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P
Paddle
未验证 提交 5670644c 编写于 作者: G GGBond8488 提交者： GitHub
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Fluid clean remove io data (#49301) 

* replace paddle.fluid.layers.data and remove io.data

* partial commit

* partial commit

* partial commit

* partial commit

* partial commit

* partial commit

* remove data in fluid.layers.io.__all__

* fix errors

* fix unitests

* fix unitest

* fix unitests

* fix unitest

* fix unitest

* fix unitests

* fix unitest

* fix test_layers unitests

* fix typro

* fix unitest

* fix unitest

* fix unitest

* fix typro

* fix unitest test_model_cast_to_bf16

* fix test_reducescatter

* fix collective unitest

* fix collective unitests

* fix collective unitests

* add coverage

* fix add layers.data

* re run ci

* fix some typro

* fix samplecode error

* fix samplecode error
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python/paddle/fluid/contrib/layers/nn.py
浏览文件 @ 5670644c
...@@ -98,10 +98,12 @@ def fused_embedding_seq_pool( ...@@ -98,10 +98,12 @@ def fused_embedding_seq_pool(
.. code-block:: python .. code-block:: python
import numpy as np import numpy as np
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle
paddle.enable_static()
dict_size = 20 dict_size = 20
data_t = fluid.layers.data( data_t = paddle.static.data(
name='word', shape=[1], dtype='int64', lod_level=1) name='word', shape=[-1, 1], dtype='int64', lod_level=1)
padding_idx = np.random.randint(1, 10) padding_idx = np.random.randint(1, 10)
out = fluid.contrib.fused_embedding_seq_pool( out = fluid.contrib.fused_embedding_seq_pool(
input=data_t, input=data_t,
...@@ -305,11 +307,13 @@ def multiclass_nms2( ...@@ -305,11 +307,13 @@ def multiclass_nms2(
import paddle.fluid as fluid import paddle.fluid as fluid
boxes = fluid.layers.data(name='bboxes', shape=[81, 4], import paddle
paddle.enable_static()
boxes = paddle.static.data(name='bboxes', shape=[-1, 81, 4],
dtype='float32', lod_level=1) dtype='float32', lod_level=1)
scores = fluid.layers.data(name='scores', shape=[81], scores = paddle.static.data(name='scores', shape=[-1, 81],
dtype='float32', lod_level=1) dtype='float32', lod_level=1)
out, index = fluid.layers.multiclass_nms2(bboxes=boxes, out, index = fluid.contrib.layers.multiclass_nms2(bboxes=boxes,
scores=scores, scores=scores,
background_label=0, background_label=0,
score_threshold=0.5, score_threshold=0.5,
...@@ -501,7 +505,9 @@ def shuffle_batch(x, seed=None): ...@@ -501,7 +505,9 @@ def shuffle_batch(x, seed=None):
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
x = fluid.layers.data(name="x", shape=[-1, 4]) import paddle
paddle.enable_static()
x = paddle.static.data(name="x", shape=[-1, 4])
out = fluid.contrib.layers.shuffle_batch(x) out = fluid.contrib.layers.shuffle_batch(x)
""" """
helper = LayerHelper('shuffle_batch', **locals()) helper = LayerHelper('shuffle_batch', **locals())
...@@ -1313,7 +1319,7 @@ def _pull_box_extended_sparse(input, size, extend_size=64, dtype='float32'): ...@@ -1313,7 +1319,7 @@ def _pull_box_extended_sparse(input, size, extend_size=64, dtype='float32'):
Examples: Examples:
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
data = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data = paddle.static.data(name='sequence', shape=[-1, 1], dtype='int64', lod_level=1)
emb, emb_ex = fluid.contrib.layers._pull_box_extended_sparse(input=data, size=8, extend_size=128) emb, emb_ex = fluid.contrib.layers._pull_box_extended_sparse(input=data, size=8, extend_size=128)
""" """
helper = LayerHelper('pull_box_extended_sparse', **locals()) helper = LayerHelper('pull_box_extended_sparse', **locals())
...@@ -1438,15 +1444,14 @@ def correlation( ...@@ -1438,15 +1444,14 @@ def correlation(
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle
x1 = fluid.layers.data(name='x1', paddle.enable_static()
shape=x_shape, x1 = paddle.static.data(name='x1',
dtype=x_type, shape=[2,3,4,5],
append_batch_size=False) dtype="float32")
x2 = fluid.layers.data(name='x2', x2 = paddle.static.data(name='x2',
shape=x_shape, shape=[2,3,4,5],
dtype=x_type, dtype="float32")
append_batch_size=False)
out = fluid.contrib.correlation( out = fluid.contrib.correlation(
...@@ -1555,8 +1560,8 @@ def fused_bn_add_act( ...@@ -1555,8 +1560,8 @@ def fused_bn_add_act(
# required: gpu # required: gpu
def build_program(main_program, startup_program): def build_program(main_program, startup_program):
with fluid.program_guard(main_program, startup_program): with fluid.program_guard(main_program, startup_program):
x = fluid.layers.data(name='x', shape=[1, 28, 28], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 1, 28, 28], dtype='float32')
y = fluid.layers.data(name="y", shape=[1], dtype='int64') y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
conv1_1 = paddle.static.nn.conv2d( conv1_1 = paddle.static.nn.conv2d(
input=x, input=x,
filter_size=3, filter_size=3,
......
python/paddle/fluid/contrib/tests/test_correlation.py
浏览文件 @ 5670644c
...@@ -85,20 +85,20 @@ class TestCorrelationOp(unittest.TestCase): ...@@ -85,20 +85,20 @@ class TestCorrelationOp(unittest.TestCase):
np.set_printoptions(threshold=np.inf) np.set_printoptions(threshold=np.inf)
x_shape = (2, 10, 3, 3) x_shape = (2, 10, 3, 3)
x_type = 'float32' x_type = 'float32'
x1 = fluid.layers.data( x1 = paddle.static.data(
name='x1', name='x1',
shape=x_shape, shape=x_shape,
dtype=x_type, dtype=x_type,
append_batch_size=False,
stop_gradient=False,
) )
x2 = fluid.layers.data( x1.desc.set_need_check_feed(False)
x1.stop_gradient = False
x2 = paddle.static.data(
name='x2', name='x2',
shape=x_shape, shape=x_shape,
dtype=x_type, dtype=x_type,
append_batch_size=False,
stop_gradient=False,
) )
x2.desc.set_need_check_feed(False)
x2.stop_gradient = False
x1_np = np.random.randn(2, 3, 4, 5).astype(x_type) x1_np = np.random.randn(2, 3, 4, 5).astype(x_type)
x2_np = np.random.randn(2, 3, 4, 5).astype(x_type) x2_np = np.random.randn(2, 3, 4, 5).astype(x_type)
......
python/paddle/fluid/contrib/tests/test_image_classification_fp16.py
浏览文件 @ 5670644c
...@@ -110,10 +110,10 @@ def train(net_type, use_cuda, save_dirname, is_local): ...@@ -110,10 +110,10 @@ def train(net_type, use_cuda, save_dirname, is_local):
train_program.random_seed = 123 train_program.random_seed = 123
startup_prog.random_seed = 456 startup_prog.random_seed = 456
with fluid.program_guard(train_program, startup_prog): with fluid.program_guard(train_program, startup_prog):
images = fluid.layers.data( images = paddle.static.data(
name='pixel', shape=data_shape, dtype='float32' name='pixel', shape=[-1] + data_shape, dtype='float32'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
if net_type == "vgg": if net_type == "vgg":
print("train vgg net") print("train vgg net")
...@@ -444,11 +444,11 @@ class TestAmpWithNonIterableDataLoader(unittest.TestCase): ...@@ -444,11 +444,11 @@ class TestAmpWithNonIterableDataLoader(unittest.TestCase):
start_prog = paddle.static.Program() start_prog = paddle.static.Program()
with paddle.static.program_guard(main_prog, start_prog): with paddle.static.program_guard(main_prog, start_prog):
with paddle.fluid.unique_name.guard(): with paddle.fluid.unique_name.guard():
image = fluid.layers.data( image = paddle.static.data(
name='image', shape=[3, 224, 224], dtype='float32' name='image', shape=[-1, 3, 224, 224], dtype='float32'
) )
label = fluid.layers.data( label = paddle.static.data(
name='label', shape=[1], dtype='int64' name='label', shape=[-1, 1], dtype='int64'
) )
py_reader = fluid.io.DataLoader.from_generator( py_reader = fluid.io.DataLoader.from_generator(
feed_list=[image, label], feed_list=[image, label],
......
python/paddle/fluid/contrib/tests/test_model_cast_to_bf16.py
浏览文件 @ 5670644c
...@@ -96,14 +96,22 @@ class TestModelCastBF16(unittest.TestCase): ...@@ -96,14 +96,22 @@ class TestModelCastBF16(unittest.TestCase):
nn_bf16 = amp.bf16.convert_float_to_uint16(nn) nn_bf16 = amp.bf16.convert_float_to_uint16(nn)
with self.static_graph(): with self.static_graph():
t_bf16 = layers.data( t_bf16 = paddle.static.data(
name='t_bf16', shape=[size, size], dtype=np.int32 name='t_bf16', shape=[-1, size, size], dtype='int32'
) )
tt_bf16 = layers.data( t_bf16.desc.set_need_check_feed(False)
name='tt_bf16', shape=[size, size], dtype=np.int32 tt_bf16 = paddle.static.data(
name='tt_bf16', shape=[-1, size, size], dtype='int32'
) )
t = layers.data(name='t', shape=[size, size], dtype='float32') tt_bf16.desc.set_need_check_feed(False)
tt = layers.data(name='tt', shape=[size, size], dtype='float32') t = paddle.static.data(
name='t', shape=[-1, size, size], dtype='float32'
)
t.desc.set_need_check_feed(False)
tt = paddle.static.data(
name='tt', shape=[-1, size, size], dtype='float32'
)
tt.desc.set_need_check_feed(False)
ret = paddle.add(t, tt) ret = paddle.add(t, tt)
ret = paddle.multiply(ret, t) ret = paddle.multiply(ret, t)
...@@ -143,8 +151,14 @@ class TestModelCastBF16(unittest.TestCase): ...@@ -143,8 +151,14 @@ class TestModelCastBF16(unittest.TestCase):
) )
with self.static_graph(): with self.static_graph():
t = layers.data(name='t', shape=[size, size], dtype='float32') t = paddle.static.data(
tt = layers.data(name='tt', shape=[size, size], dtype='float32') name='t', shape=[-1, size, size], dtype='float32'
)
t.desc.set_need_check_feed(False)
tt = paddle.static.data(
name='tt', shape=[-1, size, size], dtype='float32'
)
tt.desc.set_need_check_feed(False)
with amp.bf16.bf16_guard(): with amp.bf16.bf16_guard():
ret = paddle.add(t, tt) ret = paddle.add(t, tt)
......
python/paddle/fluid/contrib/tests/test_multi_precision_fp16_train.py
浏览文件 @ 5670644c
...@@ -102,10 +102,10 @@ def train(use_pure_fp16=True, use_nesterov=False, optimizer=""): ...@@ -102,10 +102,10 @@ def train(use_pure_fp16=True, use_nesterov=False, optimizer=""):
train_program.random_seed = 123 train_program.random_seed = 123
startup_prog.random_seed = 456 startup_prog.random_seed = 456
with fluid.program_guard(train_program, startup_prog): with fluid.program_guard(train_program, startup_prog):
images = fluid.layers.data( images = paddle.static.data(
name='pixel', shape=data_shape, dtype='float32' name='pixel', shape=[-1] + data_shape, dtype='float32'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
net = resnet_cifar10(images) net = resnet_cifar10(images)
logits = paddle.static.nn.fc(x=net, size=classdim, activation="softmax") logits = paddle.static.nn.fc(x=net, size=classdim, activation="softmax")
cost = paddle.nn.functional.softmax_with_cross_entropy( cost = paddle.nn.functional.softmax_with_cross_entropy(
...@@ -275,11 +275,11 @@ class TestAmpWithNonIterableDataLoader(unittest.TestCase): ...@@ -275,11 +275,11 @@ class TestAmpWithNonIterableDataLoader(unittest.TestCase):
start_prog = paddle.static.Program() start_prog = paddle.static.Program()
with paddle.static.program_guard(main_prog, start_prog): with paddle.static.program_guard(main_prog, start_prog):
with paddle.fluid.unique_name.guard(): with paddle.fluid.unique_name.guard():
image = fluid.layers.data( image = paddle.static.data(
name='image', shape=[3, 224, 224], dtype='float32' name='image', shape=[-1, 3, 224, 224], dtype='float32'
) )
label = fluid.layers.data( label = paddle.static.data(
name='label', shape=[1], dtype='int64' name='label', shape=[-1, 1], dtype='int64'
) )
py_reader = fluid.io.DataLoader.from_generator( py_reader = fluid.io.DataLoader.from_generator(
feed_list=[image, label], feed_list=[image, label],
......
python/paddle/fluid/contrib/tests/test_weight_decay_extend.py
浏览文件 @ 5670644c
...@@ -134,10 +134,12 @@ class TestWeightDecay(unittest.TestCase): ...@@ -134,10 +134,12 @@ class TestWeightDecay(unittest.TestCase):
startup_prog = fluid.framework.Program() startup_prog = fluid.framework.Program()
with prog_scope_guard(main_prog=main_prog, startup_prog=startup_prog): with prog_scope_guard(main_prog=main_prog, startup_prog=startup_prog):
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
)
label = paddle.static.data(
name="label", shape=[-1, 1], dtype="int64"
) )
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
avg_cost = model(data, label, self.word_dict_len) avg_cost = model(data, label, self.word_dict_len)
AdamW = fluid.contrib.extend_with_decoupled_weight_decay( AdamW = fluid.contrib.extend_with_decoupled_weight_decay(
fluid.optimizer.Adam fluid.optimizer.Adam
...@@ -158,10 +160,12 @@ class TestWeightDecay(unittest.TestCase): ...@@ -158,10 +160,12 @@ class TestWeightDecay(unittest.TestCase):
startup_prog = fluid.framework.Program() startup_prog = fluid.framework.Program()
with prog_scope_guard(main_prog=main_prog, startup_prog=startup_prog): with prog_scope_guard(main_prog=main_prog, startup_prog=startup_prog):
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
)
label = paddle.static.data(
name="label", shape=[-1, 1], dtype="int64"
) )
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
avg_cost = model(data, label, self.word_dict_len) avg_cost = model(data, label, self.word_dict_len)
