replace data layers, test=develop, test=document_fix (#20368)

paddle/fluid/API.spec

@@ -91,8 +91,8 @@ paddle.fluid.io.PyReader.reset (ArgSpec(args=['self'], varargs=None, keywords=No
 paddle.fluid.io.PyReader.start (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'a0983fb21a0a51e6a31716009fe9a9c1'))
 paddle.fluid.io.DataLoader ('paddle.fluid.reader.DataLoader', ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.io.DataLoader.__init__ 
-paddle.fluid.io.DataLoader.from_dataset (ArgSpec(args=['dataset', 'places', 'drop_last'], varargs=None, keywords=None, defaults=(True,)), ('document', '58e8bffa033f26b00b256c8bb1daff11'))
-paddle.fluid.io.DataLoader.from_generator (ArgSpec(args=['feed_list', 'capacity', 'use_double_buffer', 'iterable', 'return_list'], varargs=None, keywords=None, defaults=(None, None, True, True, False)), ('document', '8034bdb488fa18d60c4ffb0ba9658337'))
+paddle.fluid.io.DataLoader.from_dataset (ArgSpec(args=['dataset', 'places', 'drop_last'], varargs=None, keywords=None, defaults=(True,)), ('document', 'eb8b6d31e1c2ec2ca8ebbb62fcf46557'))
+paddle.fluid.io.DataLoader.from_generator (ArgSpec(args=['feed_list', 'capacity', 'use_double_buffer', 'iterable', 'return_list'], varargs=None, keywords=None, defaults=(None, None, True, True, False)), ('document', 'e3bdde36774236c3e381d2218e9cc09e'))
 paddle.fluid.io.cache (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', '1676886070eb607cb608f7ba47be0d3c'))
 paddle.fluid.io.map_readers (ArgSpec(args=['func'], varargs='readers', keywords=None, defaults=None), ('document', '77cbadb09df588e21e5cc0819b69c87d'))
 paddle.fluid.io.buffered (ArgSpec(args=['reader', 'size'], varargs=None, keywords=None, defaults=None), ('document', '0d6186f109feceb99f60ec50a0a624cb'))
@@ -1010,7 +1010,7 @@ paddle.fluid.optimizer.RMSPropOptimizer.get_opti_var_name_list (ArgSpec(args=['s
 paddle.fluid.optimizer.RMSPropOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', '8387af01322a6defc92c1832faccd304'))
 paddle.fluid.optimizer.RMSPropOptimizer.set_dict (ArgSpec(args=['self', 'state_dict'], varargs=None, keywords=None, defaults=None), ('document', '36aa497a2d29abaa4147987d71721d17'))
 paddle.fluid.optimizer.RMSPropOptimizer.state_dict (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'deca1537945d33940b350923fb16ddf8'))
-paddle.fluid.optimizer.AdadeltaOptimizer ('paddle.fluid.optimizer.AdadeltaOptimizer', ('document', 'f4354aef5e3b9134fa68919b75a3a097'))
+paddle.fluid.optimizer.AdadeltaOptimizer ('paddle.fluid.optimizer.AdadeltaOptimizer', ('document', '6710aad9700421ac6ccb4088b6b7f250'))
 paddle.fluid.optimizer.AdadeltaOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'epsilon', 'rho', 'regularization', 'name'], varargs=None, keywords=None, defaults=(1e-06, 0.95, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.optimizer.AdadeltaOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610'))
 paddle.fluid.optimizer.AdadeltaOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae'))
@@ -1101,7 +1101,7 @@ paddle.fluid.CUDAPlace ('paddle.fluid.core_avx.CUDAPlace', ('document', 'f862cb3
 paddle.fluid.CUDAPlace.__init__ __init__(self: paddle.fluid.core_avx.CUDAPlace, arg0: int) -> None
 paddle.fluid.CUDAPinnedPlace ('paddle.fluid.core_avx.CUDAPinnedPlace', ('document', '1320ef739c81c95385330dab3fe6e80b'))
 paddle.fluid.CUDAPinnedPlace.__init__ __init__(self: paddle.fluid.core_avx.CUDAPinnedPlace) -> None
-paddle.fluid.ParamAttr ('paddle.fluid.param_attr.ParamAttr', ('document', 'a4d4d13ce9eeb86bbaa7ab935c207577'))
+paddle.fluid.ParamAttr ('paddle.fluid.param_attr.ParamAttr', ('document', '7b5bfe856689036b8fffb71af1558e5c'))
 paddle.fluid.ParamAttr.__init__ (ArgSpec(args=['self', 'name', 'initializer', 'learning_rate', 'regularizer', 'trainable', 'gradient_clip', 'do_model_average'], varargs=None, keywords=None, defaults=(None, None, 1.0, None, True, None, True)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.WeightNormParamAttr ('paddle.fluid.param_attr.WeightNormParamAttr', ('document', 'b5ae1698ea72d5a9428000b916a67379'))
 paddle.fluid.WeightNormParamAttr.__init__ (ArgSpec(args=['self', 'dim', 'name', 'initializer', 'learning_rate', 'regularizer', 'trainable', 'gradient_clip', 'do_model_average'], varargs=None, keywords=None, defaults=(None, None, None, 1.0, None, True, None, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
@@ -1110,7 +1110,7 @@ paddle.fluid.DataFeeder.__init__ (ArgSpec(args=['self', 'feed_list', 'place', 'p
 paddle.fluid.DataFeeder.decorate_reader (ArgSpec(args=['self', 'reader', 'multi_devices', 'num_places', 'drop_last'], varargs=None, keywords=None, defaults=(None, True)), ('document', 'a0ed5ce816b5d603cb595aacb922335a'))
 paddle.fluid.DataFeeder.feed (ArgSpec(args=['self', 'iterable'], varargs=None, keywords=None, defaults=None), ('document', 'ce65fe1d81dcd7067d5092a5667f35cc'))
 paddle.fluid.DataFeeder.feed_parallel (ArgSpec(args=['self', 'iterable', 'num_places'], varargs=None, keywords=None, defaults=(None,)), ('document', '334c6af750941a4397a2dd2ea8a4d76f'))
-paddle.fluid.clip.set_gradient_clip (ArgSpec(args=['clip', 'param_list', 'program'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'a0b00ccc8584b4a1cf4ec5aa74780e77'))
+paddle.fluid.clip.set_gradient_clip (ArgSpec(args=['clip', 'param_list', 'program'], varargs=None, keywords=None, defaults=(None, None)), ('document', '7a0f76a77dd88a74f24485a103a22fc1'))
 paddle.fluid.clip.ErrorClipByValue ('paddle.fluid.clip.ErrorClipByValue', ('document', 'e6f815a03be88dee2537707d9e6b9209'))
 paddle.fluid.clip.ErrorClipByValue.__init__ (ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.clip.GradientClipByValue ('paddle.fluid.clip.GradientClipByValue', ('document', 'b7a22f687269cae0c338ef3866322db7'))

