[PIR]Migrate accuracy/topk into pir (#58235)

0x45f · web-flow · commit d2e150fcb035 · 2023-10-25T16:38:40.000+08:00
diff --git a/python/paddle/metric/metrics.py b/python/paddle/metric/metrics.py
@@ -17,10 +17,10 @@
 import numpy as np
 
 import paddle
-from paddle import _legacy_C_ops
+from paddle import _C_ops, _legacy_C_ops
 
 from ..base.data_feeder import check_variable_and_dtype
-from ..base.framework import _create_tensor
+from ..base.framework import _create_tensor, in_pir_mode
 from ..base.layer_helper import LayerHelper
 from ..framework import in_dynamic_mode
 
@@ -807,6 +807,10 @@ def accuracy(input, label, k=1, correct=None, total=None, name=None):
         )
 
         return _acc
+    elif in_pir_mode():
+        topk_out, topk_indices = paddle.topk(input, k=k)
+        _acc, _, _ = _C_ops.accuracy(topk_out, topk_indices, label)
+        return _acc
 
     helper = LayerHelper("accuracy", **locals())
     check_variable_and_dtype(
diff --git a/python/paddle/static/nn/metric.py b/python/paddle/static/nn/metric.py
@@ -17,9 +17,14 @@
 import numpy as np
 
 import paddle
-from paddle import _legacy_C_ops
+from paddle import _C_ops, _legacy_C_ops
 from paddle.base.data_feeder import check_variable_and_dtype
-from paddle.base.framework import Variable, _create_tensor, in_dygraph_mode
+from paddle.base.framework import (
+    Variable,
+    _create_tensor,
+    in_dygraph_mode,
+    in_pir_mode,
+)
 from paddle.base.layer_helper import LayerHelper
 from paddle.nn.initializer import ConstantInitializer
 
@@ -88,6 +93,10 @@ def accuracy(input, label, k=1, correct=None, total=None):
             topk_out, topk_indices, label, correct, total
         )
         return _acc
+    elif in_pir_mode():
+        topk_out, topk_indices = paddle.topk(input, k=k, sorted=False)
+        _acc, _, _ = _C_ops.accuracy(topk_out, topk_indices, label)
+        return _acc
 
     helper = LayerHelper("accuracy", **locals())
     check_variable_and_dtype(
diff --git a/python/paddle/tensor/search.py b/python/paddle/tensor/search.py
@@ -1005,7 +1005,7 @@ def topk(x, k, axis=None, largest=True, sorted=True, name=None):
 
     """
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         if axis is None:
             axis = -1
         out, indices = _C_ops.topk(x, k, axis, largest, sorted)
diff --git a/test/legacy_test/test_accuracy_op.py b/test/legacy_test/test_accuracy_op.py
@@ -20,6 +20,7 @@
 import paddle
 from paddle import base
 from paddle.base import Program, core, program_guard
+from paddle.pir_utils import test_with_pir_api
 
 
 def accuracy_wrapper(infer, indices, label):
@@ -53,15 +54,15 @@ def init_dtype(self):
         pass
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
 
 class TestAccuracyOpFp16(TestAccuracyOp):
     def init_dtype(self):
         self.dtype = np.float16
 
     def test_check_output(self):
-        self.check_output(atol=1e-3)
+        self.check_output(atol=1e-3, check_pir=True)
 
 
 @unittest.skipIf(
@@ -103,7 +104,7 @@ def init_dtype(self):
     def test_check_output(self):
         if core.is_compiled_with_cuda():
             place = core.CUDAPlace(0)
-            self.check_output_with_place(place, atol=1e-2)
+            self.check_output_with_place(place, atol=1e-2, check_pir=True)
 
 
 class TestAccuracyOpError(unittest.TestCase):
@@ -142,35 +143,38 @@ def test_value_errors(self):
 
