【PIR API adaptor No.167、168、243、244】 Migrate pooling ops into pir

python/paddle/nn/functional/pooling.py

@@ -253,7 +253,7 @@ def avg_pool1d(
     # use 2d to implenment 1d should expand padding in advance.
     padding = _expand_low_nd_padding(padding)
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         output = _C_ops.pool2d(
             x,
             kernel_size,
@@ -505,7 +505,7 @@ def avg_pool3d(
     _check_value_limitation(kernel_size, "kernel_size", min_limit=1e-3)
     _check_value_limitation(stride, "stride", min_limit=1e-3)
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         pool_out = _C_ops.pool3d(
             x,
             kernel_size,
@@ -629,7 +629,7 @@ def max_pool1d(
     # use 2d to implenment 1d should expand padding in advance.
     padding = _expand_low_nd_padding(padding)
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         if return_mask:
             pool_out = _C_ops.max_pool2d_with_index(
                 x, kernel_size, stride, padding, False, False
@@ -829,7 +829,7 @@ def max_unpool1d(
         x, kernel_size, stride, padding, output_size
     )
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         output = _C_ops.unpool(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
@@ -979,7 +979,7 @@ def max_unpool2d(
         x, kernel_size, stride, padding, output_size
     )
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         output = _C_ops.unpool(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
@@ -1126,7 +1126,7 @@ def max_unpool3d(
         x, kernel_size, stride, padding, output_size
     )
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         output = _C_ops.unpool3d(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
@@ -1423,7 +1423,7 @@ def max_pool3d(
             "When setting return_mask to true, data_format must be set to NCDHW in API:max_pool3d"
         )
 
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         if return_mask:
             output = _C_ops.max_pool3d_with_index(
                 x, kernel_size, stride, padding, False, False
@@ -1651,7 +1651,7 @@ def adaptive_avg_pool2d(x, output_size, data_format='NCHW', name=None):
         output_size = _convert_to_tensor_list(output_size)
 
     if in_dynamic_or_pir_mode():
-        if in_dygraph_mode():
+        if in_dynamic_mode():
             x = x._use_gpudnn(False)
         return _C_ops.pool2d(
             x,

test/legacy_test/test_pool1d_api.py

@@ -20,6 +20,7 @@
 import paddle.nn.functional as F
 from paddle import base
 from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 
 def adaptive_start_index(index, input_size, output_size):
@@ -121,8 +122,9 @@ def setUp(self):
         if core.is_compiled_with_cuda():
             self.places.append(base.CUDAPlace(0))
 
+    @test_with_pir_api
     def check_avg_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(paddle.static.Program()):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32], dtype="float32"
             )
@@ -133,14 +135,14 @@ def check_avg_static_results(self, place):
                 input_np, ksize=[2], strides=[2], paddings=[0], ceil_mode=False
             )
 
-            exe = base.Executor(place)
+            exe = paddle.static.Executor(place)
             fetches = exe.run(
-                base.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )
             np.testing.assert_allclose(fetches[0], result_np, rtol=1e-05)
 
+    @test_with_pir_api
     def check_avg_static_results_fp16(self, place):
         with paddle.static.program_guard(paddle.static.Program()):
             input = paddle.static.data(
@@ -161,7 +163,6 @@ def check_avg_static_results_fp16(self, place):
                 place = paddle.CUDAPlace(0)
                 exe = paddle.static.Executor(place)
                 fetches = exe.run(
-                    paddle.static.default_main_program(),
                     feed={"input": input_np},
                     fetch_list=[result],
                 )
@@ -206,8 +207,11 @@ def check_avg_dygraph_padding_results(self, place):
             result = avg_pool1d_dg(input)
             np.testing.assert_allclose(result.numpy(), result_np, rtol=1e-05)
 
+    @test_with_pir_api
     def check_max_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32], dtype="float32"
             )
@@ -218,9 +222,8 @@ def check_max_static_results(self, place):
                 input_np, ksize=[2], strides=[2], paddings=[0]
             )
 
-            exe = base.Executor(place)
+            exe = paddle.static.Executor(place)
             fetches = exe.run(
-                base.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )

test/legacy_test/test_pool2d_api.py

@@ -36,7 +36,9 @@ def setUp(self):
             self.places.append(base.CUDAPlace(0))
 
     def check_avg_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32, 32], dtype="float32"
             )
@@ -53,7 +55,6 @@ def check_avg_static_results(self, place):
 
             exe = base.Executor(place)
             fetches = exe.run(
-                paddle.static.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )
@@ -128,7 +129,9 @@ def check_avg_dygraph_ceilmode_results(self, place):
             np.testing.assert_allclose(result.numpy(), result_np, rtol=1e-05)
 
     def check_max_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32, 32], dtype="float32"
             )
@@ -145,7 +148,6 @@ def check_max_static_results(self, place):
 
             exe = base.Executor(place)
             fetches = exe.run(
-                paddle.static.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )

