clean elementwise doc (#49004)

python/paddle/distributed/fleet/metrics/metric.py

@@ -41,7 +41,7 @@ def sum(input, scope=None, util=None):
           input = fluid.layers.cast(some_input, dtype='float32')
           cnt = paddle.sum(input)
           global_cnt = paddle.static.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
-          tmp = fluid.layers.elementwise_add(cnt, global_cnt)
+          tmp = paddle.add(cnt, global_cnt)
           fluid.layers.assign(tmp, global_cnt)
 
           # in train.py, after train or infer
@@ -121,7 +121,7 @@ def min(input, scope=None, util=None):
           input = fluid.layers.cast(some_input, dtype='float32')
           cnt = paddle.sum(input)
           global_cnt = paddle.static.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
-          tmp = fluid.layers.elementwise_min(cnt, global_cnt)
+          tmp = paddle.minimum(cnt, global_cnt)
           fluid.layers.assign(tmp, global_cnt)
 
           # in train.py, after train or infer
@@ -161,7 +161,7 @@ def auc(stat_pos, stat_neg, scope=None, util=None):
           # in model.py
           similarity_norm = fluid.layers.sigmoid(fluid.layers.clip(output, min=-15.0, max=15.0))
           binary_predict = fluid.layers.concat(
-              input=[fluid.layers.elementwise_sub(fluid.layers.ceil(similarity_norm), similarity_norm), similarity_norm], axis=1)
+              input=[paddle.subtract(fluid.layers.ceil(similarity_norm), similarity_norm), similarity_norm], axis=1)
           self.auc, batch_auc, [batch_stat_pos, batch_stat_neg, stat_pos, stat_neg] =
               paddle.static.auc(input=binary_predict, label=label, curve='ROC', num_thresholds=4096)
 
@@ -396,11 +396,11 @@ def acc(correct, total, scope=None, util=None):
           acc = fluid.layers.acc(predict, label, k=1, correct=correct, total=total)
 
           global_correct = paddle.static.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
-          tmp1 = fluid.layers.elementwise_min(correct, global_correct)
+          tmp1 = paddle.minimum(correct, global_correct)
           fluid.layers.assign(tmp1, global_correct)
 
           global_total = paddle.static.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
-          tmp2 = fluid.layers.elementwise_min(total, global_total)
+          tmp2 = paddle.minimum(total, global_total)
           fluid.layers.assign(tmp2, global_total)
 
           # in train.py, after train or infer

python/paddle/fluid/data_feeder.py

@@ -485,7 +485,7 @@ class DataFeeder:
                 x = fluid.data(name='x', shape=[None, 2, 2])
                 y = fluid.data(name='y', shape=[None, 2, 2], dtype='float32')
 
-                z = fluid.layers.elementwise_add(x, y)
+                z = paddle.add(x, y)
 
                 feeder = fluid.DataFeeder(['x','y'], fluid.CPUPlace())
                 place_num = 2

python/paddle/fluid/incubate/fleet/utils/fleet_util.py

@@ -188,7 +188,7 @@ class FleetUtil:
               similarity_norm = fluid.layers.sigmoid(fluid.layers.clip(\
                   emb, min=-15.0, max=15.0), name="similarity_norm")\
               binary_predict = fluid.layers.concat(input=[\
-                  fluid.layers.elementwise_sub(\
+                  paddle.subtract(\
                       fluid.layers.ceil(similarity_norm), similarity_norm),\
                   similarity_norm], axis=1)
               auc, batch_auc, [batch_stat_pos, batch_stat_neg, stat_pos, \
@@ -1377,7 +1377,7 @@ class FleetUtil:
               similarity_norm = fluid.layers.sigmoid(fluid.layers.clip(\
                   emb, min=-15.0, max=15.0), name="similarity_norm")\
               binary_predict = fluid.layers.concat(input=[\
-                  fluid.layers.elementwise_sub(\
+                  paddle.subtract(\
                       fluid.layers.ceil(similarity_norm), similarity_norm),\
                   similarity_norm], axis=1)
               auc, batch_auc, [batch_stat_pos, batch_stat_neg, stat_pos, \
@@ -1577,7 +1577,7 @@ class FleetUtil:
               similarity_norm = fluid.layers.sigmoid(fluid.layers.clip(\
                   emb, min=-15.0, max=15.0), name="similarity_norm")\
               binary_predict = fluid.layers.concat(input=[\
-                  fluid.layers.elementwise_sub(\
+                  paddle.subtract(\
                       fluid.layers.ceil(similarity_norm), similarity_norm),\
                   similarity_norm], axis=1)
               auc, batch_auc, [batch_stat_pos, batch_stat_neg, stat_pos, \

python/paddle/fluid/io.py

@@ -359,7 +359,7 @@ def save_vars(
                 w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w')
                 b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b')
                 hidden_w = paddle.matmul(x=data, y=w)
-                hidden_b = fluid.layers.elementwise_add(hidden_w, b)
+                hidden_b = paddle.add(hidden_w, b)
             place = fluid.CPUPlace()
             exe = fluid.Executor(place)
             exe.run(startup_prog)
@@ -834,7 +834,7 @@ def load_vars(
                 w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w')
                 b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b')
                 hidden_w = paddle.matmul(x=data, y=w)
-                hidden_b = fluid.layers.elementwise_add(hidden_w, b)
+                hidden_b = paddle.add(hidden_w, b)
             place = fluid.CPUPlace()
             exe = fluid.Executor(place)
             exe.run(startup_prog)
@@ -1602,7 +1602,7 @@ def load_inference_model(
                 w = paddle.create_parameter(shape=[784, 200], dtype='float32')
                 b = paddle.create_parameter(shape=[200], dtype='float32')
                 hidden_w = paddle.matmul(x=data, y=w)
-                hidden_b = fluid.layers.elementwise_add(hidden_w, b)
+                hidden_b = paddle.add(hidden_w, b)
             place = fluid.CPUPlace()
             exe = fluid.Executor(place)
             exe.run(startup_prog)

python/paddle/fluid/layers/control_flow.py

@@ -1088,10 +1088,10 @@ class While:
             cond = paddle.less_than(x=i, y=loop_len)
             while_op = fluid.layers.While(cond=cond)
             with while_op.block():
-                sums_tensor = fluid.layers.elementwise_add(x=data, y=data)
+                sums_tensor = paddle.add(x=data, y=data)
                 fluid.layers.assign(sums_tensor, sums)  # Update the value of sums_tensor defined in While to the sums which defined outside of While through layers.assign
                 i = paddle.increment(x=i, value=1)
-                data = fluid.layers.elementwise_add(x=data, y=one)
+                data = paddle.add(x=data, y=one)
                 paddle.assign(paddle.less_than(x=i, y=loop_len), cond)
 
             feed_data = np.ones(1).astype('float32')

python/paddle/fluid/tests/unittests/xpu/test_assign_op_xpu.py

@@ -47,7 +47,7 @@ class TestAssignOpWithLoDTensorArray(unittest.TestCase):
             x.stop_gradient = False
             y = fluid.layers.fill_constant(
                 shape=[100, 10], dtype='float32', value=1)
-            z = fluid.layers.elementwise_add(x=x, y=y)
+            z = paddle.add(x=x, y=y)
             i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
             init_array = paddle.tensor.array_write(x=z, i=i)
             array = fluid.layers.assign(init_array)