未验证 提交 1f8d8a53 编写于 作者: Z zhongpu 提交者: GitHub

remove dygraph api to paddle.imperative, test=develop (#23628)

上级 fc1b140a
......@@ -36,6 +36,7 @@ batch = batch.batch
import paddle.sysconfig
import paddle.tensor
import paddle.nn
import paddle.imperative
# TODO: define alias in tensor and framework directory
# from .tensor.creation import create_.tensor #DEFINE_ALIAS
......
......@@ -21,6 +21,7 @@ from paddle.fluid import core
from paddle.fluid import Linear
from test_imperative_base import new_program_scope
import paddle.fluid.dygraph_utils as dygraph_utils
import paddle
class MyLayer(fluid.Layer):
......@@ -245,6 +246,24 @@ class TestImperative(unittest.TestCase):
self.assertTrue(tmp._grad_ivar() is None)
self.assertTrue(l0.weight._grad_ivar() is not None)
def test_paddle_imperative_no_grad_guard(self):
data = np.array([[2, 3], [4, 5]]).astype('float32')
with fluid.dygraph.guard():
l0 = fluid.Linear(2, 2)
self.assertTrue(l0.weight._grad_ivar() is None)
l1 = fluid.Linear(2, 2)
with paddle.imperative.no_grad():
self.assertTrue(l1.weight.stop_gradient is False)
tmp = l1.weight * 2
self.assertTrue(tmp.stop_gradient)
x = fluid.dygraph.to_variable(data)
y = l0(x) + tmp
o = l1(y)
o.backward()
self.assertTrue(tmp._grad_ivar() is None)
self.assertTrue(l0.weight._grad_ivar() is not None)
def test_sum_op(self):
x = np.ones([2, 2], np.float32)
with fluid.dygraph.guard():
......
......@@ -17,6 +17,7 @@ from __future__ import print_function
import unittest
import paddle.fluid as fluid
import numpy as np
import paddle
class MyLayer(fluid.Layer):
......@@ -31,12 +32,20 @@ class MyLayer(fluid.Layer):
class TestImperativeContainer(unittest.TestCase):
def test_layer_list(self):
def fluid_dygraph_list(self):
return fluid.dygraph.LayerList(
[fluid.dygraph.Linear(2**i, 2**(i + 1)) for i in range(6)])
def paddle_imperative_list(self):
return paddle.imperative.LayerList(
[fluid.dygraph.Linear(2**i, 2**(i + 1)) for i in range(6)])
def layer_list(self, use_fluid_api):
data_np = np.random.uniform(-1, 1, [5, 1]).astype('float32')
with fluid.dygraph.guard():
x = fluid.dygraph.to_variable(data_np)
layerlist = fluid.dygraph.LayerList(
[fluid.dygraph.Linear(2**i, 2**(i + 1)) for i in range(6)])
layerlist = self.fluid_dygraph_list(
) if use_fluid_api else self.paddle_imperative_list()
size = len(layerlist)
model = MyLayer(layerlist)
......@@ -75,6 +84,10 @@ class TestImperativeContainer(unittest.TestCase):
self.assertListEqual(res8.shape, [5, 3**3])
res8.backward()
def test_layer_list(self):
self.layer_list(True)
self.layer_list(False)
if __name__ == '__main__':
unittest.main()
......@@ -17,13 +17,25 @@ from __future__ import print_function
import unittest
import paddle.fluid as fluid
import numpy as np
import paddle
class MyLayer(fluid.Layer):
def __init__(self, num_stacked_param):
def __init__(self, num_stacked_param, use_fluid_api):
super(MyLayer, self).__init__()
# create ParameterList with iterable Parameters
self.params = fluid.dygraph.ParameterList(
self.params = self.fluid_dygraph_ParameterList(
num_stacked_param
) if use_fluid_api else self.paddle_imperative_ParameterList(
num_stacked_param)
def fluid_dygraph_ParameterList(self, num_stacked_param):
return fluid.dygraph.ParameterList(
[fluid.layers.create_parameter(
shape=[2, 2], dtype='float32')] * num_stacked_param)
def paddle_imperative_ParameterList(self, num_stacked_param):
return paddle.imperative.ParameterList(
[fluid.layers.create_parameter(
shape=[2, 2], dtype='float32')] * num_stacked_param)
......@@ -42,12 +54,12 @@ class MyLayer(fluid.Layer):
class TestImperativeContainerParameterList(unittest.TestCase):
def test_paramter_list(self):
def paramter_list(self, use_fluid_api):
data_np = np.random.uniform(-1, 1, [5, 2]).astype('float32')
with fluid.dygraph.guard():
x = fluid.dygraph.to_variable(data_np)
num_stacked_param = 4
model = MyLayer(num_stacked_param)
model = MyLayer(num_stacked_param, use_fluid_api)
self.assertEqual(len(model.params), num_stacked_param)
res = model(x)
self.assertListEqual(res.shape, [5, 2])
......@@ -67,6 +79,10 @@ class TestImperativeContainerParameterList(unittest.TestCase):
loss = fluid.layers.reduce_mean(res)
loss.backward()
def test_paramter_list(self):
self.paramter_list(True)
self.paramter_list(False)
if __name__ == '__main__':
unittest.main()
......@@ -43,7 +43,7 @@ class MLP(fluid.Layer):
class TestDataParallelStateDict(unittest.TestCase):
def test_data_parallel_state_dict(self):
with fluid.dygraph.guard():
strategy = dygraph.parallel.prepare_context()
strategy = paddle.imperative.prepare_context()
mlp = MLP()
parallel_mlp = dygraph.parallel.DataParallel(mlp, strategy)
......
