fix fill_constant bug, *test=kunlun (#39681)

* fix fill_constant bug, *test=kunlun

* fix fill_constant bug,*test=kunlun

paddle/fluid/platform/device/xpu/xpu2_op_list.h

@@ -134,7 +134,7 @@ XPUOpMap& get_kl2_ops() {
        XPUKernelSet({pOpKernelType(vartype::INT64, XPUPlace()),
                      pOpKernelType(vartype::INT32, XPUPlace()),
                      pOpKernelType(vartype::INT16, XPUPlace()),
-                     pOpKernelType(vartype::INT8, XPUPlace()),
+                     pOpKernelType(vartype::UINT8, XPUPlace()),
                      pOpKernelType(vartype::BOOL, XPUPlace()),
                      pOpKernelType(vartype::FP64, XPUPlace()),
                      pOpKernelType(vartype::FP32, XPUPlace()),

python/paddle/fluid/tests/unittests/xpu/test_fill_constant_op_xpu.py

@@ -17,224 +17,234 @@ from __future__ import print_function
 import sys
 sys.path.append("..")
 import unittest
-from op_test import OpTest
-
 import paddle
+from paddle.fluid import core
 import numpy as np
-
-
-# Situation 1: Attr(shape) is a list(without tensor)
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp1(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified value'''
-        self.op_type = "fill_constant"
-
-        self.inputs = {}
-        self.attrs = {'shape': [123, 92], 'dtype': 5, 'value': 3.8}
-        self.outputs = {'Out': np.full((123, 92), 3.8)}
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp2(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with default value'''
-        self.op_type = "fill_constant"
-
-        self.inputs = {}
-        self.attrs = {'shape': [123, 92], 'dtype': 5}
-        self.outputs = {'Out': np.full((123, 92), 0.0)}
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp3(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified int64 value'''
-        self.op_type = "fill_constant"
-
-        self.inputs = {}
-        self.attrs = {'shape': [123, 92], 'dtype': 3, 'value': 10000000000}
-        self.outputs = {'Out': np.full((123, 92), 10000000000)}
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp4(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified int value'''
-        self.op_type = "fill_constant"
-
-        self.inputs = {}
-        self.attrs = {'shape': [123, 92], 'dtype': 2, 'value': 3}
-        self.outputs = {'Out': np.full((123, 92), 3)}
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-# Situation 2: Attr(shape) is a list(with tensor)
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp1_ShapeTensorList(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified value'''
-        self.op_type = "fill_constant"
-        self.init_data()
-        shape_tensor_list = []
-        for index, ele in enumerate(self.shape):
-            shape_tensor_list.append(("x" + str(index), np.ones(
-                (1)).astype('int32') * ele))
-
-        self.inputs = {"ShapeTensorList": shape_tensor_list}
-        self.attrs = {
-            'shape': self.infer_shape,
-            'dtype': 5,
-            'value': self.value
-        }
-        self.outputs = {'Out': np.full(self.shape, self.value)}
-
-    def init_data(self):
-        self.shape = [123, 92]
-        self.infer_shape = [-1, 92]
-        self.value = 3.8
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp2_ShapeTensorList(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with default value'''
-        self.op_type = "fill_constant"
-        self.init_data()
-        shape_tensor_list = []
-        for index, ele in enumerate(self.shape):
-            shape_tensor_list.append(("x" + str(index), np.ones(
-                (1)).astype('int32') * ele))
-
-        self.inputs = {"ShapeTensorList": shape_tensor_list}
-        self.attrs = {'shape': self.infer_shape, 'dtype': 5}
-        self.outputs = {'Out': np.full(self.shape, 0.0)}
-
-    def init_data(self):
-        self.shape = [123, 92]
-        self.infer_shape = [-1, -1]
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp3_ShapeTensorList(TestFillConstantOp1_ShapeTensorList):
-    def init_data(self):
-        self.shape = [123, 92]
-        self.infer_shape = [123, -1]
-        self.value = 10000000000
-
-
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp4_ShapeTensorList(TestFillConstantOp1_ShapeTensorList):
-    def init_data(self):
-        self.shape = [123, 92]
-        self.infer_shape = [123, -1]
-        self.value = 3
-
-
-# Situation 3: shape is a tensor
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp1_ShapeTensor(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified value'''
-        self.op_type = "fill_constant"
-        self.init_data()
-
-        self.inputs = {"ShapeTensor": np.array(self.shape).astype("int32")}
-        self.attrs = {'value': self.value, 'dtype': 5}
-        self.outputs = {'Out': np.full(self.shape, self.value)}
