modify optimizer tests (#51084)

* modify optimizer tests

* lint

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -23,10 +23,47 @@ from paddle.fluid import core
 from paddle.fluid.op import Operator
 
 
+def adam_wrapper(
+    param,
+    grad,
+    LearningRate,
+    moment1,
+    moment2,
+    beta1_pow,
+    beta2_pow,
+    master_weight=None,
+    find_inf=None,
+    beta1=0.78,
+    beta2=0.836,
+    epsilon=1e-4,
+    lazy_mode=False,
+):
+    _, _, _, _, _, _ = paddle._C_ops.adam_(
+        param,
+        grad,
+        LearningRate,
+        moment1,
+        moment2,
+        beta1_pow,
+        beta2_pow,
+        master_weight,
+        find_inf,
+        beta1,
+        beta2,
+        epsilon,
+        lazy_mode,
+        1000,
+        False,
+        False,
+    )
+
+
 class TestAdamOp1(OpTest):
     def setUp(self):
         '''Test Adam Op with supplied attributes'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -73,6 +110,8 @@ class TestAdamOp2(OpTest):
     def setUp(self):
         '''Test Adam Op with supplied attributes'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         self.set_shape()
         param = np.random.uniform(-1, 1, self.shape).astype("float32")
         grad = np.random.uniform(-1, 1, self.shape).astype("float32")
@@ -122,6 +161,8 @@ class TestAdamOpMultipleSteps(OpTest):
     def setUp(self):
         '''Test Adam Operator with supplied attributes'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         self.num_steps = 10
 
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -414,6 +455,8 @@ class TestAdamOpBetaVariable(OpTest):
     def setUp(self):
         '''Test Adam Op with beta as Variable'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -459,6 +502,8 @@ class TestAdamOpBetaEpsilonVariable(OpTest):
     def setUp(self):
         '''Test Adam Op with beta/epsilon as Variable'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -505,6 +550,8 @@ class TestAdamOpWithGlobalBetaPow(OpTest):
     def setUp(self):
         '''Test Adam Op with global_beta_pow'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -554,6 +601,8 @@ class TestAdamOpWithSkipUpdate(OpTest):
     def setUp(self):
         '''Test Adam Op with global_beta_pow'''
         self.op_type = "adam"
+        self.python_api = adam_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")

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

@@ -15,7 +15,33 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
+
+import paddle
+
+
+def adamx_wrapper(
+    param,
+    grad,
+    lr,
+    moment,
+    inf_norm,
+    beta1_pow=None,
+    beta1=0.78,
+    beta2=0.899,
+    epsilon=1e-5,
+):
+    return paddle._C_ops.adamax_(
+        param,
+        grad,
+        lr,
+        moment,
+        inf_norm,
+        beta1_pow,
+        beta1,
+        beta2,
+        epsilon,
+    )
 
 import paddle
 
@@ -24,6 +50,8 @@ class TestAdamaxOp1(OpTest):
     def setUp(self):
         '''Test Adamax Operator with supplied attributes'''
         self.op_type = "adamax"
+        self.python_api = adamx_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -66,6 +94,8 @@ class TestAdamaxOp2(OpTest):
 
     def setUp(self):
         self.op_type = "adamax"
+        self.python_api = adamx_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -104,6 +134,8 @@ class TestAdamaxOpMultipleSteps(OpTest):
     def setUp(self):
         '''Test Adamax Operator with supplied attributes'''
         self.op_type = "adamax"
+        self.python_api = adamx_wrapper
+        self.python_out_sig = ['Out']
         self.num_steps = 10
 
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")

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

@@ -17,7 +17,7 @@ import unittest
 from functools import partial
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -60,10 +60,53 @@ def adamw_step(inputs, attributes):
     return param_out, moment1_out, moment2_out
 
 
+def adamw_wrapper(
+    param,
+    grad,
+    lr,
+    moment1,
+    moment2,
+    beta1_pow,
+    beta2_pow,
+    master_weight=None,
+    found_inf=None,
+    beta1=0.78,
+    beta2=0.836,
+    epsilon=1e-4,
+    lr_ratio=1.0,
+    weight_decay=0.01,
+    with_decay=True,
+    lazy_mode=False,
+):
+    _, _, _, _, _, _ = paddle._C_ops.adamw_(
+        param,
+        grad,
+        lr,
+        moment1,
+        moment2,
+        beta1_pow,
+        beta2_pow,
+        master_weight,
+        found_inf,
+        beta1,
+        beta2,
+        epsilon,
+        lr_ratio,
+        weight_decay,
+        with_decay,
+        lazy_mode,
+        1000,
+        False,
+        False,
+    )
+
+
 class TestAdamW(OpTest):
     def setUp(self):
         '''Test AdamW Op with supplied attributes'''
         self.op_type = "adamw"
+        self.python_api = adamw_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         grad = np.random.uniform(-1, 1, (102, 105)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (102, 105)).astype("float32")
@@ -118,6 +161,8 @@ class TestAdamW2(OpTest):
     def setUp(self):
         '''Test AdamW Op with supplied attributes'''
         self.op_type = "adamw"
+        self.python_api = adamw_wrapper
+        self.python_out_sig = ['Out']
         param = np.random.uniform(-1, 1, (2, 2)).astype("float32")
         grad = np.random.uniform(-1, 1, (2, 2)).astype("float32")
         moment1 = np.random.uniform(-1, 1, (2, 2)).astype("float32")

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 from paddle.fluid import core
@@ -32,6 +32,8 @@ def lamb_wrapper(
     moment2,
     beta1Pow,
     beta2Pow,
+    master_weight=None,
+    found_inf=None,
     epsilon=1e-8,
     beta1=0.9,
     beta2=0.999,
@@ -45,8 +47,8 @@ def lamb_wrapper(
         moment2,
         beta1Pow,
         beta2Pow,
-        None,
-        None,
+        master_weight,
+        found_inf,
         weight_decay,
         beta1,
         beta2,