diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py index 1034e5fb59c65a1765d1b9cb6ce642471c967f33..b979fa339de94745f22c059ca58ca6bfdf3bc909 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py @@ -21,6 +21,7 @@ from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci import paddle from paddle import fluid +from paddle.fluid import core from paddle.fluid.layer_helper import LayerHelper @@ -30,14 +31,18 @@ class TestElementwiseOp(OpTest): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), - 'Y': 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(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() self.if_enable_cinn() + def init_dtype(self): + self.dtype = np.float64 + def test_check_output(self): self.check_output() @@ -66,7 +71,55 @@ class TestElementwiseOp(OpTest): self.check_prim = True 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): @@ -75,19 +128,45 @@ class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.uniform(0.1, 1, []).astype("float64"), - 'Y': 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(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() self.if_enable_cinn() - def if_check_prim(self): - self.check_prim = True - def if_enable_cinn(self): - self.enable_cinn = False +class TestElementwiseSubFP16OP_ZeroDim1(TestElementwiseSubOp_ZeroDim1): + 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): @@ -96,19 +175,45 @@ class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), - 'Y': np.random.uniform(0.1, 1, []).astype("float64"), + 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype), + 'Y': np.random.uniform(0.1, 1, []).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() self.if_enable_cinn() - def if_check_prim(self): - self.check_prim = True - def if_enable_cinn(self): - self.enable_cinn = False +class TestElementwiseSubFP16OP_ZeroDim2(TestElementwiseSubOp_ZeroDim2): + 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): @@ -117,21 +222,52 @@ class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.uniform(0.1, 1, []).astype("float64"), - 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), + 'X': np.random.uniform(0.1, 1, []).astype(self.dtype), + 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() self.if_enable_cinn() - def if_check_prim(self): - self.check_prim = True - def if_enable_cinn(self): - self.enable_cinn = False +class TestElementwiseSubFP16OP_ZeroDim3(TestElementwiseSubOp_ZeroDim3): + 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): def setUp(self): self.op_type = "elementwise_sub" @@ -151,6 +287,12 @@ class TestBF16ElementwiseOp(OpTest): self.if_check_prim() 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): self.check_output() @@ -162,17 +304,6 @@ class TestBF16ElementwiseOp(OpTest): ['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( reason="[skip shape check] Use y_shape(1) to test broadcast." @@ -183,9 +314,10 @@ class TestElementwiseSubOp_scalar(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(10, 3, 4).astype(np.float64), - 'Y': np.random.rand(1).astype(np.float64), + 'X': np.random.rand(10, 3, 4).astype(self.dtype), + 'Y': np.random.rand(1).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() @@ -197,21 +329,23 @@ class TestElementwiseSubOp_Vector(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.random((100,)).astype("float64"), - 'Y': np.random.random((100,)).astype("float64"), + 'X': np.random.random((100,)).astype(self.dtype), + 'Y': np.random.random((100,)).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} self.if_check_prim() -class TestElementwiseSubOp_broadcast_O(TestElementwiseOp): +class TestElementwiseSubOp_broadcast_0(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" self.python_api = paddle.subtract + self.init_dtype() self.inputs = { - 'X': np.random.rand(100, 3, 2).astype(np.float64), - 'Y': np.random.rand(100).astype(np.float64), + 'X': np.random.rand(100, 3, 2).astype(self.dtype), + 'Y': np.random.rand(100).astype(self.dtype), } self.attrs = {'axis': 0} @@ -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): 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.float64), - 'Y': np.random.rand(100).astype(np.float64), + 'X': np.random.rand(100, 3, 2).astype(np.float32), + '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} @@ -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): def setUp(self): self.op_type = "elementwise_sub" self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(2, 3, 100).astype(np.float64), - 'Y': np.random.rand(100).astype(np.float64), + 'X': np.random.rand(2, 3, 100).astype(self.dtype), + 'Y': np.random.rand(100).astype(self.dtype), } self.outputs = { @@ -275,17 +493,70 @@ class TestElementwiseSubOp_broadcast_2(TestElementwiseOp): } 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): self.op_type = "elementwise_sub" self.python_api = paddle.subtract + self.init_dtype() self.inputs = { - 'X': np.random.rand(2, 10, 12, 3).astype(np.float64), - 'Y': np.random.rand(10, 12).astype(np.float64), + 'X': np.random.rand(2, 10, 12, 3).astype(self.dtype), + 'Y': np.random.rand(10, 12).astype(self.dtype), } self.attrs = {'axis': 1} @@ -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): def setUp(self): self.op_type = "elementwise_sub" self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(2, 5, 3, 12).astype(np.float64), - 'Y': np.random.rand(2, 5, 1, 12).astype(np.float64), + 'X': np.random.rand(2, 5, 3, 12).astype(self.dtype), + 'Y': np.random.rand(2, 5, 1, 12).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} 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): @@ -317,15 +619,43 @@ class TestElementwiseSubOp_commonuse_1(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(2, 3, 100).astype(np.float64), - 'Y': np.random.rand(1, 1, 100).astype(np.float64), + 'X': np.random.rand(2, 3, 100).astype(self.dtype), + 'Y': np.random.rand(1, 1, 100).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} 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): @@ -334,15 +664,43 @@ class TestElementwiseSubOp_commonuse_2(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(10, 3, 1, 4).astype(np.float64), - 'Y': np.random.rand(10, 1, 12, 1).astype(np.float64), + 'X': np.random.rand(10, 3, 1, 4).astype(self.dtype), + 'Y': np.random.rand(10, 1, 12, 1).astype(self.dtype), } self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']} 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): @@ -351,9 +709,10 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): self.python_api = paddle.subtract self.public_python_api = paddle.subtract self.prim_op_type = "prim" + self.init_dtype() self.inputs = { - 'X': np.random.rand(10, 12).astype(np.float64), - 'Y': np.random.rand(2, 3, 10, 12).astype(np.float64), + 'X': np.random.rand(10, 12).astype(self.dtype), + 'Y': np.random.rand(2, 3, 10, 12).astype(self.dtype), } self.attrs = {'axis': 2} @@ -362,8 +721,38 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): } 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): @@ -473,7 +862,7 @@ class TestSubtractApi(unittest.TestCase): def test_name(self): with fluid.program_guard(fluid.Program()): 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') self.assertEqual(('subtract_res' in y_1.name), True) @@ -483,12 +872,12 @@ class TestSubtractApi(unittest.TestCase): def gen_data(): return { - "x": np.array([2, 3, 4]).astype('float32'), - "y": np.array([1, 5, 2]).astype('float32'), + "x": np.array([2, 3, 4]).astype(np.float32), + "y": np.array([1, 5, 2]).astype(np.float32), } - x = paddle.static.data(name="x", shape=[3], dtype='float32') - y = paddle.static.data(name="y", shape=[3], dtype='float32') + x = paddle.static.data(name="x", shape=[3], dtype=np.float32) + y = paddle.static.data(name="y", shape=[3], dtype=np.float32) z = self._executed_api(x, y) place = fluid.CPUPlace() exe = fluid.Executor(place) @@ -640,7 +1029,7 @@ class TestTensorSubAPIWarnings(unittest.TestCase): paddle.enable_static() helper = LayerHelper("elementwise_sub") 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) os.environ['FLAGS_print_extra_attrs'] = "1"