......
python/paddle/fluid/executor.py
浏览文件 @ 5670644c
...@@ -1862,7 +1862,6 @@ class Executor: ...@@ -1862,7 +1862,6 @@ class Executor:
vardesc = global_block.desc.find_var(varname.encode()) vardesc = global_block.desc.find_var(varname.encode())
varobj = global_block.vars[varname] varobj = global_block.vars[varname]
# Can not check var build by fluid.layers.data(), bucause fluid.layers.data() had not set need_check_feed
if ( if (
vardesc.persistable() == False vardesc.persistable() == False
and vardesc.type() == core.VarDesc.VarType.LOD_TENSOR and vardesc.type() == core.VarDesc.VarType.LOD_TENSOR
......
python/paddle/fluid/framework.py
浏览文件 @ 5670644c
...@@ -6957,9 +6957,10 @@ class Parameter(Variable, metaclass=ParameterMetaClass): ...@@ -6957,9 +6957,10 @@ class Parameter(Variable, metaclass=ParameterMetaClass):
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle
prog = fluid.default_main_program() prog = fluid.default_main_program()
rlt = fluid.layers.data("fake_data", shape=[1,1], dtype='float32') rlt = paddle.static.data("fake_data", shape=[-1,1,1], dtype='float32')
debug_str = prog.to_string(throw_on_error=True, with_details=False) debug_str = prog.to_string(throw_on_error=True, with_details=False)
print(debug_str) print(debug_str)
""" """
......
python/paddle/fluid/incubate/fleet/tests/fleet_deep_ctr.py
浏览文件 @ 5670644c
...@@ -80,26 +80,23 @@ def model(): ...@@ -80,26 +80,23 @@ def model():
train_file_path, train_file_path,
) = ctr_dataset_reader.prepare_data() ) = ctr_dataset_reader.prepare_data()
""" network definition """ """ network definition """
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
datas = [dnn_data, lr_data, label] datas = [dnn_data, lr_data, label]
......
python/paddle/fluid/incubate/fleet/utils/fleet_util.py
浏览文件 @ 5670644c
...@@ -1371,8 +1371,8 @@ class FleetUtil: ...@@ -1371,8 +1371,8 @@ class FleetUtil:
local_total_ins.name) local_total_ins.name)
# below is part of example model # below is part of example model
label = fluid.layers.data(name="click", shape=[-1, 1],\ label = paddle.static.data(name="click", shape=[-1, 1],\
dtype="int64", lod_level=0, append_batch_size=False) dtype="int64", lod_level=0)
emb = my_slot_net(slots, label) # emb can be fc layer of size 1 emb = my_slot_net(slots, label) # emb can be fc layer of size 1
similarity_norm = fluid.layers.sigmoid(paddle.clip(\ similarity_norm = fluid.layers.sigmoid(paddle.clip(\
emb, min=-15.0, max=15.0), name="similarity_norm")\ emb, min=-15.0, max=15.0), name="similarity_norm")\
...@@ -1571,8 +1571,8 @@ class FleetUtil: ...@@ -1571,8 +1571,8 @@ class FleetUtil:
local_total_ins.name) local_total_ins.name)
# below is part of model # below is part of model
label = fluid.layers.data(name="click", shape=[-1, 1],\ label = paddle.static.data(name="click", shape=[-1, 1],\
dtype="int64", lod_level=0, append_batch_size=False) dtype="int64", lod_level=0)
emb = my_slot_net(slots, label) # emb can be fc layer of size 1 emb = my_slot_net(slots, label) # emb can be fc layer of size 1
similarity_norm = fluid.layers.sigmoid(paddle.clip(\ similarity_norm = fluid.layers.sigmoid(paddle.clip(\
emb, min=-15.0, max=15.0), name="similarity_norm")\ emb, min=-15.0, max=15.0), name="similarity_norm")\
......
python/paddle/fluid/incubate/fleet/utils/utils.py
浏览文件 @ 5670644c
...@@ -17,6 +17,7 @@ import sys ...@@ -17,6 +17,7 @@ import sys
import logging import logging
import subprocess import subprocess
import numpy as np import numpy as np
import paddle
from collections import OrderedDict from collections import OrderedDict
import paddle.fluid as fluid import paddle.fluid as fluid
from paddle.fluid import core from paddle.fluid import core
...@@ -172,8 +173,9 @@ def save_var(np_array, var_name, shape_list, dtype, save_path): ...@@ -172,8 +173,9 @@ def save_var(np_array, var_name, shape_list, dtype, save_path):
program = fluid.Program() program = fluid.Program()
place = fluid.CPUPlace() place = fluid.CPUPlace()
exe = fluid.Executor(place) exe = fluid.Executor(place)
shape = list(shape_list)
with fluid.program_guard(program): with fluid.program_guard(program):
d0_data = fluid.layers.data(var_name, shape=shape_list, dtype=dtype) d0_data = paddle.static.data(var_name, shape=shape, dtype=dtype)
append_save_op(program.global_block(), d0_data, save_path) append_save_op(program.global_block(), d0_data, save_path)
exe.run(feed={var_name: np_array}, fetch_list=[]) exe.run(feed={var_name: np_array}, fetch_list=[])
...@@ -183,7 +185,7 @@ def load_var(var_name, shape_list, dtype, save_path): ...@@ -183,7 +185,7 @@ def load_var(var_name, shape_list, dtype, save_path):
place = fluid.CPUPlace() place = fluid.CPUPlace()
exe = fluid.Executor(place) exe = fluid.Executor(place)
with fluid.program_guard(program): with fluid.program_guard(program):
d0_data = fluid.layers.data(var_name, shape=shape_list, dtype=dtype) d0_data = paddle.static.data(var_name, shape=shape_list, dtype=dtype)
append_load_op(program.global_block(), d0_data, save_path) append_load_op(program.global_block(), d0_data, save_path)
outs = exe.run(feed={}, fetch_list=[d0_data]) outs = exe.run(feed={}, fetch_list=[d0_data])
return outs return outs
......
python/paddle/fluid/install_check.py
浏览文件 @ 5670644c
...@@ -103,7 +103,7 @@ def run_check(): ...@@ -103,7 +103,7 @@ def run_check():
with unique_name.guard(): with unique_name.guard():
build_strategy = compiler.BuildStrategy() build_strategy = compiler.BuildStrategy()
build_strategy.enable_inplace = True build_strategy.enable_inplace = True
inp = layers.data(name="inp", shape=[2, 2]) inp = paddle.static.data(name="inp", shape=[-1, 2, 2])
simple_layer = SimpleLayer(input_size=2) simple_layer = SimpleLayer(input_size=2)
out = simple_layer(inp) out = simple_layer(inp)
exe = executor.Executor( exe = executor.Executor(
...@@ -138,9 +138,7 @@ def run_check(): ...@@ -138,9 +138,7 @@ def run_check():
with executor.scope_guard(scope): with executor.scope_guard(scope):
with program_guard(train_prog, startup_prog): with program_guard(train_prog, startup_prog):
with unique_name.guard(): with unique_name.guard():
inp0 = layers.data( inp0 = paddle.static.data(name="inp", shape=[2, 2])
name="inp", shape=[2, 2], append_batch_size=False
)
simple_layer0 = SimpleLayer(input_size=2) simple_layer0 = SimpleLayer(input_size=2)
out0 = simple_layer0(inp0) out0 = simple_layer0(inp0)
param_grads = backward.append_backward( param_grads = backward.append_backward(
......
python/paddle/fluid/io.py
浏览文件 @ 5670644c
...@@ -355,7 +355,7 @@ def save_vars( ...@@ -355,7 +355,7 @@ def save_vars(
main_prog = fluid.Program() main_prog = fluid.Program()
startup_prog = fluid.Program() startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
data = fluid.layers.data(name="img", shape=[64, 784], append_batch_size=False) data = paddle.static.data(name="img", shape=[64, 784])
w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w') w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w')
b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b') b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b')
hidden_w = paddle.matmul(x=data, y=w) hidden_w = paddle.matmul(x=data, y=w)
...@@ -830,7 +830,7 @@ def load_vars( ...@@ -830,7 +830,7 @@ def load_vars(
main_prog = fluid.Program() main_prog = fluid.Program()
startup_prog = fluid.Program() startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
data = fluid.layers.data(name="img", shape=[64, 784], append_batch_size=False) data = paddle.static.data(name="img", shape=[64, 784])
w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w') w = paddle.create_parameter(shape=[784, 200], dtype='float32', name='fc_w')
b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b') b = paddle.create_parameter(shape=[200], dtype='float32', name='fc_b')
hidden_w = paddle.matmul(x=data, y=w) hidden_w = paddle.matmul(x=data, y=w)
...@@ -1598,7 +1598,7 @@ def load_inference_model( ...@@ -1598,7 +1598,7 @@ def load_inference_model(
main_prog = fluid.Program() main_prog = fluid.Program()
startup_prog = fluid.Program() startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
data = fluid.layers.data(name="img", shape=[64, 784], append_batch_size=False) data = paddle.static.data(name="img", shape=[-1, 64, 784])
w = paddle.create_parameter(shape=[784, 200], dtype='float32') w = paddle.create_parameter(shape=[784, 200], dtype='float32')
b = paddle.create_parameter(shape=[200], dtype='float32') b = paddle.create_parameter(shape=[200], dtype='float32')
hidden_w = paddle.matmul(x=data, y=w) hidden_w = paddle.matmul(x=data, y=w)
......
python/paddle/fluid/layers/control_flow.py
浏览文件 @ 5670644c
...@@ -466,7 +466,7 @@ class StaticRNN: ...@@ -466,7 +466,7 @@ class StaticRNN:
is_sparse=False) is_sparse=False)
# transform batch size to dim 1 # transform batch size to dim 1
x_emb = paddle.transpose(x_emb, perm=[1, 0, 2]) x_emb = paddle.transpose(x_emb, perm=[1, 0, 2])
boot_memory = fluid.layers.data(name='boot', shape=[hidden_size], dtype='float32', lod_level=1) boot_memory = paddle.static.data(name='boot', shape=[-1, hidden_size], dtype='float32', lod_level=1)
rnn = fluid.layers.StaticRNN() rnn = fluid.layers.StaticRNN()
with rnn.step(): with rnn.step():
# mark created x_emb as input, each step process a word # mark created x_emb as input, each step process a word
......
python/paddle/fluid/layers/io.py
浏览文件 @ 5670644c
...@@ -41,108 +41,7 @@ from ..framework import ( ...@@ -41,108 +41,7 @@ from ..framework import (
_set_expected_place, _set_expected_place,
) )
__all__ = [ __all__ = []
'data',
]
@static_only
def data(
name,
shape,
append_batch_size=True,
dtype='float32',
lod_level=0,
type=core.VarDesc.VarType.LOD_TENSOR,
stop_gradient=True,
):
"""
**Data Layer**
This operator creates the global variable. The global variables can be
accessed by all the following operators in the graph.
Note:
:code:`paddle.fluid.layers.data` is deprecated as it will be removed in
a later version. Please use :code:`paddle.fluid.data` .
This :code:`paddle.fluid.layers.data` set shape and dtype at compile
time but does NOT check the shape or the dtype of fed data, the
:code:`paddle.fluid.data` checks the shape and the dtype of data fed
by Executor or ParallelExecutor during run time.
To feed variable size inputs, users can feed variable size inputs
directly to this :code:`paddle.fluid.layers.data` and PaddlePaddle will
fit the size accordingly. Or set -1 on the variable dimension when using
:code:`paddle.fluid.data` .
The default :code:`stop_gradient` attribute of the Variable created by
this API is true, which means the gradient won't be passed backward
through the data Varaible. Set :code:`var.stop_gradient = False` If
user would like to pass backward gradient.
Args:
name(str): The name/alias of the variable, see :ref:`api_guide_Name`
for more details.
shape(list|tuple): Tuple declaring the shape. If :code:`append_batch_size` is
True and there is no -1 inside :code:`shape`, it should be
considered as the shape of the each sample. Otherwise, it should
be considered as the shape of the batched data.
append_batch_size(bool):
1. If true, it prepends -1 to the shape.
For example if shape=[1], the resulting shape is [-1, 1]. This will
be useful to set different batch size at run time.
2. If shape contains -1, such as shape=[1, -1].
append_batch_size will be enforced to be be False (ineffective)
because PaddlePaddle cannot set more than 1 unknown number on the
shape.
dtype(np.dtype|VarType|str): The type of the data. Supported dtype: bool,
float16, float32, float64, int8, int16, int32, int64, uint8.
type(VarType): The output type. Supported dtype: VarType.LOD_TENSOR,
VarType.SELECTED_ROWS, VarType.NCCL_ID. Default: VarType.LOD_TENSOR.
lod_level(int): The LoD Level. 0 means the input data is not a sequence.
Default: 0.
stop_gradient(bool): A boolean that mentions whether gradient should flow.
Default: True.
Returns:
The global variable that gives access to the data.
Return Type:
Variable
Examples:
.. code-block:: python
import paddle.fluid as fluid
data = fluid.layers.data(name='x', shape=[784], dtype='float32')
"""
helper = LayerHelper('data', **locals())
check_type(name, 'name', (bytes, str), 'data')
check_type(shape, 'shape', (list, tuple), 'data')
shape = list(shape)
for i in range(len(shape)):
if shape[i] is None:
shape[i] = -1
append_batch_size = False
elif shape[i] < 0:
append_batch_size = False
if append_batch_size:
shape = [-1] + shape # append batch size as -1
data_var = helper.create_global_variable(
name=name,
shape=shape,
dtype=dtype,
type=type,
stop_gradient=stop_gradient,
lod_level=lod_level,
is_data=True,
)
return data_var
class BlockGuardServ(BlockGuard): class BlockGuardServ(BlockGuard):
...@@ -189,11 +88,10 @@ class ListenAndServ: ...@@ -189,11 +88,10 @@ class ListenAndServ:
serv = layers.ListenAndServ( serv = layers.ListenAndServ(
"127.0.0.1:6170", ["X"], optimizer_mode=False) "127.0.0.1:6170", ["X"], optimizer_mode=False)
with serv.do(): with serv.do():
