【PIR API adaptor No.178、169、137、34、129】 Migrate ReLU6/PReLU/LogSigmoid/CELU/LogSoftmax into pir (#58445)

DrRyanHuang · web-flow · commit 89c8a59a3765 · 2023-10-30T10:38:08.000+08:00
* 178, 169, 137, 34, 129

* remove wrong test
diff --git a/python/paddle/nn/functional/activation.py b/python/paddle/nn/functional/activation.py
@@ -61,7 +61,7 @@ def celu(x, alpha=1.0, name=None):
     """
     if alpha == 0:
         raise ZeroDivisionError("alpha cannot be 0 for celu")
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.celu(x, alpha)
     else:
         check_variable_and_dtype(
@@ -594,7 +594,7 @@ def prelu(x, weight, data_format="NCHW", name=None):
             ), "The weight size should be equal to x input channel in prelu() when weight shape is not [1]."
         mode = 'channel'
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.prelu(x, weight, data_format, mode)
     else:
         check_variable_and_dtype(
@@ -813,7 +813,7 @@ def log_sigmoid(x, name=None):
             [-0.31326166, -0.12692805, -0.04858733, -0.01814996])
     """
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.logsigmoid(x)
     else:
         check_variable_and_dtype(
@@ -942,7 +942,7 @@ def relu6(x, name=None):
             [0.        , 0.30000001, 6.        ])
     """
     threshold = 6.0
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.relu6(x)
 
     check_variable_and_dtype(
@@ -1683,7 +1683,7 @@ def log_softmax(x, axis=-1, dtype=None, name=None):
     if (dtype is not None) and (not isinstance(dtype, core.VarDesc.VarType)):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         if dtype is not None:
             x = _C_ops.cast(x, dtype)
         return _C_ops.log_softmax(x, axis)
diff --git a/test/legacy_test/test_activation_op.py b/test/legacy_test/test_activation_op.py
@@ -409,7 +409,7 @@ def init_dtype(self):
         self.dtype = np.complex64
 
     def test_check_output(self):
-        self.check_output(check_prim=False, check_pir=True)
+        self.check_output(check_prim=False)
 
     def test_check_grad(self):
         self.check_grad(
@@ -626,7 +626,7 @@ def setUp(self):
     def test_check_grad(self):
         if self.dtype == np.float16:
             return
-        self.check_grad(['X'], 'Out', max_relative_error=0.008)
+        self.check_grad(['X'], 'Out', max_relative_error=0.008, check_pir=True)
 
 
 class TestLogSigmoidComplex64(TestLogSigmoid):
@@ -655,6 +655,7 @@ def setUp(self):
             else paddle.CPUPlace()
         )
 
+    @test_with_pir_api
     def test_static_api(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):
@@ -2791,7 +2792,7 @@ def init_shape(self):
     def test_check_grad(self):
         if self.dtype == np.float16:
             return
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_pir=True)
 
 
 class TestRelu6_ZeroDim(TestRelu6):
@@ -2811,6 +2812,7 @@ def setUp(self):
             else paddle.CPUPlace()
         )
 
+    @test_with_pir_api
     def test_static_api(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):
@@ -2834,6 +2836,7 @@ def test_dygraph_api(self):
             for r in [out1, out2]:
                 np.testing.assert_allclose(out_ref, r.numpy(), rtol=1e-05)
 
+    @test_with_pir_api
     def test_base_api(self):
         with static_guard():
             with base.program_guard(base.Program()):
@@ -3213,7 +3216,7 @@ def init_shape(self):
     def test_check_grad(self):
         if self.dtype == np.float16:
             return
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_pir=True)
 
 
 class TestCELU_ZeroDim(TestCELU):
@@ -3236,6 +3239,7 @@ def setUp(self):
     def executed_api(self):
         self.celu = F.celu
 
+    @test_with_pir_api
     def test_static_api(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):
diff --git a/test/legacy_test/test_log_softmax.py b/test/legacy_test/test_log_softmax.py
@@ -20,6 +20,7 @@
 import paddle
 import paddle.nn.functional as F
 from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 np.random.seed(10)
 
@@ -63,10 +64,12 @@ def set_attrs(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'], user_defined_grads=[self.x_grad])
+        self.check_grad(
+            ['X'], ['Out'], user_defined_grads=[self.x_grad], check_pir=True
+        )
 
 
 class TestLogSoftmaxOp_ZeroDim(TestLogSoftmaxOp):
@@ -83,10 +86,10 @@ def setUp(self):
         self.attrs = {'axis': -1}
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['X'], ['Out'])
+        self.check_grad(['X'], ['Out'], check_pir=True)
 
 
 class TestLogSoftmaxShape(TestLogSoftmaxOp):
@@ -104,10 +107,10 @@ def set_attrs(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)
 
     def test_check_grad(self):
-        self.check_grad(['X'], ['Out'], max_relative_error=1e-2)
+        self.check_grad(['X'], ['Out'], max_relative_error=1e-2, check_pir=True)
 
 
 class TestLogSoftmaxShapeFP16OP(TestLogSoftmaxFP16OP):
@@ -143,7 +146,7 @@ def setUp(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)
@@ -152,6 +155,7 @@ def test_check_grad(self):
             ['X'],
             ['Out'],
             user_defined_grads=[self.x_grad],
+            check_pir=True,
         )
 