 
 class TestAccuracyAPI1(unittest.TestCase):
-    def setUp(self):
+    def run_api(self, accuracy_api):
         with paddle_static_guard():
-            self.predictions = paddle.static.data(
-                shape=[2, 5], name="predictions", dtype="float32"
-            )
-            self.label = paddle.static.data(
-                shape=[2, 1], name="labels", dtype="int64"
-            )
-            self.result = paddle.static.accuracy(
-                input=self.predictions, label=self.label, k=1
-            )
-            self.input_predictions = np.array(
-                [[0.2, 0.1, 0.4, 0.1, 0.1], [0.2, 0.3, 0.1, 0.15, 0.25]],
-                dtype="float32",
-            )
-            self.input_labels = np.array([[2], [0]], dtype="int64")
-            self.expect_value = np.array([0.5], dtype='float32')
+            with paddle.static.program_guard(paddle.static.Program()):
+                self.predictions = paddle.static.data(
+                    shape=[2, 5], name="predictions", dtype="float32"
+                )
+                self.label = paddle.static.data(
+                    shape=[2, 1], name="labels", dtype="int64"
+                )
+                self.result = accuracy_api(
+                    input=self.predictions, label=self.label, k=1
+                )
+                self.input_predictions = np.array(
+                    [[0.2, 0.1, 0.4, 0.1, 0.1], [0.2, 0.3, 0.1, 0.15, 0.25]],
+                    dtype="float32",
+                )
+                self.input_labels = np.array([[2], [0]], dtype="int64")
+                self.expect_value = np.array([0.5], dtype='float32')
+                exe = paddle.static.Executor()
+                (result,) = exe.run(
+                    feed={
+                        "predictions": self.input_predictions,
+                        'labels': self.input_labels,
+                    },
+                    fetch_list=[self.result],
+                )
+                self.assertEqual((result == self.expect_value).all(), True)
 
+    @test_with_pir_api
     def test_api(self):
-        with paddle_static_guard():
-            exe = paddle.static.Executor()
-            (result,) = exe.run(
-                feed={
-                    "predictions": self.input_predictions,
-                    'labels': self.input_labels,
-                },
-                fetch_list=[self.result.name],
-            )
-            self.assertEqual((result == self.expect_value).all(), True)
+        self.run_api(accuracy_api=paddle.static.accuracy)
+        self.run_api(accuracy_api=paddle.metric.accuracy)
 
 
 class TestAccuracyAPI2(unittest.TestCase):
diff --git a/test/legacy_test/test_top_k_v2_op.py b/test/legacy_test/test_top_k_v2_op.py
@@ -19,6 +19,7 @@
 
 import paddle
 from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 
 def numpy_topk(x, k=1, axis=-1, largest=True):
@@ -63,10 +64,10 @@ def if_enable_cinn(self):
         pass
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', check_prim=True)
+        self.check_grad(['X'], 'Out', check_prim=True, check_pir=True)
 
 
 class TestTopkOp_ZeroDim(TestTopkOp):
@@ -270,11 +271,13 @@ def if_enable_cinn(self):
 
     def test_check_output(self):
         place = core.CUDAPlace(0)
-        self.check_output_with_place(place)
+        self.check_output_with_place(place, check_pir=True)
 
     def test_check_grad(self):
         place = core.CUDAPlace(0)
-        self.check_grad_with_place(place, ['X'], 'Out', check_prim=True)
+        self.check_grad_with_place(
+            place, ['X'], 'Out', check_prim=True, check_pir=True
+        )
 
 
 class TestTopKAPI(unittest.TestCase):
@@ -377,8 +380,8 @@ def run_static(self, place):
             result1 = paddle.topk(input_tensor, k=2)
             result2 = paddle.topk(input_tensor, k=2, axis=-1)
             result3 = paddle.topk(input_tensor, k=k_tensor, axis=1)
-            self.assertEqual(result3[0].shape, (6, -1, 8))
-            self.assertEqual(result3[1].shape, (6, -1, 8))
+            self.assertEqual(tuple(result3[0].shape), (6, -1, 8))
+            self.assertEqual(tuple(result3[1].shape), (6, -1, 8))
             result4 = paddle.topk(input_tensor, k=2, axis=1, largest=False)
             result5 = paddle.topk(input_tensor, k=2, axis=-1, largest=False)
             result6 = paddle.topk(large_input_tensor, k=1, axis=-1)
@@ -461,12 +464,19 @@ def run_static(self, place):
                 sort_paddle[0], numpy_result[0], rtol=1e-05
             )
 
-    def test_cases(self):
+    def test_dygraph_cases(self):
         places = [core.CPUPlace()]
         if core.is_compiled_with_cuda():
             places.append(core.CUDAPlace(0))
         for place in places:
             self.run_dygraph(place)
+
+    @test_with_pir_api
+    def test_static_cases(self):
+        places = [core.CPUPlace()]
+        if core.is_compiled_with_cuda():
+            places.append(core.CUDAPlace(0))
+        for place in places:
             self.run_static(place)
 
     def test_errors(self):