x = layers.data( x = paddle.static.data(
shape=[32, 32], shape=[32, 32],
dtype='float32', dtype='float32',
name="X", name="X")
append_batch_size=False)
fluid.initializer.Constant(value=1.0)(x, main.global_block()) fluid.initializer.Constant(value=1.0)(x, main.global_block())
paddle.scale(x=x, scale=10.0, out=out_var) paddle.scale(x=x, scale=10.0, out=out_var)
......
python/paddle/fluid/layers/nn.py
浏览文件 @ 5670644c
...@@ -329,7 +329,7 @@ def _pull_sparse( ...@@ -329,7 +329,7 @@ def _pull_sparse(
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
data = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data = paddle.static.data(name='sequence', shape=[-1, 1], dtype='int64', lod_level=1)
emb = fluid.layers.nn._pull_sparse( emb = fluid.layers.nn._pull_sparse(
input=data, size=11, table_id=0, accessor_class="DownpourCtrAccessor") input=data, size=11, table_id=0, accessor_class="DownpourCtrAccessor")
""" """
...@@ -403,7 +403,7 @@ def _pull_sparse_v2( ...@@ -403,7 +403,7 @@ def _pull_sparse_v2(
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
data = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data = paddle.static.data(name='sequence', shape=[-1, 1], dtype='int64', lod_level=1)
emb = fluid.layers.nn._pull_sparse_v2( emb = fluid.layers.nn._pull_sparse_v2(
input=data, size=11, table_id=0, accessor_class="DownpourCtrAccessor") input=data, size=11, table_id=0, accessor_class="DownpourCtrAccessor")
""" """
...@@ -464,9 +464,9 @@ def _pull_gpups_sparse( ...@@ -464,9 +464,9 @@ def _pull_gpups_sparse(
import paddle.fluid as fluid import paddle.fluid as fluid
slots = [] slots = []
data_1 = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data_1 = paddle.static.data(name='sequence', shape=[-1,1], dtype='int64', lod_level=1)
slots.append(data_1) slots.append(data_1)
data_2 = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data_2 = paddle.static.data(name='sequence', shape=[-1,1], dtype='int64', lod_level=1)
slots.append(data_2) slots.append(data_2)
embs = fluid.layers.pull_gpups_sparse(input=slots, size=[11, 35]) embs = fluid.layers.pull_gpups_sparse(input=slots, size=[11, 35])
""" """
...@@ -526,7 +526,7 @@ def _pull_box_sparse( ...@@ -526,7 +526,7 @@ def _pull_box_sparse(
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
data = fluid.layers.data(name='sequence', shape=[1], dtype='int64', lod_level=1) data = paddle.static.data(name='sequence', shape=[-1,1], dtype='int64', lod_level=1)
emb = fluid.layers.pull_box_sparse(input=data, size=[11]) emb = fluid.layers.pull_box_sparse(input=data, size=[11])
""" """
helper = LayerHelper('pull_box_sparse', **locals()) helper = LayerHelper('pull_box_sparse', **locals())
...@@ -711,7 +711,7 @@ def unsqueeze(input, axes, name=None): ...@@ -711,7 +711,7 @@ def unsqueeze(input, axes, name=None):
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[5, 10]) x = paddle.static.data(name='x', shape=[-1, 5, 10], dtype="float32")
y = fluid.layers.unsqueeze(input=x, axes=[1]) y = fluid.layers.unsqueeze(input=x, axes=[1])
""" """
......
python/paddle/fluid/optimizer.py
浏览文件 @ 5670644c
...@@ -1431,8 +1431,8 @@ class SGDOptimizer(Optimizer): ...@@ -1431,8 +1431,8 @@ class SGDOptimizer(Optimizer):
place = fluid.CPUPlace() place = fluid.CPUPlace()
main = fluid.Program() main = fluid.Program()
with fluid.program_guard(main): with fluid.program_guard(main):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
...@@ -1623,8 +1623,8 @@ class MomentumOptimizer(Optimizer): ...@@ -1623,8 +1623,8 @@ class MomentumOptimizer(Optimizer):
place = fluid.CPUPlace() place = fluid.CPUPlace()
main = fluid.Program() main = fluid.Program()
with fluid.program_guard(main): with fluid.program_guard(main):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
...@@ -1772,8 +1772,8 @@ class LarsMomentumOptimizer(Optimizer): ...@@ -1772,8 +1772,8 @@ class LarsMomentumOptimizer(Optimizer):
paddle.enable_static() paddle.enable_static()
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32) np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
inp = fluid.layers.data( inp = paddle.static.data(
name="inp", shape=[2, 2], append_batch_size=False) name="inp", shape=[2, 2], dtype='float32')
out = paddle.static.nn.fc(inp, size=3) out = paddle.static.nn.fc(inp, size=3)
out = paddle.sum(out) out = paddle.sum(out)
optimizer = fluid.optimizer.LarsMomentumOptimizer(learning_rate=0.001, momentum=0.9) optimizer = fluid.optimizer.LarsMomentumOptimizer(learning_rate=0.001, momentum=0.9)
...@@ -2764,7 +2764,7 @@ class DpsgdOptimizer(Optimizer): ...@@ -2764,7 +2764,7 @@ class DpsgdOptimizer(Optimizer):
train_program = fluid.Program() train_program = fluid.Program()
startup_program = fluid.Program() startup_program = fluid.Program()
with fluid.program_guard(train_program, startup_program): with fluid.program_guard(train_program, startup_program):
data = fluid.layers.data(name='X', shape=[1], dtype='float32') data = paddle.static.data(name='X', shape=[-1,1], dtype='float32')
hidden = paddle.static.nn.fc(x=data, size=10) hidden = paddle.static.nn.fc(x=data, size=10)
loss = paddle.mean(hidden) loss = paddle.mean(hidden)
optimizer = fluid.optimizer.Dpsgd(learning_rate=0.01, clip=10.0, batch_size=16.0, sigma=1.0) optimizer = fluid.optimizer.Dpsgd(learning_rate=0.01, clip=10.0, batch_size=16.0, sigma=1.0)
...@@ -3217,8 +3217,8 @@ class RMSPropOptimizer(Optimizer): ...@@ -3217,8 +3217,8 @@ class RMSPropOptimizer(Optimizer):
place = fluid.CPUPlace() place = fluid.CPUPlace()
main = fluid.Program() main = fluid.Program()
with fluid.program_guard(main): with fluid.program_guard(main):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
...@@ -3415,8 +3415,8 @@ class FtrlOptimizer(Optimizer): ...@@ -3415,8 +3415,8 @@ class FtrlOptimizer(Optimizer):
place = fluid.CPUPlace() place = fluid.CPUPlace()
main = fluid.Program() main = fluid.Program()
with fluid.program_guard(main): with fluid.program_guard(main):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
...@@ -4354,11 +4354,12 @@ class PipelineOptimizer: ...@@ -4354,11 +4354,12 @@ class PipelineOptimizer:
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers import paddle.fluid.layers as layers
import numpy as np
paddle.enable_static() paddle.enable_static()
with fluid.device_guard("gpu:0"): with fluid.device_guard("gpu:0"):
x = fluid.layers.data(name='x', shape=[1], dtype='int64', lod_level=0) x = paddle.static.data(name='x', shape=[-1, 1], dtype='int64', lod_level=0)
y = fluid.layers.data(name='y', shape=[1], dtype='int64', lod_level=0) y = paddle.static.data(name='y', shape=[-1, 1], dtype='int64', lod_level=0)
data_loader = fluid.io.DataLoader.from_generator( data_loader = fluid.io.DataLoader.from_generator(
feed_list=[x, y], feed_list=[x, y],
capacity=64, capacity=64,
...@@ -6332,8 +6333,8 @@ class RecomputeOptimizer(Optimizer): ...@@ -6332,8 +6333,8 @@ class RecomputeOptimizer(Optimizer):
) )
sum_cost = paddle.mean(cost) sum_cost = paddle.mean(cost)
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
sgd = fluid.optimizer.Adam(learning_rate=0.01) sgd = fluid.optimizer.Adam(learning_rate=0.01)
...@@ -6410,8 +6411,8 @@ class RecomputeOptimizer(Optimizer): ...@@ -6410,8 +6411,8 @@ class RecomputeOptimizer(Optimizer):
sum_cost = paddle.mean(cost) sum_cost = paddle.mean(cost)
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
print("Finished FF") print("Finished FF")
...@@ -6458,8 +6459,8 @@ class RecomputeOptimizer(Optimizer): ...@@ -6458,8 +6459,8 @@ class RecomputeOptimizer(Optimizer):
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
print("Finished FF") print("Finished FF")
...@@ -6952,8 +6953,8 @@ class RecomputeOptimizer(Optimizer): ...@@ -6952,8 +6953,8 @@ class RecomputeOptimizer(Optimizer):
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
print("Finished FF") print("Finished FF")
...@@ -7033,8 +7034,8 @@ class RecomputeOptimizer(Optimizer): ...@@ -7033,8 +7034,8 @@ class RecomputeOptimizer(Optimizer):
sum_cost = paddle.mean(cost) sum_cost = paddle.mean(cost)
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
print("Finished FF") print("Finished FF")
...@@ -7120,8 +7121,8 @@ class LookaheadOptimizer: ...@@ -7120,8 +7121,8 @@ class LookaheadOptimizer:
paddle.enable_static() paddle.enable_static()
x = fluid.layers.data(name='x', shape=[2], dtype='float32') x = paddle.static.data(name='x', shape=[-1,2], dtype='float32')
label = fluid.layers.data(name="label", shape=[1], dtype="int64") label = paddle.static.data(name="label", shape=[-1,1], dtype="int64")
y = paddle.static.nn.fc(x=[x], size=2, activation="softmax") y = paddle.static.nn.fc(x=[x], size=2, activation="softmax")
loss = paddle.nn.functional.cross_entropy( loss = paddle.nn.functional.cross_entropy(
input=y, label=label, input=y, label=label,
...@@ -7311,8 +7312,8 @@ class GradientMergeOptimizer: ...@@ -7311,8 +7312,8 @@ class GradientMergeOptimizer:
sum_cost = paddle.mean(cost) sum_cost = paddle.mean(cost)
return sum_cost, fc_1, prediction return sum_cost, fc_1, prediction
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1,32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1,1], dtype='int64')
cost, fc_1, pred = mlp(input_x, input_y) cost, fc_1, pred = mlp(input_x, input_y)
sgd = fluid.optimizer.Adam(learning_rate=0.01) sgd = fluid.optimizer.Adam(learning_rate=0.01)
sgd = fluid.optimizer.GradientMergeOptimizer(sgd, k_steps=4, avg=True) sgd = fluid.optimizer.GradientMergeOptimizer(sgd, k_steps=4, avg=True)
......
python/paddle/fluid/reader.py
浏览文件 @ 5670644c
...@@ -1643,7 +1643,7 @@ class PyReader(DataLoaderBase): ...@@ -1643,7 +1643,7 @@ class PyReader(DataLoaderBase):
Args: Args:
feed_list (list(Variable)|tuple(Variable)): feed variable list. 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:`paddle.static.data()`.
capacity (int): capacity of the queue maintained in PyReader. capacity (int): capacity of the queue maintained in PyReader.
The unit is batch number. Set larger capacity if your reader The unit is batch number. Set larger capacity if your reader
is fast. is fast.
......
python/paddle/fluid/regularizer.py
浏览文件 @ 5670644c
...@@ -74,8 +74,8 @@ class L2DecayRegularizer(WeightDecayRegularizer): ...@@ -74,8 +74,8 @@ class L2DecayRegularizer(WeightDecayRegularizer):
main_prog = fluid.Program() main_prog = fluid.Program()
startup_prog = fluid.Program() startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
data = fluid.layers.data(name='image', shape=[3, 28, 28], dtype='float32') data = paddle.static.data(name='image', shape=[-1, 3, 28, 28], dtype='float32')
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
hidden = paddle.static.nn.fc(x=data, size=128, activation='relu') hidden = paddle.static.nn.fc(x=data, size=128, activation='relu')
prediction = paddle.static.nn.fc(x=hidden, size=10, activation='softmax') prediction = paddle.static.nn.fc(x=hidden, size=10, activation='softmax')
loss = paddle.nn.functional.cross_entropy( loss = paddle.nn.functional.cross_entropy(
...@@ -193,8 +193,8 @@ class L1DecayRegularizer(WeightDecayRegularizer): ...@@ -193,8 +193,8 @@ class L1DecayRegularizer(WeightDecayRegularizer):
main_prog = fluid.Program() main_prog = fluid.Program()
startup_prog = fluid.Program() startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
data = fluid.layers.data(name='image', shape=[3, 28, 28], dtype='float32') data = paddle.static.data(name='image', shape=[-1, 3, 28, 28], dtype='float32')
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
hidden = paddle.static.nn.fc(x=data, size=128, activation='relu') hidden = paddle.static.nn.fc(x=data, size=128, activation='relu')
prediction = paddle.static.nn.fc(x=hidden, size=10, activation='softmax') prediction = paddle.static.nn.fc(x=hidden, size=10, activation='softmax')
loss = paddle.nn.functional.cross_entropy( loss = paddle.nn.functional.cross_entropy(
......
python/paddle/fluid/tests/book/notest_understand_sentiment.py
浏览文件 @ 5670644c
...@@ -68,10 +68,10 @@ def train( ...@@ -68,10 +68,10 @@ def train(
dict_dim = len(word_dict) dict_dim = len(word_dict)
class_dim = 2 class_dim = 2
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
) )
label = fluid.layers.data(name="label", shape=[1], dtype="int64") label = paddle.static.data(name="label", shape=[-1, 1], dtype="int64")
if not parallel: if not parallel:
cost, acc_out, prediction = net_method( cost, acc_out, prediction = net_method(
......
python/paddle/fluid/tests/book/test_fit_a_line.py
浏览文件 @ 5670644c
...@@ -49,8 +49,10 @@ def convert_float_to_uint16(in_list): ...@@ -49,8 +49,10 @@ def convert_float_to_uint16(in_list):
def train(use_cuda, save_dirname, is_local, use_bf16, pure_bf16): def train(use_cuda, save_dirname, is_local, use_bf16, pure_bf16):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') x.desc.set_need_check_feed(False)
y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y.desc.set_need_check_feed(False)
if use_bf16: if use_bf16:
if not pure_bf16: if not pure_bf16:
......
python/paddle/fluid/tests/book/test_image_classification.py
