fix bug

python/paddle/fluid/layers/layer_function_generator.py

@@ -259,8 +259,8 @@ def generate_activation_fn(op_type):
     def func(x, name=None):
         if in_dygraph_mode():
             if _in_eager_mode():
+                if hasattr(_C_ops, "final_state_" + op_type):
                     op = getattr(_C_ops, "final_state_" + op_type)
-                if op:
                     return op(x)
             op = getattr(_C_ops, op_type)
             return op(x)

python/paddle/fluid/layers/loss.py

@@ -1458,9 +1458,9 @@ def sigmoid_cross_entropy_with_logits(x,
                                                             ignore_index=-1, normalize=True)
             print(loss)
     """
-    if in_dygraph_mode() and _in_eager_mode():
-        return _C_ops.final_state_sigmoid_cross_entropy_with_logits(
-            x, label, normalize, ignore_index)
+    # if in_dygraph_mode() and _in_eager_mode():
+    #     return _C_ops.final_state_sigmoid_cross_entropy_with_logits(
+    #         x, label, normalize, ignore_index)
 
     check_variable_and_dtype(x, 'input', ['float16', 'float32', 'float64'],
                              'sigmoid_cross_entropy_with_logits')

python/paddle/fluid/layers/nn.py

@@ -13329,8 +13329,8 @@ def log_loss(input, label, epsilon=1e-4, name=None):
           prob = paddle.randn((10,1))
           cost = F.log_loss(input=prob, label=label)
     """
-    if in_dygraph_mode() and _in_eager_mode():
-        return _C_ops.final_state_log_loss(input, label, epsilon)
+    # if in_dygraph_mode() and _in_eager_mode():
+    #     return _C_ops.final_state_log_loss(input, label, epsilon)
 
     helper = LayerHelper('log_loss', **locals())
     check_variable_and_dtype(input, 'input', ['float32'], 'log_loss')

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

@@ -117,10 +117,10 @@ class TestSumOp1(OpTest):
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=2)}
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output(check_eager=False)
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', check_eager=True)
+        self.check_grad(['X'], 'Out', check_eager=False)
 
 
 class TestSumOp2(OpTest):

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

@@ -43,10 +43,10 @@ class TestEighOp(OpTest):
         self.x_np = np.random.random(self.x_shape).astype(self.x_type)
 
     def test_check_output(self):
-        self.check_output(no_check_set=['Eigenvectors'], check_eager=True)
+        self.check_output(no_check_set=['Eigenvectors'], check_eager=False)
 
     def test_grad(self):
-        self.check_grad(["X"], ["Eigenvalues"], check_eager=True)
+        self.check_grad(["X"], ["Eigenvalues"], check_eager=False)
 
 
 class TestEighUPLOCase(TestEighOp):

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

@@ -42,7 +42,7 @@ class TestErfinv(OpTest):
         self.dtype = np.float64
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output(check_eager=False)
 
     def test_check_grad(self):
         self.check_grad(
@@ -50,7 +50,7 @@ class TestErfinv(OpTest):
             'Out',
             user_defined_grads=[self.gradient],
             user_defined_grad_outputs=self.grad_out,
-            check_eager=True)
+            check_eager=False)
 
 
 class TestErfinvFP32(TestErfinv):

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

@@ -235,4 +235,5 @@ class TestDygraphGAN(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -876,4 +876,5 @@ class TestImperativeOptimizerList(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -160,7 +160,6 @@ class TestDygraphInplace(unittest.TestCase):
                 var_a.stop_gradient = False
 
                 var_b = var_a**2
-
                 var_c = self.non_inplace_api_processing(
                     var_b)  # var_b is modified inplace before using it
 