python/paddle/fluid/clip.py

@@ -360,7 +360,7 @@ def set_gradient_clip(clip, param_list=None, program=None):
             import paddle.fluid as fluid
 
             def network():
-                image = fluid.layers.data(name='image', shape=[28], dtype='float32')
+                image = fluid.data(name='image', shape=[None, 28], dtype='float32')
                 param_attr1 = fluid.ParamAttr("fc1_param")
                 fc1 = fluid.layers.fc(image, size=10, param_attr=param_attr1)
                 param_attr2 = fluid.ParamAttr("fc2_param")

python/paddle/fluid/optimizer.py

@@ -1894,7 +1894,7 @@ class AdadeltaOptimizer(Optimizer):
 
             import paddle.fluid as fluid
 
-            image = fluid.layers.data(name='image', shape=[28], dtype='float32')
+            image = fluid.data(name='image', shape=[None, 28], dtype='float32')
             fc = fluid.layers.fc(image, size=10)
             cost = fluid.layers.reduce_mean(fc)
             optimizer = fluid.optimizer.Adadelta(

python/paddle/fluid/param_attr.py

@@ -58,7 +58,7 @@ class ParamAttr(object):
                                             regularizer=fluid.regularizer.L2Decay(1.0),
                                             trainable=True)
             print(w_param_attrs.name) # "fc_weight"
-            x = fluid.layers.data(name='X', shape=[1], dtype='float32')
+            x = fluid.data(name='X', shape=[None, 1], dtype='float32')
             y_predict = fluid.layers.fc(input=x, size=10, param_attr=w_param_attrs)
     """
 

python/paddle/fluid/reader.py

@@ -99,7 +99,7 @@ class DataLoader(object):
 
         Args:  
             feed_list (list(Variable)|tuple(Variable)): feed variable list.
-                The variables should be created by :code:`fluid.layers.data()`.
+                The variables should be created by :code:`fluid.data()`.
             capacity (int): capacity of the queue maintained in DataLoader.
                 The unit is batch number. Set larger capacity if your reader 
                 is fast. 
@@ -212,8 +212,8 @@ class DataLoader(object):
                     else:
                         raise ValueError('Unsupported data format')
 
-                image = fluid.layers.data(name='image', shape=[784], dtype='float32')
-                label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+                image = fluid.data(name='image', shape=[None, 784], dtype='float32')
+                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
 
                 # Define DataLoader 
                 loader = fluid.io.DataLoader.from_generator(feed_list=[image, label], capacity=16, iterable=ITERABLE)
@@ -281,8 +281,8 @@ class DataLoader(object):
 
                 import paddle.fluid as fluid
 
-                image = fluid.layers.data(name='image', shape=[784], dtype='float32')
-                label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+                image = fluid.data(name='image', shape=[None, 784], dtype='float32')
+                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
 
                 dataset = fluid.DatasetFactory().create_dataset("QueueDataset")
                 dataset.set_batch_size(32)