reshape onednn test reimplemented (#48850)

* - UT reshape onednn

- Fix

test

test2

- test4

- test5

- test6

test7

- test8

- Ut reinvented

- cosmetic

* - fix

* - fix

* - fix

* - fix

* - Fix

* - fix

* - fix

* - fix

* - Fix

* lint

python/paddle/fluid/tests/unittests/mkldnn/test_reshape_mkldnn_op.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -19,54 +19,30 @@
 import paddle
 import paddle.fluid.core as core
 from paddle.fluid.tests.unittests.op_test import (
-    OpTest,
     OpTestTool,
     convert_float_to_uint16,
 )
+from paddle.fluid.tests.unittests.test_reshape_op import TestReshapeOp
 
+paddle.enable_static()
 
-@OpTestTool.skip_if(
-    core.is_compiled_with_cuda(),
-    "CUDA has to be skipped because it forces dygraph",
-)
-class TestReshape2OneDNNOp(OpTest):
+
+class TestReshape2OneDNNOp(TestReshapeOp):
     def setUp(self):
-        self.init_data()
-        self.set_op_type()
-        self.x = np.random.random(self.ori_shape).astype("float32")
-        self.set_inputs()
+        super().setUp()
+        self.x = self.inputs["X"]
+        self.attrs['use_mkldnn'] = True
         self.set_additional_inputs()
-        self.set_attrs()
         self.set_outputs()
 
-    def set_op_type(self):
-        self.op_type = "reshape2"
-
-    def set_inputs(self):
-        self.inputs = {"X": self.x}
+    def init_dtype(self):
+        self.dtype = np.float32
 
     def set_additional_inputs(self):
         pass
 
-    def set_attrs(self):
-        self.attrs = {"shape": self.new_shape, 'use_mkldnn': True}
-
     def set_outputs(self):
-        self.outputs = {
-            "Out": self.inputs["X"].reshape(self.infered_shape),
-            'XShape': np.random.random(self.ori_shape).astype("float32"),
-        }
-
-    def init_data(self):
-        self.ori_shape = (2, 60)
-        self.new_shape = (12, 10)
-        self.infered_shape = (12, 10)
-
-    def test_check_output(self):
-        self.check_output(no_check_set=['XShape'])
-
-    def test_check_grad(self):
-        self.check_grad(["X"], "Out")
+        pass
 
 
 class TestReshape2OneDNNOpDimInfer1(TestReshape2OneDNNOp):
@@ -80,14 +56,14 @@ class TestReshape2OneDNNOpDimInfer2(TestReshape2OneDNNOp):
     def init_data(self):
         self.ori_shape = (6, 20)
         self.new_shape = (0, -1, 20)
-        self.actual_shape = (2, 3, 20)
+        self.infered_shape = (2, 3, 20)
 
     def set_additional_inputs(self):
-        self.inputs["Shape"] = np.array(self.actual_shape, dtype="int32")
+        self.inputs["Shape"] = np.array(self.infered_shape, dtype="int32")
 
     def set_outputs(self):
         self.outputs = {
-            "Out": self.inputs["X"].reshape(self.actual_shape),
+            "Out": self.inputs["X"].reshape(self.infered_shape),
             'XShape': np.random.random(self.ori_shape).astype("float32"),
         }
 
@@ -96,9 +72,6 @@ class TestReshape2OneDNNOp_attr_OnlyShape(TestReshape2OneDNNOp):
     def set_additional_inputs(self):
         self.inputs["Shape"] = np.array(self.new_shape, dtype="int32")
 
-    def set_attrs(self):
-        self.attrs = {'use_mkldnn': True}
-
     def set_outputs(self):
         self.outputs = {
             "Out": self.inputs["X"].reshape(self.infered_shape),
@@ -153,7 +126,8 @@ def set_additional_inputs(self):
 
 
 class TestReshapeOneDNNOp(TestReshape2OneDNNOp):
-    def set_op_type(self):
+    def setUp(self):
+        super().setUp()
         self.op_type = "reshape"
 
     def set_outputs(self):
@@ -171,7 +145,8 @@ def init_data(self):
 
 
 class TestReshapeOneDNNOp_attr_OnlyShape(TestReshape2OneDNNOp_attr_OnlyShape):
-    def set_op_type(self):
+    def setUp(self):
+        super().setUp()
         self.op_type = "reshape"
 
     def set_outputs(self):
@@ -195,9 +170,11 @@ def init_data(self):
 def create_reshape_bf16_test_classes(parent):
     @OpTestTool.skip_if_not_cpu_bf16()
     class TestReshape2BF16OneDNNOp(parent):
-        def set_inputs(self):
+        def setUp(self):
+            super().setUp()
             self.dtype = np.uint16
             self.inputs = {"X": convert_float_to_uint16(self.x)}
+            self.attrs['use_mkldnn'] = True
 
         def calculate_grads(self):
             self.dout = self.outputs['Out']
@@ -223,9 +200,9 @@ def test_check_grad(self):
     globals()[cls_name] = TestReshape2BF16OneDNNOp
 
     class TestReshapeBF16OneDNNOp(TestReshape2BF16OneDNNOp):
-        def set_op_type(self):
+        def setUp(self):
+            super().setUp()
             self.dtype = np.uint16
-            self.op_type = "reshape"
 
         def set_outputs(self):
             self.outputs = {"Out": self.x.reshape(self.new_shape)}
@@ -252,5 +229,4 @@ def test_check_grad(self):
 create_reshape_bf16_test_classes(TestReshape2OneDNNOpDimInfer1)
 
 if __name__ == "__main__":
-    paddle.enable_static()
     unittest.main()

python/paddle/fluid/tests/unittests/test_reshape_op.py

@@ -1,4 +1,4 @@
-#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.