浏览文件 @ 5670644c
...@@ -104,8 +104,10 @@ def train(net_type, use_cuda, save_dirname, is_local): ...@@ -104,8 +104,10 @@ def train(net_type, use_cuda, save_dirname, is_local):
classdim = 10 classdim = 10
data_shape = [3, 32, 32] data_shape = [3, 32, 32]
images = fluid.layers.data(name='pixel', shape=data_shape, dtype='float32') images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1] + data_shape, dtype='float32'
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
if net_type == "vgg": if net_type == "vgg":
print("train vgg net") print("train vgg net")
......
python/paddle/fluid/tests/book/test_recognize_digits.py
浏览文件 @ 5670644c
...@@ -77,8 +77,8 @@ def train( ...@@ -77,8 +77,8 @@ def train(
): ):
if use_cuda and not fluid.core.is_compiled_with_cuda(): if use_cuda and not fluid.core.is_compiled_with_cuda():
return return
img = fluid.layers.data(name='img', shape=[1, 28, 28], dtype='float32') img = paddle.static.data(name='img', shape=[-1, 1, 28, 28], dtype='float32')
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
if nn_type == 'mlp': if nn_type == 'mlp':
net_conf = mlp net_conf = mlp
......
python/paddle/fluid/tests/book/test_recommender_system.py
浏览文件 @ 5670644c
...@@ -40,7 +40,7 @@ def get_usr_combined_features(): ...@@ -40,7 +40,7 @@ def get_usr_combined_features():
USR_DICT_SIZE = paddle.dataset.movielens.max_user_id() + 1 USR_DICT_SIZE = paddle.dataset.movielens.max_user_id() + 1
uid = layers.data(name='user_id', shape=[1], dtype='int64') uid = paddle.static.data(name='user_id', shape=[-1, 1], dtype='int64')
usr_emb = layers.embedding( usr_emb = layers.embedding(
input=uid, input=uid,
...@@ -54,7 +54,9 @@ def get_usr_combined_features(): ...@@ -54,7 +54,9 @@ def get_usr_combined_features():
USR_GENDER_DICT_SIZE = 2 USR_GENDER_DICT_SIZE = 2
usr_gender_id = layers.data(name='gender_id', shape=[1], dtype='int64') usr_gender_id = paddle.static.data(
name='gender_id', shape=[-1, 1], dtype='int64'
)
usr_gender_emb = layers.embedding( usr_gender_emb = layers.embedding(
input=usr_gender_id, input=usr_gender_id,
...@@ -66,7 +68,7 @@ def get_usr_combined_features(): ...@@ -66,7 +68,7 @@ def get_usr_combined_features():
usr_gender_fc = paddle.static.nn.fc(x=usr_gender_emb, size=16) usr_gender_fc = paddle.static.nn.fc(x=usr_gender_emb, size=16)
USR_AGE_DICT_SIZE = len(paddle.dataset.movielens.age_table) USR_AGE_DICT_SIZE = len(paddle.dataset.movielens.age_table)
usr_age_id = layers.data(name='age_id', shape=[1], dtype="int64") usr_age_id = paddle.static.data(name='age_id', shape=[-1, 1], dtype="int64")
usr_age_emb = layers.embedding( usr_age_emb = layers.embedding(
input=usr_age_id, input=usr_age_id,
...@@ -78,7 +80,7 @@ def get_usr_combined_features(): ...@@ -78,7 +80,7 @@ def get_usr_combined_features():
usr_age_fc = paddle.static.nn.fc(x=usr_age_emb, size=16) usr_age_fc = paddle.static.nn.fc(x=usr_age_emb, size=16)
USR_JOB_DICT_SIZE = paddle.dataset.movielens.max_job_id() + 1 USR_JOB_DICT_SIZE = paddle.dataset.movielens.max_job_id() + 1
usr_job_id = layers.data(name='job_id', shape=[1], dtype="int64") usr_job_id = paddle.static.data(name='job_id', shape=[-1, 1], dtype="int64")
usr_job_emb = layers.embedding( usr_job_emb = layers.embedding(
input=usr_job_id, input=usr_job_id,
...@@ -104,7 +106,7 @@ def get_mov_combined_features(): ...@@ -104,7 +106,7 @@ def get_mov_combined_features():
MOV_DICT_SIZE = paddle.dataset.movielens.max_movie_id() + 1 MOV_DICT_SIZE = paddle.dataset.movielens.max_movie_id() + 1
mov_id = layers.data(name='movie_id', shape=[1], dtype='int64') mov_id = paddle.static.data(name='movie_id', shape=[-1, 1], dtype='int64')
mov_emb = layers.embedding( mov_emb = layers.embedding(
input=mov_id, input=mov_id,
...@@ -118,8 +120,8 @@ def get_mov_combined_features(): ...@@ -118,8 +120,8 @@ def get_mov_combined_features():
CATEGORY_DICT_SIZE = len(paddle.dataset.movielens.movie_categories()) CATEGORY_DICT_SIZE = len(paddle.dataset.movielens.movie_categories())
category_id = layers.data( category_id = paddle.static.data(
name='category_id', shape=[1], dtype='int64', lod_level=1 name='category_id', shape=[-1, 1], dtype='int64', lod_level=1
) )
mov_categories_emb = layers.embedding( mov_categories_emb = layers.embedding(
...@@ -132,8 +134,8 @@ def get_mov_combined_features(): ...@@ -132,8 +134,8 @@ def get_mov_combined_features():
MOV_TITLE_DICT_SIZE = len(paddle.dataset.movielens.get_movie_title_dict()) MOV_TITLE_DICT_SIZE = len(paddle.dataset.movielens.get_movie_title_dict())
mov_title_id = layers.data( mov_title_id = paddle.static.data(
name='movie_title', shape=[1], dtype='int64', lod_level=1 name='movie_title', shape=[-1, 1], dtype='int64', lod_level=1
) )
mov_title_emb = layers.embedding( mov_title_emb = layers.embedding(
...@@ -170,7 +172,7 @@ def model(): ...@@ -170,7 +172,7 @@ def model():
) )
scale_infer = paddle.scale(x=inference, scale=5.0) scale_infer = paddle.scale(x=inference, scale=5.0)
label = layers.data(name='score', shape=[1], dtype='float32') label = paddle.static.data(name='score', shape=[-1, 1], dtype='float32')
square_cost = paddle.nn.functional.square_error_cost( square_cost = paddle.nn.functional.square_error_cost(
input=scale_infer, label=label input=scale_infer, label=label
) )
......
python/paddle/fluid/tests/book/test_word2vec_book.py
浏览文件 @ 5670644c
...@@ -108,11 +108,13 @@ def train( ...@@ -108,11 +108,13 @@ def train(
word_dict = paddle.dataset.imikolov.build_dict() word_dict = paddle.dataset.imikolov.build_dict()
dict_size = len(word_dict) dict_size = len(word_dict)
first_word = fluid.layers.data(name='firstw', shape=[1], dtype='int64') first_word = paddle.static.data(name='firstw', shape=[-1, 1], dtype='int64')
second_word = fluid.layers.data(name='secondw', shape=[1], dtype='int64') second_word = paddle.static.data(
third_word = fluid.layers.data(name='thirdw', shape=[1], dtype='int64') name='secondw', shape=[-1, 1], dtype='int64'
forth_word = fluid.layers.data(name='forthw', shape=[1], dtype='int64') )
next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64') third_word = paddle.static.data(name='thirdw', shape=[-1, 1], dtype='int64')
forth_word = paddle.static.data(name='forthw', shape=[-1, 1], dtype='int64')
next_word = paddle.static.data(name='nextw', shape=[-1, 1], dtype='int64')
if not is_parallel: if not is_parallel:
avg_cost, predict_word = __network__( avg_cost, predict_word = __network__(
......
python/paddle/fluid/tests/test_data_feeder.py
浏览文件 @ 5670644c
...@@ -22,8 +22,8 @@ paddle.enable_static() ...@@ -22,8 +22,8 @@ paddle.enable_static()
class TestDataFeeder(unittest.TestCase): class TestDataFeeder(unittest.TestCase):
def test_lod_level_0_converter(self): def test_lod_level_0_converter(self):
img = fluid.layers.data(name='image', shape=[1, 28, 28]) img = paddle.static.data(name='image', shape=[-1, 1, 28, 28])
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
feeder = fluid.DataFeeder([img, label], fluid.CPUPlace()) feeder = fluid.DataFeeder([img, label], fluid.CPUPlace())
result = feeder.feed([([0] * 784, [9]), ([1] * 784, [1])]) result = feeder.feed([([0] * 784, [9]), ([1] * 784, [1])])
...@@ -41,10 +41,10 @@ class TestDataFeeder(unittest.TestCase): ...@@ -41,10 +41,10 @@ class TestDataFeeder(unittest.TestCase):
def test_lod_level_1_converter(self): def test_lod_level_1_converter(self):
# lod_level = 1 # lod_level = 1
# each sentence has a different number of words # each sentence has a different number of words
sentences = fluid.layers.data( sentences = paddle.static.data(
name='sentences', shape=[1], dtype='int64', lod_level=1 name='sentences', shape=[-1, 1], dtype='int64', lod_level=1
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
feeder = fluid.DataFeeder([sentences, label], fluid.CPUPlace()) feeder = fluid.DataFeeder([sentences, label], fluid.CPUPlace())
# lod = [[0, 3, 5, 9]] # lod = [[0, 3, 5, 9]]
...@@ -64,10 +64,10 @@ class TestDataFeeder(unittest.TestCase): ...@@ -64,10 +64,10 @@ class TestDataFeeder(unittest.TestCase):
def test_lod_level_2_converter(self): def test_lod_level_2_converter(self):
# lod_level = 2 # lod_level = 2
# paragraphs -> sentences -> words # paragraphs -> sentences -> words
paragraphs = fluid.layers.data( paragraphs = paddle.static.data(
name='paragraphs', shape=[1], dtype='int64', lod_level=2 name='paragraphs', shape=[-1, 1], dtype='int64', lod_level=2
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
feeder = fluid.DataFeeder([paragraphs, label], fluid.CPUPlace()) feeder = fluid.DataFeeder([paragraphs, label], fluid.CPUPlace())
# lod = [[0, 2, 3], [0, 3, 5, 9]] # lod = [[0, 2, 3], [0, 3, 5, 9]]
......
python/paddle/fluid/tests/test_detection.py
浏览文件 @ 5670644c
...@@ -20,7 +20,6 @@ from unittests.test_imperative_base import new_program_scope ...@@ -20,7 +20,6 @@ from unittests.test_imperative_base import new_program_scope
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
from paddle.fluid.dygraph import base from paddle.fluid.dygraph import base
from paddle.fluid.framework import Program, program_guard from paddle.fluid.framework import Program, program_guard
...@@ -154,10 +153,12 @@ class TestMulticlassNMS2(unittest.TestCase): ...@@ -154,10 +153,12 @@ class TestMulticlassNMS2(unittest.TestCase):
def test_multiclass_nms2(self): def test_multiclass_nms2(self):
program = Program() program = Program()
with program_guard(program): with program_guard(program):
bboxes = layers.data( bboxes = paddle.static.data(
name='bboxes', shape=[-1, 10, 4], dtype='float32' name='bboxes', shape=[-1, 10, 4], dtype='float32'
) )
scores = layers.data(name='scores', shape=[-1, 10], dtype='float32') scores = paddle.static.data(
name='scores', shape=[-1, 10], dtype='float32'
)
output = fluid.contrib.multiclass_nms2( output = fluid.contrib.multiclass_nms2(
bboxes, scores, 0.3, 400, 200, 0.7 bboxes, scores, 0.3, 400, 200, 0.7
) )
......
python/paddle/fluid/tests/test_error_clip.py
浏览文件 @ 5670644c
...@@ -23,13 +23,13 @@ paddle.enable_static() ...@@ -23,13 +23,13 @@ paddle.enable_static()
prog = fluid.framework.Program() prog = fluid.framework.Program()
with fluid.program_guard(main_program=prog): with fluid.program_guard(main_program=prog):
image = fluid.layers.data(name='x', shape=[784], dtype='float32') image = paddle.static.data(name='x', shape=[-1, 784], dtype='float32')
hidden1 = paddle.static.nn.fc(x=image, size=128, activation='relu') hidden1 = paddle.static.nn.fc(x=image, size=128, activation='relu')
hidden2 = paddle.static.nn.fc(x=hidden1, size=64, activation='relu') hidden2 = paddle.static.nn.fc(x=hidden1, size=64, activation='relu')
predict = paddle.static.nn.fc(x=hidden2, size=10, activation='softmax') predict = paddle.static.nn.fc(x=hidden2, size=10, activation='softmax')
label = fluid.layers.data(name='y', shape=[1], dtype='int64') label = paddle.static.data(name='y', shape=[-1, 1], dtype='int64')
cost = paddle.nn.functional.cross_entropy( cost = paddle.nn.functional.cross_entropy(
input=predict, label=label, reduction='none', use_softmax=False input=predict, label=label, reduction='none', use_softmax=False
......
python/paddle/fluid/tests/unittests/check_nan_inf_base.py
浏览文件 @ 5670644c
...@@ -46,8 +46,8 @@ def generator(): ...@@ -46,8 +46,8 @@ def generator():
def net(): def net():
x = fluid.layers.data(name="x", shape=[3], dtype='float32') x = paddle.static.data(name="x", shape=[-1, 3], dtype='float32')
y = fluid.layers.data(name="y", shape=[1], dtype='int64') y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
# test int64 value # test int64 value
zero = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0) zero = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
......
python/paddle/fluid/tests/unittests/collective/collective_allgather_api.py
浏览文件 @ 5670644c
...@@ -20,7 +20,6 @@ import test_collective_api_base as test_base ...@@ -20,7 +20,6 @@ import test_collective_api_base as test_base
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -33,7 +32,9 @@ class TestCollectiveAllgatherAPI(test_base.TestCollectiveAPIRunnerBase): ...@@ -33,7 +32,9 @@ class TestCollectiveAllgatherAPI(test_base.TestCollectiveAPIRunnerBase):
dtype = "float32" if dtype is None else dtype dtype = "float32" if dtype is None else dtype
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tensor_list = [] tensor_list = []
tindata = layers.data(name="tindata", shape=[10, 1000], dtype=dtype) tindata = paddle.static.data(
name="tindata", shape=[-1, 10, 1000], dtype=dtype
)
paddle.distributed.all_gather(tensor_list, tindata) paddle.distributed.all_gather(tensor_list, tindata)
return tensor_list return tensor_list
......
python/paddle/fluid/tests/unittests/collective/collective_allreduce_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,8 +26,8 @@ class TestCollectiveAllreduceAPI(TestCollectiveAPIRunnerBase): ...@@ -27,8 +26,8 @@ class TestCollectiveAllreduceAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
paddle.distributed.all_reduce(tindata) paddle.distributed.all_reduce(tindata)