-
-    def init_data(self):
-        self.shape = [123, 92]
-        self.value = 3.8
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-# Situation 4: value is a tensor
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp1_ValueTensor(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified value'''
-        self.op_type = "fill_constant"
-        self.init_data()
-
-        self.inputs = {
-            "ShapeTensor": np.array(self.shape).astype("int32"),
-            'ValueTensor': np.array([self.value]).astype("float32")
-        }
-        self.attrs = {'value': self.value + 1.0, 'dtype': 5}
-        self.outputs = {'Out': np.full(self.shape, self.value)}
-
-    def init_data(self):
-        self.shape = [123, 92]
-        self.value = 3.8
-        self.dtype = np.float32
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
-
-# Situation 5: value is a tensor
-@unittest.skipIf(not paddle.is_compiled_with_xpu(),
-                 "core is not compiled with XPU")
-class TestFillConstantOp2_ValueTensor(OpTest):
-    def setUp(self):
-        '''Test fill_constant op with specified value'''
-        self.op_type = "fill_constant"
-        self.init_data()
-
-        self.inputs = {
-            "ShapeTensor": np.array(self.shape).astype("int32"),
-            'ValueTensor': np.array([self.value]).astype("int32")
-        }
-        self.attrs = {'value': self.value, 'dtype': 2}
-        self.outputs = {'Out': np.full(self.shape, self.value)}
-
-    def init_data(self):
-        self.shape = [123, 92]
-        self.value = 3
-        self.dtype = np.int32
-
-    def test_check_output(self):
-        place = paddle.XPUPlace(0)
-        self.check_output_with_place(place)
-
+from op_test import OpTest, convert_float_to_uint16
+from op_test_xpu import XPUOpTest
+from xpu.get_test_cover_info import create_test_class, get_xpu_op_support_types, XPUOpTestWrapper
+
+
+class XPUTestFillConstantOp(XPUOpTestWrapper):
+    def __init__(self):
+        self.op_name = 'fill_constant'
+        self.use_dynamic_create_class = False
+
+    # Situation 1: Attr(shape) is a list(without tensor)
+    class TestFillConstantOp(XPUOpTest):
+        def setUp(self):
+            '''Test fill_constant op with specified value
+            '''
+            self.init_dtype()
+            self.set_xpu()
+            self.op_type = "fill_constant"
+            self.place = paddle.XPUPlace(0)
+            self.set_shape()
+            self.convert_dtype2index()
+            self.set_value()
+            self.set_data()
+
+        def init_dtype(self):
+            self.dtype = self.in_type
+
+        def set_shape(self):
+            self.shape = [90, 10]
+
+        def set_xpu(self):
+            self.__class__.use_xpu = True
+            self.__class__.no_need_check_grad = True
+            self.__class__.op_type = self.in_type
+
+        def convert_dtype2index(self):
+            '''
+            if new type added, need to add corresponding index
+            '''
+            if self.dtype == np.bool_:
+                self.index = 0
+            if self.dtype == np.int16:
+                self.index = 1
+            if self.dtype == np.int32:
+                self.index = 2
+            if self.dtype == np.int64:
+                self.index = 3
+            if self.dtype == np.float16:
+                self.index = 4
+            if self.dtype == np.float32:
+                self.index = 5
+            if self.dtype == np.float64:
+                self.index = 6
+            if self.dtype == np.uint8:
+                self.index = 20
+            if self.dtype == np.int8:
+                self.index = 21
+            if self.dtype == np.uint16:  # same as paddle.bfloat16
+                self.index = 22
+            if self.dtype == np.complex64:
+                self.index = 23
+            if self.dtype == np.complex128:
+                self.index = 24
+
+        def set_value(self):
+            if self.index == 3:
+                self.value = 10000000000
+            elif self.index == 0:
+                self.value = np.random.randint(0, 2)
+            elif self.index in [20, 21]:
+                self.value = 125
+            elif self.index in [1, 2]:
+                self.value = 7
+            elif self.index in [4, 5, 6]:
+                self.value = 1e-5
+            elif self.index == 22:
+                self.value = 1.0
+            else:
+                self.value = 3.7
+
+        def set_data(self):
+            self.inputs = {}
+            self.attrs = {
+                'shape': self.shape,
+                'dtype': self.index,
+                'value': self.value
+            }
+            self.outputs = {'Out': np.full(self.shape, self.value)}
+
+        def test_check_output(self):
+            self.check_output_with_place(self.place)
