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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_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_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.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.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.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b524b73e10f9ccdfa6d189e2e535fc17'))
paddle.fluid.DistributeTranspilerConfig.__init__ 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_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_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.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.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.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')) 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: Examples:
.. code-block:: python .. 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 = fluid.ExecutionStrategy()
exec_strategy.num_threads = 4 exec_strategy.num_threads = 4
train_exe = fluid.ParallelExecutor(use_cuda=True, train_exe = fluid.ParallelExecutor(use_cuda=False,
loss_name=loss.name, loss_name=avg_loss.name,
exec_strategy=exec_strategy) exec_strategy=exec_strategy)
train_loss, = train_exe.run([loss.name], feed=feed_dict)
)DOC"); )DOC");
exec_strategy.def(py::init()) exec_strategy.def(py::init())

1
python/paddle/fluid/initializer.py
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@ -824,6 +824,7 @@ class NumpyArrayInitializer(Initializer):
Examples: Examples:
.. code-block:: python .. code-block:: python
x = fluid.layers.data(name="x", shape=[5], dtype='float32')
fc = fluid.layers.fc(input=x, size=10, fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.NumpyArrayInitializer(numpy.array([1,2]))) 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 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. 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 slice_var_up = True
@ -181,13 +186,23 @@ class DistributeTranspiler(object):
Examples: Examples:
.. code-block:: python .. 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 # for pserver mode
pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174" pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
trainer_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" current_endpoint = "192.168.0.1:6174"
trainer_id = 0 trainer_id = 0
trainers = 4 trainers = 4
role = os.getenv("PADDLE_TRAINING_ROLE") role = "PSERVER"
t = fluid.DistributeTranspiler() t = fluid.DistributeTranspiler()
t.transpile( t.transpile(
trainer_id, pservers=pserver_endpoints, trainers=trainers) trainer_id, pservers=pserver_endpoints, trainers=trainers)
@ -199,14 +214,17 @@ class DistributeTranspiler(object):
trainer_program = t.get_trainer_program() trainer_program = t.get_trainer_program()
# for nccl2 mode # for nccl2 mode
trainer_num = 2
trainer_id = 0
config = fluid.DistributeTranspilerConfig() config = fluid.DistributeTranspilerConfig()
config.mode = "nccl2" config.mode = "nccl2"
trainer_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
t = fluid.DistributeTranspiler(config=config) 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( exe = fluid.ParallelExecutor(
use_cuda, use_cuda=True,
loss_name=loss_var.name, loss_name=avg_loss.name,
num_trainers=len(trainers.split(",)), num_trainers=trainer_num,
trainer_id=trainer_id trainer_id=trainer_id
) )
""" """
@ -289,7 +307,7 @@ class DistributeTranspiler(object):
startup_program=None, startup_program=None,
current_endpoint="127.0.0.1:6174"): current_endpoint="127.0.0.1:6174"):
""" """
Run the transpiler. Run the transpiler. Transpile the input program.
Args: Args:
trainer_id (int): id for current trainer worker, if you have 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 current_endpoint (str): need pass current endpoint when
transpile as nccl2 distributed mode. In pserver mode transpile as nccl2 distributed mode. In pserver mode
this argument is not used. 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: if program is None:
program = default_main_program() program = default_main_program()

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