test/legacy_test/test_pool2d_op.py

@@ -19,6 +19,7 @@
 
 import paddle
 from paddle.base import core
+from paddle.framework import in_dynamic_mode
 
 
 def adaptive_start_index(index, input_size, output_size):
@@ -298,11 +299,12 @@ def pool2d_wrapper_not_use_cudnn(
     adaptive=False,
     padding_algorithm="EXPLICIT",
 ):
-    tmp = X._use_gpudnn(False)
+    if in_dynamic_mode():
+        X = X._use_gpudnn(False)
     if data_format == "AnyLayout":
         data_format = "NCDHW"
     return paddle._C_ops.pool2d(
-        tmp,
+        X,
         ksize,
         strides,
         paddings,
@@ -425,9 +427,13 @@ def test_check_output(self):
                 atol=1e-5,
                 check_dygraph=(not self.use_mkldnn),
                 check_cinn=True,
+                check_pir=True,
             )
         else:
-            self.check_output(check_dygraph=(not self.use_mkldnn))
+            self.check_output(
+                check_dygraph=(not self.use_mkldnn),
+                check_pir=True,
+            )
 
     def test_check_grad(self):
         if self.dtype == np.float16:
@@ -441,13 +447,15 @@ def test_check_grad(self):
                 'Out',
                 check_dygraph=(not self.use_mkldnn),
                 check_cinn=True,
+                check_pir=True,
             )
         elif self.pool_type != "max":
             self.check_grad(
                 {'X'},
                 'Out',
                 max_relative_error=0.07,
                 check_dygraph=(not self.use_mkldnn),
+                check_pir=True,
             )
 
     def init_data_format(self):
@@ -1011,11 +1019,20 @@ def test_check_grad(self):
         if self.has_cudnn() and self.pool_type == "max":
             place = core.CUDAPlace(0)
             self.check_grad_with_place(
-                place, {'X'}, 'Out', max_relative_error=1.00, check_cinn=True
+                place,
+                {'X'},
+                'Out',
+                max_relative_error=1.00,
+                check_cinn=True,
+                check_pir=True,
             )
         elif self.pool_type == "max":
             self.check_grad(
-                {'X'}, 'Out', max_relative_error=1.00, check_cinn=True
+                {'X'},
+                'Out',
+                max_relative_error=1.00,
+                check_cinn=True,
+                check_pir=True,
             )
 
 

test/legacy_test/test_pool3d_api.py

@@ -25,6 +25,7 @@
 from paddle import base
 from paddle.base import core
 from paddle.nn.functional import avg_pool3d, max_pool3d
+from paddle.pir_utils import test_with_pir_api
 
 
 class TestPool3D_API(unittest.TestCase):
@@ -34,8 +35,11 @@ def setUp(self):
         if core.is_compiled_with_cuda():
             self.places.append(base.CUDAPlace(0))
 
+    @test_with_pir_api
     def check_avg_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32, 32, 32], dtype="float32"
             )
@@ -50,9 +54,8 @@ def check_avg_static_results(self, place):
                 pool_type='avg',
             )
 
-            exe = base.Executor(place)
+            exe = paddle.static.Executor(place)
             fetches = exe.run(
-                base.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )
@@ -139,8 +142,11 @@ def check_avg_dygraph_ceilmode_results(self, place):
             result = avg_pool3d_dg(input)
             np.testing.assert_allclose(result.numpy(), result_np, rtol=1e-05)
 
+    @test_with_pir_api
     def check_max_static_results(self, place):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             input = paddle.static.data(
                 name="input", shape=[2, 3, 32, 32, 32], dtype="float32"
             )
@@ -155,9 +161,8 @@ def check_max_static_results(self, place):
                 pool_type='max',
             )
 
-            exe = base.Executor(place)
+            exe = paddle.static.Executor(place)
             fetches = exe.run(
-                base.default_main_program(),
                 feed={"input": input_np},
                 fetch_list=[result],
             )
@@ -366,6 +371,7 @@ def test_pool3d(self):
             self.check_max_dygraph_ndhwc_results(place)
             self.check_max_dygraph_ceilmode_results(place)
 
+    @test_with_pir_api
     def test_static_fp16_gpu(self):
         paddle.enable_static()
         if paddle.base.core.is_compiled_with_cuda():
@@ -384,7 +390,6 @@ def test_static_fp16_gpu(self):
 
                 exe = paddle.static.Executor(place)
                 res = exe.run(
-                    paddle.static.default_main_program(),
                     feed={
                         "x": input,
                     },
@@ -393,6 +398,7 @@ def test_static_fp16_gpu(self):
 
                 np.testing.assert_array_equal(res[0].shape, [1, 2, 1, 16, 16])
 
+    @test_with_pir_api
     def test_static_bf16_gpu(self):
         paddle.enable_static()
         if (
@@ -414,7 +420,6 @@ def test_static_bf16_gpu(self):
 
                 exe = paddle.static.Executor(place)
                 res = exe.run(
-                    paddle.static.default_main_program(),
                     feed={
                         "x": input,
                     },