......@@ -27,7 +27,6 @@ from paddle.fluid.dygraph.nn import Conv2D, Pool2D, Linear
from paddle.fluid.dygraph.base import to_variable
from test_imperative_base import new_program_scope
from utils import DyGraphProgramDescTracerTestHelper, is_equal_program
from paddle.fluid.dygraph import TracedLayer
class SimpleImgConvPool(fluid.dygraph.Layer):
......@@ -154,7 +153,7 @@ class TestImperativeMnist(unittest.TestCase):
label.stop_gradient = True
if batch_id % 10 == 0:
cost, traced_layer = TracedLayer.trace(
cost, traced_layer = paddle.imperative.TracedLayer.trace(
mnist, inputs=img)
if program is not None:
self.assertTrue(program, traced_layer.program)
......
......@@ -15,6 +15,7 @@
import unittest
import numpy as np
import paddle.fluid as fluid
import paddle
class MyLayer(fluid.Layer):
......@@ -66,7 +67,7 @@ class TestImperativeNamedParameters(unittest.TestCase):
fc1 = fluid.Linear(10, 3)
fc2 = fluid.Linear(3, 10, bias_attr=False)
custom = MyLayer(3, 10)
model = fluid.dygraph.Sequential(fc1, fc2, custom)
model = paddle.imperative.Sequential(fc1, fc2, custom)
named_parameters = list(model.named_parameters())
expected_named_parameters = list()
......
......@@ -26,6 +26,7 @@ from paddle.fluid.dygraph.learning_rate_scheduler import LearningRateDecay
from test_imperative_base import new_program_scope
import numpy as np
import six
import paddle
class SimpleLSTMRNN(fluid.Layer):
......@@ -880,17 +881,18 @@ class TestDygraphPtbRnn(unittest.TestCase):
with fluid.dygraph.guard():
emb = fluid.dygraph.Embedding([10, 10])
state_dict = emb.state_dict()
fluid.save_dygraph(state_dict, os.path.join('saved_dy', 'emb_dy'))
paddle.imperative.save_dygraph(state_dict,
os.path.join('saved_dy', 'emb_dy'))
para_state_dict, opti_state_dict = fluid.load_dygraph(
para_state_dict, opti_state_dict = paddle.imperative.load_dygraph(
os.path.join('saved_dy', 'emb_dy'))
self.assertTrue(opti_state_dict == None)
para_state_dict, opti_state_dict = fluid.load_dygraph(
para_state_dict, opti_state_dict = paddle.imperative.load_dygraph(
os.path.join('saved_dy', 'emb_dy.pdparams'))
para_state_dict, opti_state_dict = fluid.load_dygraph(
para_state_dict, opti_state_dict = paddle.imperative.load_dygraph(
os.path.join('saved_dy', 'emb_dy.pdopt'))
......
......@@ -21,9 +21,10 @@ from paddle.fluid.dygraph.nn import Embedding
from paddle.fluid.optimizer import SGDOptimizer
import numpy as np
import paddle.fluid.core as core
import paddle
class SimpleNet(fluid.Layer):
class SimpleNet(paddle.imperative.Layer):
def __init__(self, vocab_size, hidden_size, dtype):
super(SimpleNet, self).__init__()
self.emb = fluid.dygraph.Embedding(
......@@ -46,13 +47,13 @@ class TestSimpleNet(unittest.TestCase):
for place in places:
for dtype in ["float32", "float64"]:
for sort_sum_gradient in [True, False]:
with fluid.dygraph.guard(place):
backward_strategy = fluid.dygraph.BackwardStrategy()
with paddle.imperative.guard(place):
backward_strategy = paddle.imperative.BackwardStrategy()
backward_strategy.sort_sum_gradient = sort_sum_gradient
# grad_clip = fluid.clip.GradientClipByGlobalNorm(5.0)
input_word = np.array([[1, 2], [2, 1]]).astype('int64')
input = to_variable(input_word)
input = paddle.imperative.to_variable(input_word)
simplenet = SimpleNet(20, 32, dtype)
adam = SGDOptimizer(
......
......@@ -12,15 +12,19 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: define api used to run in imperative mode
# __all__ = ['BackwardStrategy',
# 'guard',
# 'Layer',
# 'LayerList',
# 'load_dygraph',
# 'save_dygraph',
# 'prepare_context',
# 'to_variable',
# 'TracedLayer',
# 'no_grad',
# 'ParameterList']
# define api used to run in imperative mode
__all__ = [
'BackwardStrategy', 'guard', 'Layer', 'LayerList', 'load_dygraph',
'save_dygraph', 'prepare_context', 'to_variable', 'TracedLayer', 'no_grad',
'ParameterList', 'Sequential'
]
from paddle.fluid import core
from ..fluid.dygraph.base import guard, no_grad, to_variable
from ..fluid.dygraph.layers import Layer
from ..fluid.dygraph.container import LayerList, ParameterList, Sequential
from ..fluid.dygraph.checkpoint import load_dygraph, save_dygraph
from ..fluid.dygraph.parallel import prepare_context
from ..fluid.dygraph.jit import TracedLayer
BackwardStrategy = core.BackwardStrategy
......@@ -177,7 +177,8 @@ packages=['paddle',
'paddle.fluid.incubate.fleet.utils',
'paddle.nn',
'paddle.nn.functional',
'paddle.nn.layer']
'paddle.nn.layer',
'paddle.imperative']
with open('@PADDLE_SOURCE_DIR@/python/requirements.txt') as f:
setup_requires = f.read().splitlines()
......
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