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fix distribute doc test=develop (#17318)

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* fix distribute doc
fix_ema
Qiao Longfei 6 years ago committed by GitHub
parent c1aae8b8d2
commit 92e7d5d7cc
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4 changed files with 50 additions and 12 deletions
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4
paddle/fluid/API.spec
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@ -26,7 +26,7 @@ paddle.fluid.DistributeTranspiler.get_pserver_program (ArgSpec(args=['self', 'en
paddle.fluid.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', '78f4949aedf317666a89ca74b3748ba8'))
paddle.fluid.DistributeTranspiler.get_startup_program (ArgSpec(args=['self', 'endpoint', 'pserver_program', 'startup_program'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'd796fc0c8d51503b556fcf6dc15c4f0c'))
paddle.fluid.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '736330e31a7a54abccc0c7fd9119d9ff'))
paddle.fluid.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '06ce55338dfe96311ad1078235ab3bf4'))
paddle.fluid.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '418c7e8b268e9be4104f2809e654c2f7'))
paddle.fluid.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, False)), ('document', '97fdf61cf1ed4fb8f6a4b58aebce26a2'))
paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b524b73e10f9ccdfa6d189e2e535fc17'))
paddle.fluid.DistributeTranspilerConfig.__init__
@ -427,7 +427,7 @@ paddle.fluid.transpiler.DistributeTranspiler.get_pserver_program (ArgSpec(args=[
paddle.fluid.transpiler.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', '78f4949aedf317666a89ca74b3748ba8'))
paddle.fluid.transpiler.DistributeTranspiler.get_startup_program (ArgSpec(args=['self', 'endpoint', 'pserver_program', 'startup_program'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'd796fc0c8d51503b556fcf6dc15c4f0c'))
paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '736330e31a7a54abccc0c7fd9119d9ff'))
paddle.fluid.transpiler.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '06ce55338dfe96311ad1078235ab3bf4'))
paddle.fluid.transpiler.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '418c7e8b268e9be4104f2809e654c2f7'))
paddle.fluid.transpiler.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, False)), ('document', '97fdf61cf1ed4fb8f6a4b58aebce26a2'))
paddle.fluid.transpiler.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b524b73e10f9ccdfa6d189e2e535fc17'))
paddle.fluid.transpiler.HashName.__init__ (ArgSpec(args=['self', 'pserver_endpoints'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))

16
paddle/fluid/pybind/pybind.cc
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@ -1209,15 +1209,23 @@ All parameter, weight, gradient are variables in Paddle.
Examples:
.. code-block:: python
x = fluid.layers.data(name='x', shape=[13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, act=None)
cost = fluid.layers.square_error_cost(input=y_predict, label=y)
avg_loss = fluid.layers.mean(cost)
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
sgd_optimizer.minimize(avg_loss)
exec_strategy = fluid.ExecutionStrategy()
exec_strategy.num_threads = 4
train_exe = fluid.ParallelExecutor(use_cuda=True,
loss_name=loss.name,
train_exe = fluid.ParallelExecutor(use_cuda=False,
loss_name=avg_loss.name,
exec_strategy=exec_strategy)
train_loss, = train_exe.run([loss.name], feed=feed_dict)
)DOC");
exec_strategy.def(py::init())

1
python/paddle/fluid/initializer.py
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@ -824,6 +824,7 @@ class NumpyArrayInitializer(Initializer):
Examples:
.. code-block:: python
x = fluid.layers.data(name="x", shape=[5], dtype='float32')
fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.NumpyArrayInitializer(numpy.array([1,2])))
"""

41
python/paddle/fluid/transpiler/distribute_transpiler.py
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@ -146,6 +146,11 @@ class DistributeTranspilerConfig(object):
We can use bandwidth effiently when data size is larger than 2MB.If you
want to change it, please be sure you have read the slice_variable function.
Examples:
.. code-block:: python
config = fluid.DistributeTranspilerConfig()
config.slice_var_up = True
"""
slice_var_up = True
@ -181,13 +186,23 @@ class DistributeTranspiler(object):
Examples:
.. code-block:: python
x = fluid.layers.data(name='x', shape=[13], dtype='float32')
y = fluid.layers.data(name='y', shape=[1], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, act=None)
cost = fluid.layers.square_error_cost(input=y_predict, label=y)
avg_loss = fluid.layers.mean(cost)
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
sgd_optimizer.minimize(avg_loss)
# for pserver mode
pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
trainer_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
current_endpoint = "192.168.0.1:6174"
trainer_id = 0
trainers = 4
role = os.getenv("PADDLE_TRAINING_ROLE")
role = "PSERVER"
t = fluid.DistributeTranspiler()
t.transpile(
trainer_id, pservers=pserver_endpoints, trainers=trainers)
@ -199,14 +214,17 @@ class DistributeTranspiler(object):
trainer_program = t.get_trainer_program()
# for nccl2 mode
trainer_num = 2
trainer_id = 0
config = fluid.DistributeTranspilerConfig()
config.mode = "nccl2"
trainer_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
t = fluid.DistributeTranspiler(config=config)
t.transpile(trainer_id, workers=workers, current_endpoint=curr_ep)
t.transpile(trainer_id=trainer_id, trainers=trainer_endpoints, current_endpoint="192.168.0.1:6174")
exe = fluid.ParallelExecutor(
use_cuda,
loss_name=loss_var.name,
num_trainers=len(trainers.split(",)),
use_cuda=True,
loss_name=avg_loss.name,
num_trainers=trainer_num,
trainer_id=trainer_id
)
"""
@ -289,7 +307,7 @@ class DistributeTranspiler(object):
startup_program=None,
current_endpoint="127.0.0.1:6174"):
"""
Run the transpiler.
Run the transpiler. Transpile the input program.
Args:
trainer_id (int): id for current trainer worker, if you have
@ -309,6 +327,17 @@ class DistributeTranspiler(object):
current_endpoint (str): need pass current endpoint when
transpile as nccl2 distributed mode. In pserver mode
this argument is not used.
Examples:
.. code-block:: python
transpiler = fluid.DistributeTranspiler()
t.transpile(
trainer_id=0,
pservers="127.0.0.1:7000,127.0.0.1:7001",
trainers=2,
sync_mode=False,
current_endpoint="127.0.0.1:7000")
"""
if program is None:
program = default_main_program()

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