return [tindata] return [tindata]
......
python/paddle/fluid/tests/unittests/collective/collective_allreduce_new_group_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,8 +26,8 @@ class TestCollectiveAllreduceNewGroupAPI(TestCollectiveAPIRunnerBase): ...@@ -27,8 +26,8 @@ class TestCollectiveAllreduceNewGroupAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[1, 10, 1000], dtype='float32'
) )
gp = paddle.distributed.new_group([0, 1]) gp = paddle.distributed.new_group([0, 1])
paddle.distributed.all_reduce(tindata, group=gp, sync_op=True) paddle.distributed.all_reduce(tindata, group=gp, sync_op=True)
......
python/paddle/fluid/tests/unittests/collective/collective_allreduce_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -29,9 +28,10 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase): ...@@ -29,9 +28,10 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program): def get_model(self, main_prog, startup_program):
ring_id = 0 ring_id = 0
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofallreduce", name="outofallreduce",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_allreduce_op_wait.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -29,9 +28,10 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase): ...@@ -29,9 +28,10 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program): def get_model(self, main_prog, startup_program):
ring_id = 0 ring_id = 0
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofallreduce", name="outofallreduce",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_alltoall_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,9 +26,10 @@ class TestCollectiveAllToAllAPI(TestCollectiveAPIRunnerBase): ...@@ -27,9 +26,10 @@ class TestCollectiveAllToAllAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
tindata = paddle.split(tindata, 2, axis=0) tindata = paddle.split(tindata, 2, axis=0)
tout_data = [] tout_data = []
paddle.distributed.alltoall(tindata, tout_data) paddle.distributed.alltoall(tindata, tout_data)
......
python/paddle/fluid/tests/unittests/collective/collective_broadcast_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,9 +26,10 @@ class TestCollectiveBroadcastAPI(TestCollectiveAPIRunnerBase): ...@@ -27,9 +26,10 @@ class TestCollectiveBroadcastAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
paddle.distributed.broadcast(tindata, src=1) paddle.distributed.broadcast(tindata, src=1)
return [tindata] return [tindata]
......
python/paddle/fluid/tests/unittests/collective/collective_broadcast_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveBroadcast(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveBroadcast(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
rootid = 1 rootid = 1
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofbroadcast", name="outofbroadcast",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_concat_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveConcat(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveConcat(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofconcat", name="outofconcat",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_identity_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveIdentity(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveIdentity(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofgather", name="outofgather",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_reduce_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,9 +26,10 @@ class TestCollectiveReduceAPI(TestCollectiveAPIRunnerBase): ...@@ -27,9 +26,10 @@ class TestCollectiveReduceAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
paddle.distributed.reduce(tindata, dst=0) paddle.distributed.reduce(tindata, dst=0)
return [tindata] return [tindata]
......
python/paddle/fluid/tests/unittests/collective/collective_reduce_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveReduce(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveReduce(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
rootid = 1 rootid = 1
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofreduce", name="outofreduce",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_reduce_op_calc_stream.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,11 @@ class TestCollectiveReduce(TestCollectiveRunnerBase): ...@@ -30,9 +29,11 @@ class TestCollectiveReduce(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
rootid = 1 rootid = 1
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofreduce", name="outofreduce",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_scatter_api.py
浏览文件 @ 5670644c
...@@ -27,11 +27,10 @@ class TestCollectiveScatterAPI(TestCollectiveAPIRunnerBase): ...@@ -27,11 +27,10 @@ class TestCollectiveScatterAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", name="tindata",
shape=[10, 1000], shape=[10, 1000],
dtype='float32', dtype='float32',
append_batch_size=False,
) )
toutdata = layers.fill_constant( toutdata = layers.fill_constant(
shape=[5, 1000], dtype='float32', value=1.0 shape=[5, 1000], dtype='float32', value=1.0
......
python/paddle/fluid/tests/unittests/collective/collective_scatter_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveScatter(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveScatter(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
rootid = 1 rootid = 1
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofreduce", name="outofreduce",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/collective_sendrecv_api.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -27,11 +26,10 @@ class TestCollectiveSendRecvAPI(TestCollectiveAPIRunnerBase): ...@@ -27,11 +26,10 @@ class TestCollectiveSendRecvAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", name="tindata",
shape=[10, 1000], shape=[10, 1000],
dtype='float32', dtype='float32',
append_batch_size=False,
) )
if rank == 0: if rank == 0:
paddle.distributed.send(tindata, dst=1) paddle.distributed.send(tindata, dst=1)
......
python/paddle/fluid/tests/unittests/collective/collective_sendrecv_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -28,12 +27,12 @@ class TestCollectiveSendRecv(TestCollectiveRunnerBase): ...@@ -28,12 +27,12 @@ class TestCollectiveSendRecv(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program): def get_model(self, main_prog, startup_program):
ring_id = self.global_ring_id ring_id = self.global_ring_id
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", name="tindata",
shape=[10, 1000], shape=[10, 1000],
dtype='float64', dtype='float64',
append_batch_size=False,
) )
tindata.desc.set_need_check_feed(False)
if self.rank == 0: if self.rank == 0:
main_prog.global_block().append_op( main_prog.global_block().append_op(
type="send_v2", type="send_v2",
......
python/paddle/fluid/tests/unittests/collective/collective_sendrecv_op_array.py
浏览文件 @ 5670644c
...@@ -17,7 +17,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -17,7 +17,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -29,12 +28,12 @@ class TestCollectiveSendRecv(TestCollectiveRunnerBase): ...@@ -29,12 +28,12 @@ class TestCollectiveSendRecv(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program): def get_model(self, main_prog, startup_program):
ring_id = self.global_ring_id ring_id = self.global_ring_id
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", name="tindata",
shape=[10, 1000], shape=[10, 1000],
dtype='float64', dtype='float64',
append_batch_size=False,
) )
tindata.desc.set_need_check_feed(False)
if self.rank == 0: if self.rank == 0:
data1 = fluid.layers.assign( data1 = fluid.layers.assign(
np.array([[0, 1, 2]], dtype='float32') np.array([[0, 1, 2]], dtype='float32')
......
python/paddle/fluid/tests/unittests/collective/collective_sendrecv_op_dynamic_shape.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -28,12 +27,12 @@ class TestCollectiveSendRecvDynamicShape(TestCollectiveRunnerBase): ...@@ -28,12 +27,12 @@ class TestCollectiveSendRecvDynamicShape(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program): def get_model(self, main_prog, startup_program):
ring_id = self.global_ring_id ring_id = self.global_ring_id
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", name="tindata",
shape=[10, 1000], shape=[-1, 10, 1000],
dtype='float64', dtype='float64',
append_batch_size=False,
) )
tindata.desc.set_need_check_feed(False)
if self.rank == 0: if self.rank == 0:
main_prog.global_block().append_op( main_prog.global_block().append_op(
type="send_v2", type="send_v2",
......
python/paddle/fluid/tests/unittests/collective/collective_split_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveAllGather(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveAllGather(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofsplit", name="outofsplit",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective/fleet/dist_mnist_gradient_merge.py
浏览文件 @ 5670644c
...@@ -29,8 +29,10 @@ fluid.default_main_program().random_seed = 1 ...@@ -29,8 +29,10 @@ fluid.default_main_program().random_seed = 1
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2): def get_model(self, batch_size=2):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/collective/fleet/pipeline_mnist.py
浏览文件 @ 5670644c
...@@ -85,10 +85,12 @@ class TestDistMnist2x2(TestDistRunnerBase): ...@@ -85,10 +85,12 @@ class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None): def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
# Input data # Input data
with fluid.device_guard("gpu:0"): with fluid.device_guard("gpu:0"):
images = fluid.layers.data( images = paddle.static.data(
name='pixel', shape=[1, 28, 28], dtype=DTYPE name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(
name='label', shape=[-1, 1], dtype='int64'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
if dist_strategy: if dist_strategy:
data_loader = fluid.io.DataLoader.from_generator( data_loader = fluid.io.DataLoader.from_generator(
......
python/paddle/fluid/tests/unittests/collective/fleet/pipeline_mnist_multi_device.py
浏览文件 @ 5670644c
...@@ -85,10 +85,12 @@ class TestDistMnist2x2(TestDistRunnerBase): ...@@ -85,10 +85,12 @@ class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None): def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
# Input data # Input data
with fluid.device_guard("gpu:0"): with fluid.device_guard("gpu:0"):
images = fluid.layers.data( images = paddle.static.data(
name='pixel', shape=[1, 28, 28], dtype=DTYPE name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(
name='label', shape=[-1, 1], dtype='int64'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
if dist_strategy: if dist_strategy:
data_loader = fluid.io.DataLoader.from_generator( data_loader = fluid.io.DataLoader.from_generator(
......
python/paddle/fluid/tests/unittests/collective/fleet/pipeline_mnist_one_device.py
浏览文件 @ 5670644c
...@@ -77,10 +77,12 @@ class TestDistMnist2x2(TestDistRunnerBase): ...@@ -77,10 +77,12 @@ class TestDistMnist2x2(TestDistRunnerBase):
if dist_strategy: if dist_strategy:
fleet.init(is_collective=True) fleet.init(is_collective=True)
with fluid.device_guard("gpu:0"): with fluid.device_guard("gpu:0"):
images = fluid.layers.data( images = paddle.static.data(
name='pixel', shape=[1, 28, 28], dtype=DTYPE name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(
name='label', shape=[-1, 1], dtype='int64'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
if dist_strategy: if dist_strategy:
data_loader = fluid.io.DataLoader.from_generator( data_loader = fluid.io.DataLoader.from_generator(
......
python/paddle/fluid/tests/unittests/collective/fleet/test_communicator_half_async.py
浏览文件 @ 5670644c
...@@ -29,9 +29,9 @@ paddle.enable_static() ...@@ -29,9 +29,9 @@ paddle.enable_static()
class TestCommunicatorHalfAsyncEnd2End(unittest.TestCase): class TestCommunicatorHalfAsyncEnd2End(unittest.TestCase):
def net(self): def net(self):
x = fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
......
python/paddle/fluid/tests/unittests/collective/fleet/test_communicator_sync.py
浏览文件 @ 5670644c
...@@ -27,8 +27,8 @@ import paddle.fluid as fluid ...@@ -27,8 +27,8 @@ import paddle.fluid as fluid
class TestCommunicator(unittest.TestCase): class TestCommunicator(unittest.TestCase):
def net(self): def net(self):
x = fluid.layers.data(name='x', shape=[1], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 1], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
cost = paddle.nn.functional.square_error_cost(input=x, label=y) cost = paddle.nn.functional.square_error_cost(input=x, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
return avg_cost return avg_cost
......
python/paddle/fluid/tests/unittests/collective/fleet/test_distributed_strategy.py
浏览文件 @ 5670644c
...@@ -270,8 +270,8 @@ class TestHalfAsyncStrategy(unittest.TestCase): ...@@ -270,8 +270,8 @@ class TestHalfAsyncStrategy(unittest.TestCase):
class TestDebugInfo(unittest.TestCase): class TestDebugInfo(unittest.TestCase):
def test_debug_info(self): def test_debug_info(self):