+
+    class TestFillConstantOp2(TestFillConstantOp):
+        '''Test fill_constant op with default value
+        '''
+
+        def set_shape(self):
+            self.shape = [10, 10]
+
+    class TestFillConstantOp3(TestFillConstantOp):
+        '''Test fill_constant op with specified int64 value
+        '''
+
+        def set_shape(self):
+            self.shape = [123, 2, 1]
+
+    class TestFillConstantOp4(TestFillConstantOp):
+        '''Test fill_constant op with specified int value
+        '''
+
+        def set_shape(self):
+            self.shape = [123, 3, 2, 1]
+
+    class TestFillConstantOp5(TestFillConstantOp):
+        '''Test fill_constant op with specified float value
+        '''
+
+        def set_shape(self):
+            self.shape = [123]
+
+    # Situation 2: Attr(shape) is a list(with tensor)
+    class TestFillConstantOp1_ShapeTensorList(TestFillConstantOp):
+        '''Test fill_constant op with specified value
+        '''
+
+        def set_data(self):
+            shape_tensor_list = []
+            for index, ele in enumerate(self.shape):
+                shape_tensor_list.append(("x" + str(index), np.ones(
+                    (1)).astype('int32') * ele))
+
+            self.inputs = {"ShapeTensorList": shape_tensor_list}
+            self.attrs = {
+                'shape': self.infer_shape,
+                'dtype': self.index,
+                'value': self.value
+            }
+            self.outputs = {'Out': np.full(self.shape, self.value)}
+            if self.index == 22:
+                self.outputs = {
+                    'Out':
+                    np.full(self.shape,
+                            convert_float_to_uint16(
+                                np.array([self.value]).astype("float32")))
+                }
+
+        def set_shape(self):
+            self.shape = [123, 92]
+            self.infer_shape = [123, 1]
+
+    class TestFillConstantOp2_ShapeTensorList(TestFillConstantOp):
+        '''Test fill_constant op with default value
+        '''
+
+        def set_data(self):
+            shape_tensor_list = []
+            for index, ele in enumerate(self.shape):
+                shape_tensor_list.append(("x" + str(index), np.ones(
+                    (1)).astype('int32') * ele))
+
+            self.inputs = {"ShapeTensorList": shape_tensor_list}
+            self.attrs = {'shape': self.infer_shape, 'dtype': self.index}
+            self.outputs = {'Out': np.full(self.shape, 0.0)}
+
+        def set_shape(self):
+            self.shape = [123, 2, 1]
+            self.infer_shape = [1, 1, 1]
+
+    class TestFillConstantOp3_ShapeTensorList(
+            TestFillConstantOp1_ShapeTensorList):
+        def set_shape(self):
+            self.shape = [123, 3, 2, 1]
+            self.infer_shape = [123, 111, 11, 1]
+
+    class TestFillConstantOp4_ShapeTensorList(
+            TestFillConstantOp1_ShapeTensorList):
+        def set_shape(self):
+            self.shape = [123]
+            self.infer_shape = [1]
+
+    # Situation 3: shape is a tensor
+    class TestFillConstantOp1_ShapeTensor(TestFillConstantOp):
+        '''Test fill_constant op with specified value
+        '''
+
+        def set_data(self):
+            self.inputs = {"ShapeTensor": np.array(self.shape).astype("int32")}
+            self.attrs = {'value': self.value, 'dtype': self.index}
+            self.outputs = {'Out': np.full(self.shape, self.value)}
+            if self.index == 22:
+                self.outputs = {
+                    'Out':
+                    np.full(self.shape,
+                            convert_float_to_uint16(
+                                np.array([self.value]).astype("float32")))
+                }
+
+        def set_shape(self):
+            self.shape = [123, 92]
+
+    # Situation 4: value is a tensor
+    class TestFillConstantOp1_ValueTensor(TestFillConstantOp):
+        '''Test fill_constant op with specified value
+        '''
+
+        def set_data(self):
+            self.inputs = {
+                "ShapeTensor": np.array(self.shape).astype("int32"),
+                'ValueTensor': np.array([self.value]).astype(self.dtype)
+            }
+            if self.index == 22:
+                self.inputs = {
+                    'ValueTensor': convert_float_to_uint16(
+                        np.array([self.value]).astype("float32"))
+                }
+            self.attrs = {'value': self.value, 'dtype': self.index}
+            self.outputs = {'Out': np.full(self.shape, self.value)}
+
+        def set_shape(self):
+            self.shape = [123, 92]
+
+
+support_types = get_xpu_op_support_types('fill_constant')
+for stype in support_types:
+    create_test_class(globals(), XPUTestFillConstantOp, stype)
 
 if __name__ == "__main__":
     paddle.enable_static()