未验证 提交 05d2b7a3 编写于 作者: J joejiong 提交者: GitHub

Update paddle.static.Print with paddle2.0 api (#30846)

As the title
上级 e49d0746
......@@ -13,25 +13,26 @@
# limitations under the License.
from __future__ import print_function
import unittest
import paddle.fluid.core as core
from paddle.fluid.executor import Executor
import numpy as np
from op_test import OpTest
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid.backward import append_backward
from paddle.fluid import core
from paddle.fluid.framework import switch_main_program
from paddle.fluid.framework import Program
import numpy as np
from simple_nets import simple_fc_net, init_data
from paddle.fluid import compiler, Program, program_guard
from op_test import OpTest
from paddle.static import Program, program_guard
paddle.enable_static()
class TestPrintOpCPU(unittest.TestCase):
def setUp(self):
self.place = core.CPUPlace()
self.x_tensor = core.LoDTensor()
self.place = paddle.CPUPlace()
self.x_tensor = fluid.core.LoDTensor()
tensor_np = np.random.random(size=(2, 3)).astype('float32')
self.x_tensor.set(tensor_np, self.place)
self.x_tensor.set_recursive_sequence_lengths([[1, 1]])
......@@ -39,15 +40,15 @@ class TestPrintOpCPU(unittest.TestCase):
def build_network(self, only_forward, **kargs):
x = layers.data('x', shape=[3], dtype='float32', lod_level=1)
x.stop_gradient = False
layers.Print(input=x, **kargs)
loss = layers.mean(x)
append_backward(loss=loss)
paddle.static.Print(input=x, **kargs)
loss = paddle.mean(x)
paddle.static.append_backward(loss=loss)
return loss
def test_forward(self):
switch_main_program(Program())
printed = self.build_network(True, print_phase='forward')
exe = Executor(self.place)
exe = paddle.static.Executor(self.place)
outs = exe.run(feed={'x': self.x_tensor},
fetch_list=[printed],
return_numpy=False)
......@@ -55,7 +56,7 @@ class TestPrintOpCPU(unittest.TestCase):
def test_backward(self):
switch_main_program(Program())
loss = self.build_network(False, print_phase='backward')
exe = Executor(self.place)
exe = paddle.static.Executor(self.place)
outs = exe.run(feed={'x': self.x_tensor},
fetch_list=[loss],
return_numpy=False)
......@@ -68,15 +69,15 @@ class TestPrintOpCPU(unittest.TestCase):
for print_tensor_type in [True, False]:
for print_tensor_shape in [True, False]:
for print_tensor_lod in [True, False]:
layers.Print(
paddle.static.Print(
input=x,
print_tensor_name=print_tensor_name,
print_tensor_type=print_tensor_type,
print_tensor_shape=print_tensor_shape,
print_tensor_lod=print_tensor_lod, )
loss = layers.mean(x)
append_backward(loss=loss)
exe = Executor(self.place)
loss = paddle.mean(x)
paddle.static.append_backward(loss=loss)
exe = paddle.static.Executor(self.place)
outs = exe.run(feed={'x': self.x_tensor},
fetch_list=[loss],
return_numpy=False)
......@@ -84,7 +85,7 @@ class TestPrintOpCPU(unittest.TestCase):
def test_no_summarize(self):
switch_main_program(Program())
printed = self.build_network(True, summarize=-1, print_phase='forward')
exe = Executor(self.place)
exe = paddle.static.Executor(self.place)
outs = exe.run(feed={'x': self.x_tensor},
fetch_list=[printed],
return_numpy=False)
......@@ -95,19 +96,19 @@ class TestPrintOpError(unittest.TestCase):
with program_guard(Program(), Program()):
# The input type of Print_op must be Variable.
x1 = fluid.create_lod_tensor(
np.array([[-1]]), [[1]], fluid.CPUPlace())
self.assertRaises(TypeError, fluid.layers.Print, x1)
np.array([[-1]]), [[1]], paddle.CPUPlace())
self.assertRaises(TypeError, paddle.static.Print, x1)
# The input dtype of Print_op must be float32, float64, int32_t, int64_t or bool.
x2 = fluid.layers.data(name='x2', shape=[4], dtype="float16")
self.assertRaises(TypeError, fluid.layers.Print, x2)
x2 = paddle.static.data(name='x2', shape=[4], dtype="float16")
self.assertRaises(TypeError, paddle.static.Print, x2)
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestPrintOpGPU(TestPrintOpCPU):
def setUp(self):
self.place = core.CUDAPlace(0)
self.x_tensor = core.LoDTensor()
self.place = paddle.CUDAPlace(0)
self.x_tensor = fluid.core.LoDTensor()
tensor_np = np.random.random(size=(2, 3)).astype('float32')
self.x_tensor.set(tensor_np, self.place)
self.x_tensor.set_recursive_sequence_lengths([[1, 1]])
......@@ -115,22 +116,22 @@ class TestPrintOpGPU(TestPrintOpCPU):
class TestPrintOpBackward(unittest.TestCase):
def check_backward(self, use_cuda):
main = fluid.Program()
startup = fluid.Program()
main = paddle.static.Program()
startup = paddle.static.Program()
with fluid.program_guard(main, startup):
with program_guard(main, startup):
loss = simple_fc_net()
loss = fluid.layers.Print(loss)
fluid.optimizer.Adam().minimize(loss)
loss = paddle.static.Print(loss)
paddle.optimizer.Adam().minimize(loss)
print_ops = [op for op in main.blocks[0].ops if op.type == u'print']
assert len(print_ops) == 2, "The number of print op should be 2"
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
exe = fluid.Executor(place)
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
exe = paddle.static.Executor(place)
exe.run(startup)
binary = fluid.compiler.CompiledProgram(main).with_data_parallel(
binary = paddle.static.CompiledProgram(main).with_data_parallel(
loss_name=loss.name)
img, label = init_data()
......@@ -138,7 +139,7 @@ class TestPrintOpBackward(unittest.TestCase):
exe.run(binary, feed_dict)
def test_fw_bw(self):
if core.is_compiled_with_cuda():
if paddle.is_compiled_with_cuda():
self.check_backward(use_cuda=True)
self.check_backward(use_cuda=False)
......
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