x = fluid.layers.data(name='x', shape=[1], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 1], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y) cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
avg_cost = paddle.mean(cost) avg_cost = paddle.mean(cost)
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_fp16_allreduce_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -30,12 +30,8 @@ class TestFleetFP16CompressOptimizer(unittest.TestCase): ...@@ -30,12 +30,8 @@ class TestFleetFP16CompressOptimizer(unittest.TestCase):
def net(self, main_prog, startup_prog, dtype='float32'): def net(self, main_prog, startup_prog, dtype='float32'):
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(name="x", shape=[-1, 32], dtype=dtype)
name="x", shape=[32], dtype=dtype input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
)
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_graph_execution_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -60,12 +60,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase): ...@@ -60,12 +60,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase):
import paddle.distributed.fleet as fleet import paddle.distributed.fleet as fleet
fleet.init(is_collective=True) fleet.init(is_collective=True)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
...@@ -126,12 +124,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase): ...@@ -126,12 +124,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase):
import paddle.distributed.fleet as fleet import paddle.distributed.fleet as fleet
fleet.init(is_collective=True) fleet.init(is_collective=True)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
...@@ -204,12 +200,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase): ...@@ -204,12 +200,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase):
import paddle.distributed.fleet as fleet import paddle.distributed.fleet as fleet
fleet.init(is_collective=True) fleet.init(is_collective=True)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
...@@ -269,12 +263,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase): ...@@ -269,12 +263,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase):
import paddle.distributed.fleet as fleet import paddle.distributed.fleet as fleet
fleet.init(is_collective=True) fleet.init(is_collective=True)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_graph_executor.py
浏览文件 @ 5670644c
...@@ -45,12 +45,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase): ...@@ -45,12 +45,10 @@ class TestFleetGraphExecutionMetaOptimizer(unittest.TestCase):
def node_func(): def node_func():
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_lamb_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -33,11 +33,11 @@ class TestFleetLambMetaOptimizer(unittest.TestCase): ...@@ -33,11 +33,11 @@ class TestFleetLambMetaOptimizer(unittest.TestCase):
def net(self, main_prog, startup_prog): def net(self, main_prog, startup_prog):
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
with fluid.unique_name.guard(): with fluid.unique_name.guard():
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(
name="y", shape=[1], dtype='int64' name="y", shape=[-1, 1], dtype='int64'
) )
fc_1 = paddle.static.nn.fc( fc_1 = paddle.static.nn.fc(
...@@ -117,10 +117,8 @@ class TestFleetLambMetaOptimizer(unittest.TestCase): ...@@ -117,10 +117,8 @@ class TestFleetLambMetaOptimizer(unittest.TestCase):
def test_lamb_apply_with_amp(self): def test_lamb_apply_with_amp(self):
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(name="x", shape=[-1, 32], dtype='float32')
name="x", shape=[32], dtype='float32' input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
)
input_y = paddle.fluid.layers.data(name="y", shape=[1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_lars_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -33,11 +33,11 @@ class TestFleetLarsMetaOptimizer(unittest.TestCase): ...@@ -33,11 +33,11 @@ class TestFleetLarsMetaOptimizer(unittest.TestCase):
def net(self, main_prog, startup_prog): def net(self, main_prog, startup_prog):
with fluid.program_guard(main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog):
with fluid.unique_name.guard(): with fluid.unique_name.guard():
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(
name="y", shape=[1], dtype='int64' name="y", shape=[-1, 1], dtype='int64'
) )
fc_1 = paddle.static.nn.fc( fc_1 = paddle.static.nn.fc(
...@@ -122,10 +122,8 @@ class TestFleetLarsMetaOptimizer(unittest.TestCase): ...@@ -122,10 +122,8 @@ class TestFleetLarsMetaOptimizer(unittest.TestCase):
def test_lars_apply_with_amp(self): def test_lars_apply_with_amp(self):
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(name="x", shape=[-1, 32], dtype='float32')
name="x", shape=[32], dtype='float32' input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
)
input_y = paddle.fluid.layers.data(name="y", shape=[1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_meta_optimizer_base.py
浏览文件 @ 5670644c
...@@ -29,11 +29,11 @@ class TestFleetMetaOptimizerBase(unittest.TestCase): ...@@ -29,11 +29,11 @@ class TestFleetMetaOptimizerBase(unittest.TestCase):
with fluid.unique_name.guard(): with fluid.unique_name.guard():
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(
name="y", shape=[1], dtype='int64' name="y", shape=[-1, 1], dtype='int64'
) )
fc_1 = paddle.static.nn.fc( fc_1 = paddle.static.nn.fc(
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_pipeline_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -33,14 +33,12 @@ class TestFleetMetaOptimizer(unittest.TestCase): ...@@ -33,14 +33,12 @@ class TestFleetMetaOptimizer(unittest.TestCase):
def net(self): def net(self):
with static.device_guard("gpu:0"): with static.device_guard("gpu:0"):
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
name="y", shape=[1], dtype='int64' input_z = paddle.static.data(
) name="z", shape=[-1, 1], dtype="float32"
input_z = paddle.fluid.layers.data(
name="z", shape=[1], dtype="float32"
) )
with static.device_guard("gpu:all"): with static.device_guard("gpu:all"):
input_z = input_z * 1.0 input_z = input_z * 1.0
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_pipeline_meta_optimizer_with_recompute.py
浏览文件 @ 5670644c
...@@ -34,12 +34,10 @@ class TestFleetMetaOptimizer(unittest.TestCase): ...@@ -34,12 +34,10 @@ class TestFleetMetaOptimizer(unittest.TestCase):
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
with paddle.fluid.device_guard("gpu:0"): with paddle.fluid.device_guard("gpu:0"):
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
fc_3 = paddle.static.nn.fc(x=fc_2, size=64, activation='tanh') fc_3 = paddle.static.nn.fc(x=fc_2, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_raw_program_meta_optimizer.py
浏览文件 @ 5670644c
...@@ -33,10 +33,8 @@ class TestFleetMetaOptimizer(unittest.TestCase): ...@@ -33,10 +33,8 @@ class TestFleetMetaOptimizer(unittest.TestCase):
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(name="x", shape=[-1, 32], dtype='float32')
name="x", shape=[32], dtype='float32' input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
)
input_y = paddle.fluid.layers.data(name="y", shape=[1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh')
......
python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_rolemaker_new.py
浏览文件 @ 5670644c
...@@ -443,9 +443,9 @@ class TestGlooWithCloudRoleMaker(unittest.TestCase): ...@@ -443,9 +443,9 @@ class TestGlooWithCloudRoleMaker(unittest.TestCase):
os.environ["PADDLE_GLOO_FS_PATH"] = tmp os.environ["PADDLE_GLOO_FS_PATH"] = tmp
def net(): def net():
x = paddle.fluid.layers.data(name='x', shape=[13], dtype='float32') x = paddle.static.data(name='x', shape=[-1, 13], dtype='float32')
y_predict = paddle.static.nn.fc(x, size=1, activation=None) y_predict = paddle.static.nn.fc(x, size=1, activation=None)
y = paddle.fluid.layers.data(name='y', shape=[1], dtype='float32') y = paddle.static.data(name='y', shape=[-1, 1], dtype='float32')
cost = paddle.nn.functional.square_error_cost( cost = paddle.nn.functional.square_error_cost(
input=y_predict, label=y input=y_predict, label=y
) )
......
python/paddle/fluid/tests/unittests/collective_allgather_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveAllGather(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveAllGather(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofgather", name="outofgather",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/collective_reducescatter.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static() paddle.enable_static()
...@@ -29,9 +28,10 @@ class TestCollectiveReduceScatter(TestCollectiveRunnerBase): ...@@ -29,9 +28,10 @@ class TestCollectiveReduceScatter(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = fluid.layers.collective._c_reducescatter(tindata, nranks) toutdata = fluid.layers.collective._c_reducescatter(tindata, nranks)
toutdata = fluid.layers.collective._c_sync_comm_stream(toutdata, 0) toutdata = fluid.layers.collective._c_sync_comm_stream(toutdata, 0)
return toutdata return toutdata
......
python/paddle/fluid/tests/unittests/collective_reducescatter_op.py
浏览文件 @ 5670644c
...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main ...@@ -16,7 +16,6 @@ from test_collective_base import TestCollectiveRunnerBase, runtime_main
import paddle import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core from paddle.fluid import core
paddle.enable_static() paddle.enable_static()
...@@ -30,9 +29,10 @@ class TestCollectiveReduceScatter(TestCollectiveRunnerBase): ...@@ -30,9 +29,10 @@ class TestCollectiveReduceScatter(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofrs", name="outofrs",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/dist_allreduce_op.py
浏览文件 @ 5670644c
...@@ -72,8 +72,10 @@ def cnn_model(data): ...@@ -72,8 +72,10 @@ def cnn_model(data):
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2, single_device=False): def get_model(self, batch_size=2, single_device=False):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_ctr.py
浏览文件 @ 5670644c
...@@ -33,26 +33,23 @@ class TestDistCTR2x2(TestDistRunnerBase): ...@@ -33,26 +33,23 @@ class TestDistCTR2x2(TestDistRunnerBase):
dnn_input_dim, lr_input_dim = dist_ctr_reader.load_data_meta() dnn_input_dim, lr_input_dim = dist_ctr_reader.load_data_meta()
""" network definition """ """ network definition """
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
# build dnn model # build dnn model
......
python/paddle/fluid/tests/unittests/dist_fleet_ctr.py
浏览文件 @ 5670644c
...@@ -62,26 +62,23 @@ class TestDistCTR2x2(FleetDistRunnerBase): ...@@ -62,26 +62,23 @@ class TestDistCTR2x2(FleetDistRunnerBase):
""" """
dnn_input_dim, lr_input_dim = int(1e5), int(1e5) dnn_input_dim, lr_input_dim = int(1e5), int(1e5)
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
datas = [dnn_data, lr_data, label] datas = [dnn_data, lr_data, label]
......
python/paddle/fluid/tests/unittests/dist_fleet_heter_pipeline_ctr.py
浏览文件 @ 5670644c
...@@ -49,26 +49,23 @@ class TestHeterPipelinePsCTR2x2(FleetDistHeterRunnerBase): ...@@ -49,26 +49,23 @@ class TestHeterPipelinePsCTR2x2(FleetDistHeterRunnerBase):
dnn_input_dim, lr_input_dim = int(1e5), int(1e5) dnn_input_dim, lr_input_dim = int(1e5), int(1e5)
with fluid.device_guard("cpu"): with fluid.device_guard("cpu"):
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="float32", dtype="float32",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
datas = [dnn_data, lr_data, label] datas = [dnn_data, lr_data, label]
......
python/paddle/fluid/tests/unittests/dist_fleet_raw_program_optimizer.py
浏览文件 @ 5670644c
...@@ -74,8 +74,10 @@ def cnn_model(data): ...@@ -74,8 +74,10 @@ def cnn_model(data):
class TestFleetMetaOptimizerPrecision(TestDistRunnerBase): class TestFleetMetaOptimizerPrecision(TestDistRunnerBase):
def get_model(self, batch_size=2, single_device=False): def get_model(self, batch_size=2, single_device=False):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_fleet_raw_program_optimizer_fuse_allreduce.py
浏览文件 @ 5670644c
...@@ -74,8 +74,10 @@ def cnn_model(data): ...@@ -74,8 +74,10 @@ def cnn_model(data):
class TestFleetMetaOptimizerFuseAllReducePrecision(TestDistRunnerBase): class TestFleetMetaOptimizerFuseAllReducePrecision(TestDistRunnerBase):
def get_model(self, batch_size=2, single_device=False): def get_model(self, batch_size=2, single_device=False):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_fleet_simnet_bow.py
浏览文件 @ 5670644c
...@@ -93,18 +93,18 @@ def train_network( ...@@ -93,18 +93,18 @@ def train_network(
is_pyreader=False, is_pyreader=False,
): ):
# query # query
q = fluid.layers.data( q = paddle.static.data(
name="query_ids", shape=[1], dtype="int64", lod_level=1 name="query_ids", shape=[-1, 1], dtype="int64", lod_level=1
) )
# label data # label data
label = fluid.layers.data(name="label", shape=[1], dtype="int64") label = paddle.static.data(name="label", shape=[-1, 1], dtype="int64")
# pt # pt
pt = fluid.layers.data( pt = paddle.static.data(