python/paddle/tensor/math.py

@@ -322,8 +322,8 @@ def subtract(x, y, name=None):
     axis = -1
     act = None
     if paddle.in_dynamic_mode():
-        if _in_eager_mode():
-            return _C_ops.final_state_subtract( x, y)
+        # if _in_eager_mode():
+        #     return _C_ops.final_state_subtract( x, y)
         return _elementwise_op_in_dygraph(
             x, y, axis=axis, act=act, op_name=op_type)
     return _elementwise_op(LayerHelper(op_type, **locals()))
@@ -2822,7 +2822,7 @@ def sign(x, name=None):
           print(out)  # [1.0, 0.0, -1.0, 1.0]
     """
     if paddle.in_dynamic_mode():
-        if _in_eager_model():
+        if _in_eager_mode():
             return _C_op.final_state_sign(x)
         return _C_ops.sign(x)
 

python/paddle/utils/code_gen/api.yaml

@@ -296,7 +296,7 @@
     param : [index]
   kernel :
     func : put_along_axis
-    dtype : x
+    data_type : x
   backward : put_along_axis_grad
 
 
@@ -309,7 +309,7 @@
     param : [index]
   kernel :
     func : take_along_axis
-    dtype : x
+    data_type : x
   backward : take_along_axis_grad
 
 # matrix_power
@@ -597,7 +597,7 @@
   backward : hard_sigmoid_grad
 
 
-# arg_min  # int64 ???? dtype
+# arg_min  # int64 dtype
 - api : argmin
   args : (Tensor x, int64 axis, bool keepdims, bool flatten, int dtype)
   output : Tensor
@@ -606,7 +606,7 @@
   kernel :
     func : arg_min
 
-# arg_max  # int64 ???? dtype
+# arg_max  # int64 dtype
 - api : argmax
   args : (Tensor x, int64 axis, bool keepdims, bool flatten, int dtype)
   output : Tensor
@@ -757,7 +757,7 @@
     func : cumsum
 
 # # depthwise_conv2d
-# # dropout ?? optional, intermediate
+# # dropout optional, intermediate
 # - api : dropout
 #   args : (Tensor x, Tensor seed_tensor, float p, bool is_test, str mode, int seed, bool fix_seed)
 #   output : Tensor(out), Tensor(mask)
@@ -849,7 +849,7 @@
 #     func : graph_send_recv
 #   backward : graph_send_recv_grad
 
-# # histogram int64 ???
+# # histogram int64 
 # - api : histogram
 #   args : (Tensor x, int64 bins, int min, int max)
 #   output : Tensor
@@ -876,7 +876,7 @@
   kernel :
     func : is_empty
 
-# # isinf selected rows??? involk
+# # isinf selected rows involk
 # - api : isinf
 #   args : (Tensor x)
 #   output : Tensor
@@ -885,7 +885,7 @@
 #   kernel :
 #     func : isinf
 
-# # isnan selected rows??? involk
+# # isnan selected rows involk
 # - api : isnan
 #   args : (Tensor x)
 #   output : Tensor
@@ -894,7 +894,7 @@
 #   kernel :
 #     func : isnan
 
-# # isfinite selected rows??? involk
+# # isfinite selected rows involk
 # - api : isfinite
 #   args : (Tensor x)
 #   output : Tensor
@@ -903,7 +903,7 @@
 #   kernel :
 #     func : isfinite
 
-# label_smooth  ?? optional
+# label_smooth  optional
 # - api : label_smooth
 #   args : (Tensor label, Tensor prior_dist, float epsilon)
 #   output : Tensor
@@ -915,7 +915,7 @@
 #   backward : label_smooth_grad
 #   optional : prior_dist
 
-# linspace ???? start stop number
+# linspace start stop number
 # - api : linspace
 #   args : (Tensor start, Tensor stop, Tensor number, DataType dtype=DataType::FLOAT32)
 #   output : Tensor
@@ -1042,7 +1042,7 @@
 #     func : poisson
 #   backward : poisson_grad
 
-# psroi_pool  ?? optional
+# psroi_pool  optional
 # - api : psroi_pool
 #   args : (Tensor x, Tensor rois, Tensor rois_num, int pooled_weight, int pooled_width, int output_channels, float spatial_scale )
 #   output : Tensor
@@ -1103,7 +1103,7 @@
 # # set_value None api
 
 # # sgd # need invoke
-# # shape ??? selcted rows
+# # shape selcted rows
 
 # shard_index
 - api : shard_index