 
@@ -171,6 +175,7 @@ def setUp(self):
             else paddle.CPUPlace()
         )
 
+    @test_with_pir_api
     def check_api(self, axis=-1):
         ref_out = np.apply_along_axis(ref_log_softmax, axis, self.x)
 
@@ -190,6 +195,7 @@ def check_api(self, axis=-1):
         np.testing.assert_allclose(y.numpy(), ref_out, rtol=1e-05)
         paddle.enable_static()
 
+    @test_with_pir_api
     def test_check_api(self):
         for axis in [-1, 1]:
             self.check_api(axis)
@@ -205,6 +211,7 @@ def setUp(self):
             else paddle.CPUPlace()
         )
 
+    @test_with_pir_api
     def check_api(self, axis=-1, dtype=None):
         x = self.x.copy()
         if dtype is not None:
@@ -223,6 +230,7 @@ def check_api(self, axis=-1, dtype=None):
         np.testing.assert_allclose(y.numpy(), ref_out, rtol=1e-05)
         paddle.enable_static()
 
+    @test_with_pir_api
     def test_check_api(self):
         for axis in [-1, 1]:
             self.check_api(axis)
diff --git a/test/legacy_test/test_prelu_op.py b/test/legacy_test/test_prelu_op.py
@@ -21,6 +21,7 @@
 import paddle.nn.functional as F
 from paddle import base
 from paddle.base import Program, core
+from paddle.pir_utils import test_with_pir_api
 
 
 def ref_prelu(x, weight):
@@ -48,6 +49,7 @@ def setUp(self):
         self.weight_np_0 = np.random.randn(1).astype('float32')
         self.weight_np_1 = np.random.randn(self.x_np.shape[1]).astype('float32')
 
+    @test_with_pir_api
     def static_check(self, weight_np):
         with paddle.static.program_guard(paddle.static.Program()):
             x = paddle.static.data('X', self.x_np.shape, 'float32')
@@ -69,6 +71,7 @@ def dygraph_check(self, weight_np):
         np.testing.assert_allclose(out_ref, out.numpy(), rtol=1e-05)
         paddle.enable_static()
 
+    @test_with_pir_api
     def test_static_api(self):
         self.static_check(self.weight_np_0)
         self.static_check(self.weight_np_1)
@@ -105,6 +108,7 @@ def setUp(self):
         )
         self.x_np = np.ones([1, 2, 3, 4]).astype('float32')
 
+    @test_with_pir_api
     def test_static_api(self):
         startup_program = paddle.static.Program()
         train_program = paddle.static.Program()
@@ -226,10 +230,10 @@ def init_attr(self):
         self.attrs = {'mode': "channel", "data_format": "NCHW"}
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['X', 'Alpha'], 'Out')
+        self.check_grad(['X', 'Alpha'], 'Out', check_pir=True)
 
 
 @skip_check_grad_ci(
@@ -392,13 +396,17 @@ def test_check_output(self):
             if core.is_compiled_with_cuda():
                 place = core.CUDAPlace(0)
                 if core.is_float16_supported(place):
-                    self.check_output_with_place(place, atol=atol)
+                    self.check_output_with_place(
+                        place, atol=atol, check_pir=True
+                    )
 
         def test_check_grad(self):
             place = core.CUDAPlace(0)
             if core.is_float16_supported(place) and check_grad:
                 # Use the default max_relative_error, not use max_relative_error
-                self.check_grad_with_place(place, ['X', 'Alpha'], 'Out')
+                self.check_grad_with_place(
+                    place, ['X', 'Alpha'], 'Out', check_pir=True
+                )
 
     cls_name = "{}_{}".format(parent.__name__, "Fp16Op")
     TestPReluFp16Case.__name__ = cls_name
@@ -426,13 +434,15 @@ def init_dtype(self):
 
         def test_check_output(self):
             place = core.CUDAPlace(0)
-            self.check_output_with_place(place, atol=atol)
+            self.check_output_with_place(place, atol=atol, check_pir=True)
 
         def test_check_grad(self):
             place = core.CUDAPlace(0)
             if check_grad:
                 # Use the default max_relative_error, not use max_relative_error
-                self.check_grad_with_place(place, ['X', 'Alpha'], 'Out')
+                self.check_grad_with_place(
+                    place, ['X', 'Alpha'], 'Out', check_pir=True
+                )
 
     cls_name = "{}_{}".format(parent.__name__, "BF16Op")
     TestPReluBF16Op.__name__ = cls_name