name="pos_title_ids", shape=[1], dtype="int64", lod_level=1 name="pos_title_ids", shape=[-1, 1], dtype="int64", lod_level=1
) )
# nt # nt
nt = fluid.layers.data( nt = paddle.static.data(
name="neg_title_ids", shape=[1], dtype="int64", lod_level=1 name="neg_title_ids", shape=[-1, 1], dtype="int64", lod_level=1
) )
datas = [q, label, pt, nt] datas = [q, label, pt, nt]
......
python/paddle/fluid/tests/unittests/dist_fleet_sparse_embedding_ctr.py
浏览文件 @ 5670644c
...@@ -52,26 +52,23 @@ class TestDistCTR2x2(FleetDistRunnerBase): ...@@ -52,26 +52,23 @@ class TestDistCTR2x2(FleetDistRunnerBase):
""" """
dnn_input_dim, lr_input_dim = 10, 10 dnn_input_dim, lr_input_dim = 10, 10
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
datas = [dnn_data, lr_data, label] datas = [dnn_data, lr_data, label]
......
python/paddle/fluid/tests/unittests/dist_mnist.py
浏览文件 @ 5670644c
...@@ -73,8 +73,10 @@ def cnn_model(data): ...@@ -73,8 +73,10 @@ def cnn_model(data):
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None): def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_mnist_batch_merge.py
浏览文件 @ 5670644c
...@@ -38,8 +38,10 @@ def test_merge_reader(repeat_batch_size=8): ...@@ -38,8 +38,10 @@ def test_merge_reader(repeat_batch_size=8):
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2): def get_model(self, batch_size=2):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_mnist_fp16_allreduce.py
浏览文件 @ 5670644c
...@@ -32,8 +32,10 @@ fluid.default_main_program().random_seed = 1 ...@@ -32,8 +32,10 @@ fluid.default_main_program().random_seed = 1
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2): def get_model(self, batch_size=2):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_mnist_lars.py
浏览文件 @ 5670644c
...@@ -29,8 +29,10 @@ fluid.default_main_program().random_seed = 1 ...@@ -29,8 +29,10 @@ fluid.default_main_program().random_seed = 1
class TestDistMnist2x2(TestDistRunnerBase): class TestDistMnist2x2(TestDistRunnerBase):
def get_model(self, batch_size=2): def get_model(self, batch_size=2):
# Input data # Input data
images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) images = paddle.static.data(
label = fluid.layers.data(name='label', shape=[1], dtype='int64') name='pixel', shape=[-1, 1, 28, 28], dtype=DTYPE
)
label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = cnn_model(images) predict = cnn_model(images)
......
python/paddle/fluid/tests/unittests/dist_se_resnext.py
浏览文件 @ 5670644c
...@@ -209,10 +209,10 @@ class SE_ResNeXt: ...@@ -209,10 +209,10 @@ class SE_ResNeXt:
class DistSeResneXt2x2(TestDistRunnerBase): class DistSeResneXt2x2(TestDistRunnerBase):
def get_model(self, batch_size=2, use_dgc=False): def get_model(self, batch_size=2, use_dgc=False):
# Input data # Input data
image = fluid.layers.data( image = paddle.static.data(
name="data", shape=[3, 224, 224], dtype='float32' name="data", shape=[-1, 3, 224, 224], dtype='float32'
) )
label = fluid.layers.data(name="int64", shape=[1], dtype='int64') label = paddle.static.data(name="int64", shape=[-1, 1], dtype='int64')
# Train program # Train program
model = SE_ResNeXt(layers=50) model = SE_ResNeXt(layers=50)
......
python/paddle/fluid/tests/unittests/dist_sharding_save.py
浏览文件 @ 5670644c
...@@ -38,12 +38,10 @@ def runtime_main(): ...@@ -38,12 +38,10 @@ def runtime_main():
fleet.init(role) fleet.init(role)
with fluid.program_guard(train_prog, startup_prog): with fluid.program_guard(train_prog, startup_prog):
with fluid.unique_name.guard(): with fluid.unique_name.guard():
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
)
input_y = paddle.fluid.layers.data(
name="y", shape=[1], dtype='int64'
) )
input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh')
fc_2 = paddle.static.nn.fc(x=fc_1, size=256, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=256, activation='tanh')
......
python/paddle/fluid/tests/unittests/dist_text_classification.py
浏览文件 @ 5670644c
...@@ -95,8 +95,8 @@ def conv_net( ...@@ -95,8 +95,8 @@ def conv_net(
def inference_network(dict_dim): def inference_network(dict_dim):
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
) )
out = conv_net(data, dict_dim) out = conv_net(data, dict_dim)
return out return out
...@@ -125,10 +125,10 @@ class TestDistTextClassification2x2(TestDistRunnerBase): ...@@ -125,10 +125,10 @@ class TestDistTextClassification2x2(TestDistRunnerBase):
word_dict, dict_dim = get_worddict(vocab) word_dict, dict_dim = get_worddict(vocab)
# Input data # Input data
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64') label = paddle.static.data(name='label', shape=[-1, 1], dtype='int64')
# Train program # Train program
predict = conv_net(data, dict_dim) predict = conv_net(data, dict_dim)
......
python/paddle/fluid/tests/unittests/dist_transformer.py
浏览文件 @ 5670644c
...@@ -1512,14 +1512,13 @@ def make_all_inputs(input_fields): ...@@ -1512,14 +1512,13 @@ def make_all_inputs(input_fields):
""" """
inputs = [] inputs = []
for input_field in input_fields: for input_field in input_fields:
input_var = layers.data( input_var = paddle.static.data(
name=input_field, name=input_field,
shape=input_descs[input_field][0], shape=input_descs[input_field][0],
dtype=input_descs[input_field][1], dtype=input_descs[input_field][1],
lod_level=input_descs[input_field][2] lod_level=input_descs[input_field][2]
if len(input_descs[input_field]) == 3 if len(input_descs[input_field]) == 3
else 0, else 0,
append_batch_size=False,
) )
inputs.append(input_var) inputs.append(input_var)
return inputs return inputs
......
python/paddle/fluid/tests/unittests/dist_word2vec.py
浏览文件 @ 5670644c
...@@ -107,13 +107,21 @@ class TestDistWord2vec2x2(TestDistRunnerBase): ...@@ -107,13 +107,21 @@ class TestDistWord2vec2x2(TestDistRunnerBase):
word_dict = paddle.dataset.imikolov.build_dict() word_dict = paddle.dataset.imikolov.build_dict()
dict_size = len(word_dict) dict_size = len(word_dict)
first_word = fluid.layers.data(name='firstw', shape=[1], dtype='int64') first_word = paddle.static.data(
second_word = fluid.layers.data( name='firstw', shape=[-1, 1], dtype='int64'
name='secondw', shape=[1], dtype='int64' )
second_word = paddle.static.data(
name='secondw', shape=[-1, 1], dtype='int64'
)
third_word = paddle.static.data(
name='thirdw', shape=[-1, 1], dtype='int64'
)
forth_word = paddle.static.data(
name='forthw', shape=[-1, 1], dtype='int64'
)
next_word = paddle.static.data(
name='nextw', shape=[-1, 1], dtype='int64'
) )
third_word = fluid.layers.data(name='thirdw', shape=[1], dtype='int64')
forth_word = fluid.layers.data(name='forthw', shape=[1], dtype='int64')
next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64')
avg_cost, predict_word = __network__( avg_cost, predict_word = __network__(
[first_word, second_word, third_word, forth_word, next_word] [first_word, second_word, third_word, forth_word, next_word]
) )
......
python/paddle/fluid/tests/unittests/distribution/test_distribution_normal.py
浏览文件 @ 5670644c
...@@ -24,7 +24,6 @@ from test_distribution import DistributionNumpy ...@@ -24,7 +24,6 @@ from test_distribution import DistributionNumpy
import paddle import paddle
from paddle import fluid from paddle import fluid
from paddle.distribution import Normal from paddle.distribution import Normal
from paddle.fluid import layers
np.random.seed(2022) np.random.seed(2022)
...@@ -117,8 +116,8 @@ class NormalTest(unittest.TestCase): ...@@ -117,8 +116,8 @@ class NormalTest(unittest.TestCase):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[], dtype='float32' name='values', shape=[-1], dtype='float32'
) )
def compare_with_numpy(self, fetch_list, sample_shape=7, tolerance=1e-6): def compare_with_numpy(self, fetch_list, sample_shape=7, tolerance=1e-6):
...@@ -237,8 +236,8 @@ class NormalTest3(NormalTest): ...@@ -237,8 +236,8 @@ class NormalTest3(NormalTest):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -266,8 +265,8 @@ class NormalTest4(NormalTest): ...@@ -266,8 +265,8 @@ class NormalTest4(NormalTest):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -302,8 +301,8 @@ class NormalTest5(NormalTest): ...@@ -302,8 +301,8 @@ class NormalTest5(NormalTest):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float64' name='values', shape=[-1, dims], dtype='float64'
) )
...@@ -334,20 +333,20 @@ class NormalTest6(NormalTest): ...@@ -334,20 +333,20 @@ class NormalTest6(NormalTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_loc = layers.data( self.static_loc = paddle.static.data(
name='loc', shape=[dims], dtype='float32' name='loc', shape=[-1, dims], dtype='float32'
) )
self.static_scale = layers.data( self.static_scale = paddle.static.data(
name='scale', shape=[dims], dtype='float32' name='scale', shape=[-1, dims], dtype='float32'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
self.static_other_loc = layers.data( self.static_other_loc = paddle.static.data(
name='other_loc', shape=[dims], dtype='float32' name='other_loc', shape=[-1, dims], dtype='float32'
) )
self.static_other_scale = layers.data( self.static_other_scale = paddle.static.data(
name='other_scale', shape=[dims], dtype='float32' name='other_scale', shape=[-1, dims], dtype='float32'
) )
...@@ -382,20 +381,20 @@ class NormalTest7(NormalTest): ...@@ -382,20 +381,20 @@ class NormalTest7(NormalTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_loc = layers.data( self.static_loc = paddle.static.data(
name='loc', shape=[dims], dtype='float64' name='loc', shape=[-1, dims], dtype='float64'
) )
self.static_scale = layers.data( self.static_scale = paddle.static.data(
name='scale', shape=[dims], dtype='float64' name='scale', shape=[-1, dims], dtype='float64'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float64' name='values', shape=[-1, dims], dtype='float64'
) )
self.static_other_loc = layers.data( self.static_other_loc = paddle.static.data(
name='other_loc', shape=[dims], dtype='float64' name='other_loc', shape=[-1, dims], dtype='float64'
) )
self.static_other_scale = layers.data( self.static_other_scale = paddle.static.data(
name='other_scale', shape=[dims], dtype='float64' name='other_scale', shape=[-1, dims], dtype='float64'
) )
...@@ -430,20 +429,20 @@ class NormalTest8(NormalTest): ...@@ -430,20 +429,20 @@ class NormalTest8(NormalTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_loc = layers.data( self.static_loc = paddle.static.data(
name='loc', shape=[dims], dtype='float64' name='loc', shape=[-1, dims], dtype='float64'
) )
self.static_scale = layers.data( self.static_scale = paddle.static.data(
name='scale', shape=[dims], dtype='float64' name='scale', shape=[-1, dims], dtype='float64'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
self.static_other_loc = layers.data( self.static_other_loc = paddle.static.data(
name='other_loc', shape=[dims], dtype='float64' name='other_loc', shape=[-1, dims], dtype='float64'
) )
self.static_other_scale = layers.data( self.static_other_scale = paddle.static.data(
name='other_scale', shape=[dims], dtype='float64' name='other_scale', shape=[-1, dims], dtype='float64'
) )
...@@ -477,8 +476,8 @@ class NormalTest9(NormalTest): ...@@ -477,8 +476,8 @@ class NormalTest9(NormalTest):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -512,8 +511,8 @@ class NormalTest10(NormalTest): ...@@ -512,8 +511,8 @@ class NormalTest10(NormalTest):
self.static_other_loc = self.other_loc_np self.static_other_loc = self.other_loc_np
self.static_other_scale = self.other_scale_np self.static_other_scale = self.other_scale_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
......
python/paddle/fluid/tests/unittests/distribution/test_distribution_uniform.py
浏览文件 @ 5670644c
...@@ -20,7 +20,6 @@ from test_distribution import DistributionNumpy ...@@ -20,7 +20,6 @@ from test_distribution import DistributionNumpy
import paddle import paddle
from paddle import fluid from paddle import fluid
from paddle.distribution import Uniform from paddle.distribution import Uniform
from paddle.fluid import layers
np.random.seed(2022) np.random.seed(2022)
...@@ -88,8 +87,8 @@ class UniformTest(unittest.TestCase): ...@@ -88,8 +87,8 @@ class UniformTest(unittest.TestCase):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[], dtype='float32' name='values', shape=[-1], dtype='float32'
) )
def compare_with_numpy(self, fetch_list, sample_shape=7, tolerance=1e-6): def compare_with_numpy(self, fetch_list, sample_shape=7, tolerance=1e-6):
...@@ -170,8 +169,8 @@ class UniformTest3(UniformTest): ...@@ -170,8 +169,8 @@ class UniformTest3(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -188,8 +187,8 @@ class UniformTest4(UniformTest): ...@@ -188,8 +187,8 @@ class UniformTest4(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -211,8 +210,8 @@ class UniformTest5(UniformTest): ...@@ -211,8 +210,8 @@ class UniformTest5(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float64' name='values', shape=[-1, dims], dtype='float64'
) )
...@@ -232,14 +231,14 @@ class UniformTest6(UniformTest): ...@@ -232,14 +231,14 @@ class UniformTest6(UniformTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_low = layers.data( self.static_low = paddle.static.data(
