def guard(place=None):
train = framework.Program()
startup = framework.Program()
tracer = Tracer(train.current_block().desc)
if place is None:
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with framework.program_guard(train, startup):
with framework.unique_name.guard():
with framework._dygraph_guard(tracer):
with framework._dygraph_place_guard(place):
yield
def guard(place=None):
"""
:api_attr: imperative
This context will create a dygraph context for dygraph to run, using python ``with`` statement.
Parameters:
place(fluid.CPUPlace| fluid.CUDAPlace|str, optional): Place to execute dygraph.
If None, the running place will be determined according to the way of paddle compilation.
If ``place`` is string, It can be ``cpu``, ``gpu:x`` and ``xpu:x``, where ``x`` is the
index of the GPUs or XPUs. Default: None
return:
None
Examples:
.. code-block:: python
import numpy as np
import paddle.fluid as fluid
with fluid.dygraph.guard():
inp = np.ones([3, 1024], dtype='float32')
t = fluid.dygraph.base.to_variable(inp)
linear1 = fluid.Linear(1024, 4, bias_attr=False)
linear2 = fluid.Linear(4, 4)
ret = linear1(t)
dy_ret = linear2(ret)
"""
train = framework.Program()
startup = framework.Program()
tracer = Tracer()
VarBase = core.VarBase
if place is not None:
expected_place = _get_paddle_place(place)
else:
expected_place = framework._current_expected_place()
with framework.program_guard(train, startup):
with framework.unique_name.guard():
with framework._dygraph_guard(tracer):
with framework._dygraph_place_guard(expected_place):
yield
def guard(place=None):
"""
:api_attr: imperative
This context will create a dygraph context for dygraph to run, using python ``with`` statement.
Parameters:
place(fluid.CPUPlace or fluid.CUDAPlace, optional): Place to execute dygraph.
If None, the running place will be determined according to the way of paddle compilation. Default: None
return:
None
Examples:
.. code-block:: python
import numpy as np
import paddle.fluid as fluid
with fluid.dygraph.guard():
inp = np.ones([3, 1024], dtype='float32')
t = fluid.dygraph.base.to_variable(inp)
linear1 = fluid.Linear(1024, 4, bias_attr=False)
linear2 = fluid.Linear(4, 4)
ret = linear1(t)
dy_ret = linear2(ret)
"""
train = framework.Program()
startup = framework.Program()
tracer = Tracer()
VarBase = core.VarBase
if place is None:
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
tracer._expected_place = place
with framework.program_guard(train, startup):
with framework.unique_name.guard():
with framework._dygraph_guard(tracer):
with framework._dygraph_place_guard(place):
yield
def guard(place=None):
"""
This context will create a dygraph context for dygraph to run
Args:
place(fluid.CPUPlace|fluid.CUDAPlace|None): Place to run
return:
None
Examples:
.. code-block:: python
import numpy as np
import paddle.fluid as fluid
with fluid.dygraph.guard():
inp = np.ones([3, 32, 32], dtype='float32')
t = fluid.dygraph.base.to_variable(inp)
fc1 = fluid.FC('fc1', size=4, bias_attr=False, num_flatten_dims=1)
fc2 = fluid.FC('fc2', size=4)
ret = fc1(t)
dy_ret = fc2(ret)
"""
train = framework.Program()
startup = framework.Program()
tracer = Tracer()
if place is None:
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with framework.program_guard(train, startup):
with framework.unique_name.guard():
with framework._dygraph_guard(tracer):
with framework._dygraph_place_guard(place):
yield