hackathon No.64】matmul_with_flatten 算子FP16/BF16单测完善 #52953

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Merged
merged 1 commit into from
May 4, 2023
Merged

【Hackathon No.64】matmul_with_flatten 算子FP16/BF16单测完善 #52953

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1 change: 1 addition & 0 deletions paddle/phi/kernels/gpu/matmul_grad_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -64,4 +64,5 @@ PD_REGISTER_KERNEL(matmul_with_flatten_double_grad,
phi::MatmulWithFlattenDoubleGradKernel,
float,
double,
phi::dtype::bfloat16,
phi::dtype::float16) {}
126 changes: 115 additions & 11 deletions python/paddle/fluid/tests/unittests/test_mul_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
from paddle.fluid import core

sys.path.append("..")
from eager_op_test import OpTest
from eager_op_test import OpTest, convert_float_to_uint16


class TestMulOp(OpTest):
Expand Down Expand Up @@ -114,14 +114,14 @@ def test_check_grad_ignore_y(self):
@unittest.skipIf(
not core.is_compiled_with_cuda(), "core is not compiled with CUDA"
)
class TestFP16MulOp1(TestMulOp):
class TestMulFP16Op1(TestMulOp):
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前向测试中的atol还未修改，需要补充修改

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已修改

def init_dtype_type(self):
self.dtype = np.float16

def test_check_output(self):
place = core.CUDAPlace(0)
if core.is_float16_supported(place):
self.check_output_with_place(place, atol=1e-1, check_dygraph=False)
self.check_output_with_place(place, check_dygraph=False)

def test_check_grad_normal(self):
place = core.CUDAPlace(0)
Expand All @@ -130,7 +130,6 @@ def test_check_grad_normal(self):
place,
['X', 'Y'],
'Out',
max_relative_error=0.5,
check_dygraph=False,
)

Expand All @@ -141,7 +140,6 @@ def test_check_grad_ingore_x(self):
place,
['Y'],
'Out',
max_relative_error=0.5,
no_grad_set=set("X"),
check_dygraph=False,
)
Expand All @@ -153,7 +151,6 @@ def test_check_grad_ingore_y(self):
place,
['X'],
'Out',
max_relative_error=0.5,
no_grad_set=set('Y'),
check_dygraph=False,
)
Expand All @@ -162,14 +159,14 @@ def test_check_grad_ingore_y(self):
@unittest.skipIf(
not core.is_compiled_with_cuda(), "core is not compiled with CUDA"
)
class TestFP16MulOp2(TestMulOp2):
class TestMulFP16Op2(TestMulOp2):
def init_dtype_type(self):
self.dtype = np.float16

def test_check_output(self):
place = core.CUDAPlace(0)
if core.is_float16_supported(place):
self.check_output_with_place(place, atol=2e-1, check_dygraph=False)
self.check_output_with_place(place, check_dygraph=False)

def test_check_grad_normal(self):
place = core.CUDAPlace(0)
Expand All @@ -178,7 +175,6 @@ def test_check_grad_normal(self):
place,
['X', 'Y'],
'Out',
max_relative_error=0.9,
check_dygraph=False,
)

Expand All @@ -189,7 +185,6 @@ def test_check_grad_ingore_x(self):
place,
['Y'],
'Out',
max_relative_error=0.5,
no_grad_set=set("X"),
check_dygraph=False,
)
Expand All @@ -201,11 +196,120 @@ def test_check_grad_ingore_y(self):
place,
['X'],
'Out',
max_relative_error=0.9,
no_grad_set=set('Y'),
check_dygraph=False,
)


@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA or not support bfloat16",
)
class TestMulBF16Op1(OpTest):
def setUp(self):
self.op_type = "mul"
self.init_dtype_type()
self.inputs = {
'X': np.random.random((20, 5)).astype(self.np_dtype),
'Y': np.random.random((5, 21)).astype(self.np_dtype),
}
self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])}

self.inputs['X'] = convert_float_to_uint16(self.inputs['X'])
self.inputs['Y'] = convert_float_to_uint16(self.inputs['Y'])
self.outputs['Out'] = convert_float_to_uint16(self.outputs['Out'])
self.place = core.CUDAPlace(0)

def init_dtype_type(self):
self.dtype = np.uint16
self.np_dtype = np.float32

def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)

def test_check_grad_normal(self):
self.check_grad_with_place(
self.place, ['X', 'Y'], 'Out', check_dygraph=False
)

def test_check_grad_ingore_x(self):
self.check_grad_with_place(
self.place,
['Y'],
'Out',
no_grad_set=set("X"),
check_dygraph=False,
)

def test_check_grad_ingore_y(self):
self.check_grad_with_place(
self.place,
['X'],
'Out',
no_grad_set=set('Y'),
check_dygraph=False,
)


@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA or not support bfloat16",
)
class TestMulBF16Op2(TestMulBF16Op1):
def setUp(self):
self.op_type = "mul"
self.init_dtype_type()
self.inputs = {
'X': np.random.random((3, 4, 2, 9)).astype(self.np_dtype),
'Y': np.random.random((3, 6, 1, 2, 3)).astype(self.np_dtype),
}
self.attrs = {
'x_num_col_dims': 2,
'y_num_col_dims': 2,
}
result = np.dot(
self.inputs['X'].reshape(3 * 4, 2 * 9),
self.inputs['Y'].reshape(3 * 6, 1 * 2 * 3),
)
result = result.reshape(3, 4, 1, 2, 3)
self.outputs = {'Out': result}

self.inputs['X'] = convert_float_to_uint16(self.inputs['X'])
self.inputs['Y'] = convert_float_to_uint16(self.inputs['Y'])
self.outputs['Out'] = convert_float_to_uint16(self.outputs['Out'])
self.place = core.CUDAPlace(0)

def test_check_grad_normal(self):
self.check_grad_with_place(
self.place,
['X', 'Y'],
'Out',
numeric_grad_delta=0.02,
check_dygraph=False,
)

def test_check_grad_ingore_x(self):
self.check_grad_with_place(
self.place,
['Y'],
'Out',
numeric_grad_delta=0.02,
no_grad_set=set("X"),
check_dygraph=False,
)

def test_check_grad_ingore_y(self):
self.check_grad_with_place(
self.place,
['X'],
'Out',
numeric_grad_delta=0.02,
no_grad_set=set('Y'),
check_dygraph=False,
)


if __name__ == "__main__":
unittest.main()