diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index b1fd0d578589d53d87c8a5b95be91f5810c6a7da..af6df7ce8116a0c22acbcfa884cb7075b681bb31 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -5736,27 +5736,28 @@ def device_guard(device=None): Examples: .. code-block:: python - import paddle.fluid as fluid + import paddle - support_gpu = fluid.is_compiled_with_cuda() - place = fluid.CPUPlace() + paddle.enable_static() + support_gpu = paddle.is_compiled_with_cuda() + place = paddle.CPUPlace() if support_gpu: - place = fluid.CUDAPlace(0) + place = paddle.CUDAPlace(0) # if GPU is supported, the three OPs below will be automatically assigned to CUDAPlace(0) - data1 = fluid.layers.fill_constant(shape=[1, 3, 8, 8], value=0.5, dtype='float32') - data2 = fluid.layers.fill_constant(shape=[1, 3, 5, 5], value=0.5, dtype='float32') - shape = fluid.layers.shape(data2) + data1 = paddle.full(shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32') + data2 = paddle.full(shape=[1, 3, 64], fill_value=0.5, dtype='float32') + shape = paddle.shape(data2) - with fluid.device_guard("cpu"): + with paddle.static.device_guard("cpu"): # Ops created here will be placed on CPUPlace - shape = fluid.layers.slice(shape, axes=[0], starts=[0], ends=[4]) - with fluid.device_guard('gpu'): + shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4]) + with paddle.static.device_guard('gpu'): # if GPU is supported, OPs created here will be placed on CUDAPlace(0), otherwise on CPUPlace - out = fluid.layers.crop_tensor(data1, shape=shape) + out = paddle.reshape(data1, shape=shape) - exe = fluid.Executor(place) - exe.run(fluid.default_startup_program()) + exe = paddle.static.Executor(place) + exe.run(paddle.static.default_startup_program()) result = exe.run(fetch_list=[out]) """ diff --git a/python/paddle/fluid/tests/unittests/test_device_guard.py b/python/paddle/fluid/tests/unittests/test_device_guard.py index 330065ecd92f1537e10df7b993682da821a46548..e547c786feb1193a526189300ce8586e708c52be 100644 --- a/python/paddle/fluid/tests/unittests/test_device_guard.py +++ b/python/paddle/fluid/tests/unittests/test_device_guard.py @@ -18,17 +18,18 @@ import unittest from op_test import OpTest import numpy as np +import paddle import paddle.fluid as fluid import paddle.fluid.core as core import warnings def execute(main_program, startup_program): - if core.is_compiled_with_cuda(): - place = core.CUDAPlace(0) + if paddle.is_compiled_with_cuda(): + place = paddle.CUDAPlace(0) else: - place = core.CPUPlace() - exe = fluid.Executor(place) + place = paddle.CPUPlace() + exe = paddle.static.Executor(place) exe.run(startup_program) exe.run(main_program) @@ -43,18 +44,17 @@ def get_vaild_warning_num(warning, w): class TestDeviceGuard(unittest.TestCase): def test_device_guard(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - data1 = fluid.layers.fill_constant( - shape=[1, 3, 8, 8], value=0.5, dtype='float32') - data2 = fluid.layers.fill_constant( - shape=[1, 3, 5, 5], value=0.5, dtype='float32') - shape = fluid.layers.shape(data2) - with fluid.device_guard("cpu"): - shape = fluid.layers.slice( - shape, axes=[0], starts=[0], ends=[4]) - with fluid.device_guard("gpu"): + main_program = paddle.static.Program() + startup_program = paddle.static.Program() + with paddle.static.program_guard(main_program, startup_program): + data1 = paddle.full( + shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32') + data2 = paddle.full( + shape=[1, 3, 5, 5], fill_value=0.5, dtype='float32') + shape = paddle.shape(data2) + with paddle.static.device_guard("cpu"): + shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4]) + with paddle.static.device_guard("gpu"): out = fluid.layers.crop_tensor(data1, shape=shape) # check if the device attr is set correctly all_ops = main_program.global_block().ops @@ -68,18 +68,17 @@ class TestDeviceGuard(unittest.TestCase): execute(main_program, startup_program) def test_device_guard_with_id(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - data1 = fluid.layers.fill_constant( - shape=[1, 3, 8, 8], value=0.5, dtype='float32') - data2 = fluid.layers.fill_constant( - shape=[1, 3, 5, 5], value=0.5, dtype='float32') - shape = fluid.layers.shape(data2) - with fluid.device_guard("cpu"): - shape = fluid.layers.slice( - shape, axes=[0], starts=[0], ends=[4]) - with fluid.device_guard("gpu:1"): + main_program = paddle.static.Program() + startup_program = paddle.static.Program() + with paddle.static.program_guard(main_program, startup_program): + data1 = paddle.full( + shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32') + data2 = paddle.full( + shape=[1, 3, 5, 5], fill_value=0.5, dtype='float32') + shape = paddle.shape(data2) + with paddle.static.device_guard("cpu"): + shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4]) + with paddle.static.device_guard("gpu:1"): out = fluid.layers.crop_tensor(data1, shape=shape) # check if the device attr is set correctly all_ops = main_program.global_block().ops @@ -93,23 +92,22 @@ class TestDeviceGuard(unittest.TestCase): execute(main_program, startup_program) def test_cpu_only_op(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - x = fluid.layers.fill_constant( - shape=[2, 255, 13, 13], value=0.3, dtype='float32') - gt_box = fluid.layers.fill_constant( - shape=[2, 6, 4], value=0.5, dtype='float32') - gt_label = fluid.layers.fill_constant( - shape=[2, 6], value=1.0, dtype='int32') - gt_score = fluid.layers.fill_constant( - shape=[2, 6], value=0.5, dtype='float32') + main_program = paddle.static.Program() + startup_program = paddle.static.Program() + with paddle.static.program_guard(main_program, startup_program): + x = paddle.full( + shape=[2, 255, 13, 13], fill_value=0.3, dtype='float32') + gt_box = paddle.full( + shape=[2, 6, 4], fill_value=0.5, dtype='float32') + gt_label = paddle.full(shape=[2, 6], fill_value=1.0, dtype='int32') + gt_score = paddle.full( + shape=[2, 6], fill_value=0.5, dtype='float32') anchors = [ 10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326 ] anchor_mask = [0, 1, 2] - with fluid.device_guard("gpu"): + with paddle.static.device_guard("gpu"): # yolov3_loss only has cpu kernel, so its cpu kernel will be executed loss = fluid.layers.yolov3_loss( x=x, @@ -125,20 +123,19 @@ class TestDeviceGuard(unittest.TestCase): execute(main_program, startup_program) def test_without_kernel_op(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0) - loop_len = fluid.layers.fill_constant( - shape=[1], dtype='int64', value=10) - cond = fluid.layers.less_than(x=i, y=loop_len) + main_program = paddle.static.Program() + startup_program = paddle.static.Program() + with paddle.static.program_guard(main_program, startup_program): + i = paddle.full(shape=[1], dtype='int64', fill_value=0) + loop_len = paddle.full(shape=[1], dtype='int64', fill_value=10) + cond = paddle.less_than(x=i, y=loop_len) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") - with fluid.device_guard("cpu"): + with paddle.static.device_guard("cpu"): while_op = fluid.layers.While(cond=cond) with while_op.block(): - i = fluid.layers.increment(x=i, value=1, in_place=True) + i = paddle.increment(x=i, value=1) fluid.layers.less_than(x=i, y=loop_len, cond=cond) warning = "The Op(while) is not support to set device." @@ -155,55 +152,32 @@ class TestDeviceGuard(unittest.TestCase): def test_error(self): def device_attr(): - with fluid.device_guard("cpu1"): - out = fluid.layers.fill_constant( - shape=[1], value=0.2, dtype='float32') + with paddle.static.device_guard("cpu1"): + out = paddle.full(shape=[1], fill_value=0.2, dtype='float32') def device_attr2(): - with fluid.device_guard("cpu:1"): - out = fluid.layers.fill_constant( - shape=[1], value=0.2, dtype='float32') + with paddle.static.device_guard("cpu:1"): + out = paddle.full(shape=[1], fill_value=0.2, dtype='float32') self.assertRaises(ValueError, device_attr) self.assertRaises(ValueError, device_attr2) - def test_warning(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter("always") - with fluid.device_guard("gpu"): - x = fluid.layers.fill_constant( - shape=[1], value=3.0, dtype='float32', force_cpu=True) - y = fluid.layers.fill_constant( - shape=[1], value=4.0, dtype='float32') - result = fluid.layers.less_than(x=x, y=y, force_cpu=False) - - warning = "\'device_guard\' has higher priority when they are used at the same time." - warning_num = get_vaild_warning_num(warning, w) - assert warning_num == 2 - - all_ops = main_program.global_block().ops - device_attr_name = core.op_proto_and_checker_maker.kOpDeviceAttrName() - for op in all_ops: - self.assertEqual(op.desc.attr(device_attr_name), "gpu") - # check if op_descs have op_device attr def test_op_descs_device_attr(self): - main_program = fluid.Program() - startup_program = fluid.Program() - with fluid.program_guard(main_program, startup_program): - data1 = fluid.layers.data(name="data_1", shape=[2], dtype="float32") - data2 = fluid.layers.data(name="data_2", shape=[2], dtype="float32") - label = fluid.layers.data(name="label", shape=[1], dtype="int64") - fc1 = fluid.layers.fc(input=data1, size=10) - fc2 = fluid.layers.fc(input=fc1, size=10) - with fluid.device_guard("gpu"): - out = fluid.layers.softmax_with_cross_entropy( + main_program = paddle.static.Program() + startup_program = paddle.static.Program() + with paddle.static.program_guard(main_program, startup_program): + data1 = paddle.static.data( + name="data_1", shape=[4, 2], dtype="float32") + label = paddle.static.data( + name="label", shape=[4, 1], dtype="int64") + fc1 = paddle.static.nn.fc(x=data1, size=10) + fc2 = paddle.static.nn.fc(x=fc1, size=10) + with paddle.static.device_guard("gpu"): + out = paddle.nn.functional.softmax_with_cross_entropy( logits=fc1 + fc2, label=label) - loss = fluid.layers.mean(out) - opt = fluid.optimizer.SGDOptimizer(0.1) + loss = paddle.mean(out) + opt = paddle.optimizer.SGD(0.1) opt.minimize(loss) all_ops = main_program.global_block().ops diff --git a/python/paddle/static/__init__.py b/python/paddle/static/__init__.py index 332e9c255101813fe9c6be71fbbf1e2816e1caee..0ac5dbee5f8effe0e3b06ac681d1f71e2d173ff1 100644 --- a/python/paddle/static/__init__.py +++ b/python/paddle/static/__init__.py @@ -72,6 +72,7 @@ from ..fluid.compiler import CompiledProgram #DEFINE_ALIAS from ..fluid.compiler import ExecutionStrategy #DEFINE_ALIAS from ..fluid.framework import default_main_program #DEFINE_ALIAS from ..fluid.framework import default_startup_program #DEFINE_ALIAS +from ..fluid.framework import device_guard #DEFINE_ALIAS from ..fluid.framework import Program #DEFINE_ALIAS from ..fluid.framework import name_scope #DEFINE_ALIAS from ..fluid.framework import program_guard #DEFINE_ALIAS