name='low', shape=[dims], dtype='float32' name='low', shape=[-1, dims], dtype='float32'
) )
self.static_high = layers.data( self.static_high = paddle.static.data(
name='high', shape=[dims], dtype='float32' name='high', shape=[-1, dims], dtype='float32'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -259,14 +258,14 @@ class UniformTest7(UniformTest): ...@@ -259,14 +258,14 @@ class UniformTest7(UniformTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_low = layers.data( self.static_low = paddle.static.data(
name='low', shape=[dims], dtype='float64' name='low', shape=[-1, dims], dtype='float64'
) )
self.static_high = layers.data( self.static_high = paddle.static.data(
name='high', shape=[dims], dtype='float64' name='high', shape=[-1, dims], dtype='float64'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float64' name='values', shape=[-1, dims], dtype='float64'
) )
...@@ -286,14 +285,14 @@ class UniformTest8(UniformTest): ...@@ -286,14 +285,14 @@ class UniformTest8(UniformTest):
def init_static_data(self, batch_size, dims): def init_static_data(self, batch_size, dims):
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_low = layers.data( self.static_low = paddle.static.data(
name='low', shape=[dims], dtype='float64' name='low', shape=[-1, dims], dtype='float64'
) )
self.static_high = layers.data( self.static_high = paddle.static.data(
name='high', shape=[dims], dtype='float64' name='high', shape=[-1, dims], dtype='float64'
) )
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -311,8 +310,8 @@ class UniformTest9(UniformTest): ...@@ -311,8 +310,8 @@ class UniformTest9(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -333,8 +332,8 @@ class UniformTest10(UniformTest): ...@@ -333,8 +332,8 @@ class UniformTest10(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
...@@ -355,8 +354,8 @@ class UniformTest11(UniformTest): ...@@ -355,8 +354,8 @@ class UniformTest11(UniformTest):
self.static_low = self.low_np self.static_low = self.low_np
self.static_high = self.high_np self.static_high = self.high_np
with fluid.program_guard(self.test_program): with fluid.program_guard(self.test_program):
self.static_values = layers.data( self.static_values = paddle.static.data(
name='values', shape=[dims], dtype='float32' name='values', shape=[-1, dims], dtype='float32'
) )
......
python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_util.py
浏览文件 @ 5670644c
...@@ -296,12 +296,11 @@ class InputField: ...@@ -296,12 +296,11 @@ class InputField:
self.feed_list = [] self.feed_list = []
for slot in input_slots: for slot in input_slots:
self.feed_list.append( self.feed_list.append(
fluid.layers.data( paddle.static.data(
name=slot['name'], name=slot['name'],
shape=slot['shape'], shape=slot['shape'],
dtype=slot['dtype'], dtype=slot['dtype'],
lod_level=slot.get('lod_level', 0), lod_level=slot.get('lod_level', 0),
append_batch_size=False,
) )
) )
......
python/paddle/fluid/tests/unittests/fleet_heter_ps_training.py
浏览文件 @ 5670644c
...@@ -41,26 +41,23 @@ def net(batch_size=4, lr=0.01): ...@@ -41,26 +41,23 @@ def net(batch_size=4, lr=0.01):
dnn_input_dim, lr_input_dim = int(2), int(2) dnn_input_dim, lr_input_dim = int(2), int(2)
with fluid.device_guard("cpu"): with fluid.device_guard("cpu"):
dnn_data = fluid.layers.data( dnn_data = paddle.static.data(
name="dnn_data", name="dnn_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
lr_data = fluid.layers.data( lr_data = paddle.static.data(
name="lr_data", name="lr_data",
shape=[-1, 1], shape=[-1, 1],
dtype="int64", dtype="int64",
lod_level=1, lod_level=1,
append_batch_size=False,
) )
label = fluid.layers.data( label = paddle.static.data(
name="click", name="click",
shape=[-1, 1], shape=[-1, 1],
dtype="float32", dtype="float32",
lod_level=0, lod_level=0,
append_batch_size=False,
) )
datas = [dnn_data, lr_data, label] datas = [dnn_data, lr_data, label]
......
python/paddle/fluid/tests/unittests/fleet_meta_optimizer_base.py
浏览文件 @ 5670644c
...@@ -55,11 +55,11 @@ class TestFleetMetaOptimizer(unittest.TestCase): ...@@ -55,11 +55,11 @@ class TestFleetMetaOptimizer(unittest.TestCase):
with fluid.unique_name.guard(): with fluid.unique_name.guard():
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(
name="y", shape=[1], dtype='int64' name="y", shape=[-1, 1], dtype='int64'
) )
fc_1 = paddle.static.nn.fc( fc_1 = paddle.static.nn.fc(
...@@ -92,11 +92,11 @@ class TestFleetMetaOptimizer(unittest.TestCase): ...@@ -92,11 +92,11 @@ class TestFleetMetaOptimizer(unittest.TestCase):
role = role_maker.PaddleCloudRoleMaker(is_collective=True) role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role) fleet.init(role)
with fluid.device_guard("gpu:0"): with fluid.device_guard("gpu:0"):
input_x = paddle.fluid.layers.data( input_x = paddle.static.data(
name="x", shape=[32], dtype='float32' name="x", shape=[-1, 32], dtype='float32'
) )
input_y = paddle.fluid.layers.data( input_y = paddle.static.data(
name="y", shape=[1], dtype='int64' name="y", shape=[-1, 1], dtype='int64'
) )
for stage_idx in range(pp_degree): for stage_idx in range(pp_degree):
......
python/paddle/fluid/tests/unittests/fleet_ps_training.py
浏览文件 @ 5670644c
...@@ -15,14 +15,15 @@ ...@@ -15,14 +15,15 @@
from nets import mlp from nets import mlp
from utils import gen_data from utils import gen_data
import paddle
import paddle.fluid as fluid import paddle.fluid as fluid
from paddle.fluid.incubate.fleet.base import role_maker from paddle.fluid.incubate.fleet.base import role_maker
from paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler import ( from paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler import (
fleet, fleet,
) )
input_x = fluid.layers.data(name="x", shape=[32], dtype='float32') input_x = paddle.static.data(name="x", shape=[-1, 32], dtype='float32')
input_y = fluid.layers.data(name="y", shape=[1], dtype='int64') input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
input_y = fluid.layers.cast(input_y, dtype="float32") input_y = fluid.layers.cast(input_y, dtype="float32")
with fluid.device_guard("gpu"): with fluid.device_guard("gpu"):
......
python/paddle/fluid/tests/unittests/ir/test_ir_embedding_eltwise_layernorm_fuse_pass.py
浏览文件 @ 5670644c
...@@ -25,23 +25,20 @@ import paddle.fluid.core as core ...@@ -25,23 +25,20 @@ import paddle.fluid.core as core
class EmbEltwiseLayerNormFusePassTest(PassTest): class EmbEltwiseLayerNormFusePassTest(PassTest):
def setUp(self): def setUp(self):
with fluid.program_guard(self.main_program, self.startup_program): with fluid.program_guard(self.main_program, self.startup_program):
word_id = fluid.layers.data( word_id = paddle.static.data(
name="word_id", name="word_id",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
pos_id = fluid.layers.data( pos_id = paddle.static.data(
name="pos_id", name="pos_id",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
sent_id = fluid.layers.data( sent_id = paddle.static.data(
name="sent_id", name="sent_id",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
word_emb = fluid.layers.embedding( word_emb = fluid.layers.embedding(
input=word_id, size=(128, 768), dtype='float32' input=word_id, size=(128, 768), dtype='float32'
...@@ -56,29 +53,25 @@ class EmbEltwiseLayerNormFusePassTest(PassTest): ...@@ -56,29 +53,25 @@ class EmbEltwiseLayerNormFusePassTest(PassTest):
add2 = paddle.add(add1, sent_emb) add2 = paddle.add(add1, sent_emb)
hidden1 = paddle.static.nn.layer_norm(input=add2, begin_norm_axis=2) hidden1 = paddle.static.nn.layer_norm(input=add2, begin_norm_axis=2)
id1 = fluid.layers.data( id1 = paddle.static.data(
name="id1", name="id1",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
id2 = fluid.layers.data( id2 = paddle.static.data(
name="id2", name="id2",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
id3 = fluid.layers.data( id3 = paddle.static.data(
name="id3", name="id3",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
id4 = fluid.layers.data( id4 = paddle.static.data(
name="id4", name="id4",
shape=[1, 128, 1], shape=[1, 128, 1],
dtype="int64", dtype="int64",
append_batch_size=False,
) )
emb1 = fluid.layers.embedding( emb1 = fluid.layers.embedding(
input=id1, size=(128, 768), dtype='float32' input=id1, size=(128, 768), dtype='float32'
......
python/paddle/fluid/tests/unittests/ir/test_ir_subgraph_python_interface.py
浏览文件 @ 5670644c
...@@ -28,10 +28,12 @@ paddle.enable_static() ...@@ -28,10 +28,12 @@ paddle.enable_static()
class TestQuantizationSubGraph(unittest.TestCase): class TestQuantizationSubGraph(unittest.TestCase):
def build_graph_with_sub_graph(self): def build_graph_with_sub_graph(self):
def linear_fc(num): def linear_fc(num):
data = fluid.layers.data( data = paddle.static.data(
name='image', shape=[1, 32, 32], dtype='float32' name='image', shape=[-1, 1, 32, 32], dtype='float32'
)
label = paddle.static.data(
name='label', shape=[-1, 1], dtype='int64'
) )
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
hidden = data hidden = data
for _ in range(num): for _ in range(num):
hidden = paddle.static.nn.fc( hidden = paddle.static.nn.fc(
......
python/paddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
浏览文件 @ 5670644c
...@@ -60,11 +60,11 @@ class BuildIrMemOptBase(unittest.TestCase): ...@@ -60,11 +60,11 @@ class BuildIrMemOptBase(unittest.TestCase):
fluid.default_startup_program().random_seed = 100 fluid.default_startup_program().random_seed = 100
fluid.default_main_program().random_seed = 100 fluid.default_main_program().random_seed = 100
data = fluid.layers.data( data = paddle.static.data(
name="words", shape=[1], dtype="int64", lod_level=1 name="words", shape=[-1, 1], dtype="int64", lod_level=1
) )
label = fluid.layers.data(name="label", shape=[1], dtype="int64") label = paddle.static.data(name="label", shape=[-1, 1], dtype="int64")
cost = network(data, label, len(self.word_dict)) cost = network(data, label, len(self.word_dict))
optimizer = fluid.optimizer.Adam(learning_rate=0.001) optimizer = fluid.optimizer.Adam(learning_rate=0.001)
......
python/paddle/fluid/tests/unittests/mlu/collective_allgather_api.py
浏览文件 @ 5670644c
...@@ -45,8 +45,8 @@ class TestCollectiveAllgatherAPI(TestCollectiveAPIRunnerBase): ...@@ -45,8 +45,8 @@ class TestCollectiveAllgatherAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tensor_list = [] tensor_list = []
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
paddle.distributed.all_gather(tensor_list, tindata) paddle.distributed.all_gather(tensor_list, tindata)
return tensor_list return tensor_list
......
python/paddle/fluid/tests/unittests/mlu/collective_allgather_op.py
浏览文件 @ 5670644c
...@@ -42,9 +42,10 @@ class TestCollectiveAllgather(TestCollectiveRunnerBase): ...@@ -42,9 +42,10 @@ class TestCollectiveAllgather(TestCollectiveRunnerBase):
ring_id = 0 ring_id = 0
nranks = 2 nranks = 2
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outofallgather", name="outofallgather",
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/mlu/collective_allreduce_api.py
浏览文件 @ 5670644c
...@@ -44,8 +44,8 @@ class TestCollectiveAllreduceAPI(TestCollectiveAPIRunnerBase): ...@@ -44,8 +44,8 @@ class TestCollectiveAllreduceAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
paddle.distributed.all_reduce(tindata) paddle.distributed.all_reduce(tindata)
return [tindata] return [tindata]
......
python/paddle/fluid/tests/unittests/mlu/collective_allreduce_op.py
浏览文件 @ 5670644c
...@@ -42,9 +42,11 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase): ...@@ -42,9 +42,11 @@ class TestCollectiveAllreduce(TestCollectiveRunnerBase):
def get_model(self, main_prog, startup_program, col_type): def get_model(self, main_prog, startup_program, col_type):
ring_id = 0 ring_id = 0
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype='float32' name="tindata", shape=[-1, 10, 1000], dtype='float32'
) )
tindata.desc.set_need_check_feed(False)
toutdata = main_prog.current_block().create_var( toutdata = main_prog.current_block().create_var(
name="outof" + col_type, name="outof" + col_type,
dtype='float32', dtype='float32',
......
python/paddle/fluid/tests/unittests/mlu/collective_broadcast_api.py
浏览文件 @ 5670644c
...@@ -44,9 +44,11 @@ class TestCollectiveBroadcastAPI(TestCollectiveAPIRunnerBase): ...@@ -44,9 +44,11 @@ class TestCollectiveBroadcastAPI(TestCollectiveAPIRunnerBase):
def get_model(self, main_prog, startup_program, rank): def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program): with fluid.program_guard(main_prog, startup_program):
tindata = layers.data( tindata = paddle.static.data(
name="tindata", shape=[10, 1000], dtype="float32" name="tindata", shape=[-1, 10, 1000], dtype="float32"
) )
tindata.desc.set_need_check_feed(False)
paddle.distributed.broadcast(tindata, src=1) paddle.distributed.broadcast(tindata, src=1)
return [tindata] return [tindata]
......
tools/infrt/fake_models/multi_fc.py
浏览文件 @ 5670644c
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