提交 3829eac2 编写于 作者: D dongdaxiang

fix API spec about infer_from_dataset

test=develop
上级 87027a2e
...@@ -15,9 +15,9 @@ paddle.fluid.cpu_places (ArgSpec(args=['device_count'], varargs=None, keywords=N ...@@ -15,9 +15,9 @@ paddle.fluid.cpu_places (ArgSpec(args=['device_count'], varargs=None, keywords=N
paddle.fluid.cuda_pinned_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd0c3ebd813c39958c92b78e3eef7e912')) paddle.fluid.cuda_pinned_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd0c3ebd813c39958c92b78e3eef7e912'))
paddle.fluid.Executor.__init__ (ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.Executor.__init__ (ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.Executor.close (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'f5369953dd0c443961cf79f7a00e1a03')) paddle.fluid.Executor.close (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'f5369953dd0c443961cf79f7a00e1a03'))
paddle.fluid.Executor.infer_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', '961c7c79758bed3caf0eb275474a15da')) paddle.fluid.Executor.infer_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', '43f35c287262edff30258b81bfe99203'))
paddle.fluid.Executor.run (ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False)), ('document', 'f482e93b38b4018796969a2e1dde479d')) paddle.fluid.Executor.run (ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False)), ('document', 'f482e93b38b4018796969a2e1dde479d'))
paddle.fluid.Executor.train_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', '3d553eeda32fa9dd367cc5df316bf076')) paddle.fluid.Executor.train_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', 'd521011d79e71080fe9b5bb179b43518'))
paddle.fluid.global_scope (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'e148d3ab1ed8edf3e928212a375959c0')) paddle.fluid.global_scope (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'e148d3ab1ed8edf3e928212a375959c0'))
paddle.fluid.scope_guard (ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None), ('document', 'b94d1f6bcc29c4fb58fc0058561250c2')) paddle.fluid.scope_guard (ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None), ('document', 'b94d1f6bcc29c4fb58fc0058561250c2'))
paddle.fluid.DistributeTranspiler.__init__ (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.DistributeTranspiler.__init__ (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
...@@ -495,9 +495,10 @@ paddle.fluid.regularizer.L1DecayRegularizer.__init__ (ArgSpec(args=['self', 'reg ...@@ -495,9 +495,10 @@ paddle.fluid.regularizer.L1DecayRegularizer.__init__ (ArgSpec(args=['self', 'reg
paddle.fluid.regularizer.L2DecayRegularizer.__init__ (ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.regularizer.L2DecayRegularizer.__init__ (ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.LoDTensor.__init__ 1. __init__(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None 2. __init__(self: paddle.fluid.core.LoDTensor) -> None paddle.fluid.LoDTensor.__init__ 1. __init__(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None 2. __init__(self: paddle.fluid.core.LoDTensor) -> None
paddle.fluid.LoDTensor.has_valid_recursive_sequence_lengths has_valid_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> bool paddle.fluid.LoDTensor.has_valid_recursive_sequence_lengths has_valid_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> bool
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CPUPlace) -> None 9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPlace) -> None 10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None 11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None 12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None 13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None 14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None 15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None 16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPlace) -> None 17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None 18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None 19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None 20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None 21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None 22. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None 23. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPinnedPlace) -> None 24. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPinnedPlace) -> None
paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, lod: List[List[int]]) -> None
paddle.fluid.LoDTensor.lod lod(self: paddle.fluid.core.LoDTensor) -> List[List[int]] paddle.fluid.LoDTensor.lod lod(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.recursive_sequence_lengths recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> List[List[int]] paddle.fluid.LoDTensor.recursive_sequence_lengths recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CPUPlace) -> None 9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPlace) -> None 10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None 11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None 12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None 13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None 14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None 15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None 16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPlace) -> None 17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None 18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None 19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None 20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None 21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None 22. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None 23. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPinnedPlace) -> None 24. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPinnedPlace) -> None
paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, lod: List[List[int]]) -> None paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, lod: List[List[int]]) -> None
paddle.fluid.LoDTensor.set_recursive_sequence_lengths set_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor, recursive_sequence_lengths: List[List[int]]) -> None paddle.fluid.LoDTensor.set_recursive_sequence_lengths set_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor, recursive_sequence_lengths: List[List[int]]) -> None
paddle.fluid.LoDTensor.shape shape(self: paddle.fluid.core.Tensor) -> List[int] paddle.fluid.LoDTensor.shape shape(self: paddle.fluid.core.Tensor) -> List[int]
......
...@@ -220,9 +220,11 @@ class InMemoryDataset(DatasetBase): ...@@ -220,9 +220,11 @@ class InMemoryDataset(DatasetBase):
def global_shuffle(self, fleet=None): def global_shuffle(self, fleet=None):
""" """
Global shuffle. Global shuffle.
If you run distributed, you should pass fleet instead of None. Global shuffle can be used only in distributed mode. i.e. multiple
processes on single machine or multiple machines training together.
If you run in distributed mode, you should pass fleet instead of None.
Example: Examples:
>>> import paddle.fluid as fluid >>> import paddle.fluid as fluid
>>> import paddle.fluid.incubate.fleet.parameter_server as fleet >>> import paddle.fluid.incubate.fleet.parameter_server as fleet
>>> dataset = fluid.DatasetFactory.create_dataset("InMemoryDataset") >>> dataset = fluid.DatasetFactory.create_dataset("InMemoryDataset")
......
...@@ -11,7 +11,6 @@ ...@@ -11,7 +11,6 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
import sys
__all__ = ['DeviceWorker', 'Hogwild', 'DownpourSGD'] __all__ = ['DeviceWorker', 'Hogwild', 'DownpourSGD']
...@@ -117,7 +116,7 @@ class DownpourSGD(DeviceWorker): ...@@ -117,7 +116,7 @@ class DownpourSGD(DeviceWorker):
program_id = str(id(self.program_)) program_id = str(id(self.program_))
if self.program_ == None: if self.program_ == None:
print("program of current device worker is not configured") print("program of current device worker is not configured")
sys.exit(-1) exit(-1)
opt_info = self.program_._fleet_opt opt_info = self.program_._fleet_opt
program_configs = opt_info["program_configs"] program_configs = opt_info["program_configs"]
downpour = trainer_desc.downpour_param downpour = trainer_desc.downpour_param
......
...@@ -112,30 +112,6 @@ class DownpourServer(Server): ...@@ -112,30 +112,6 @@ class DownpourServer(Server):
fea_dim += reduce(lambda x, y: x * y, param.shape, 1) fea_dim += reduce(lambda x, y: x * y, param.shape, 1)
table.accessor.fea_dim = fea_dim table.accessor.fea_dim = fea_dim
def add_data_norm_table(self, table_id, learning_rate, param_var, grad_var):
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
param_var(list): all dense param. it is a list.
grad_var(list): all dense grad parm it is a list.
Returns:
return None
"""
table = self.server_.downpour_server_param.downpour_table_param.add()
table.table_id = table_id
table.table_class = "DownpourDenseTable"
table.type = pslib.PS_DENSE_TABLE
table.accessor.accessor_class = "DownpourDenseValueAccessor"
table.accessor.dense_sgd_param.name = "summary"
table.accessor.dense_sgd_param.summary.summary_decay_rate = 0.999999
fea_dim = 0
for param in filter(lambda x: x.name.find("embedding") == -1,
param_var):
fea_dim += reduce(lambda x, y: x * y, param.shape, 1)
table.accessor.fea_dim = fea_dim
def get_desc(self): def get_desc(self):
""" """
Return downpour server program_desc Return downpour server program_desc
......
...@@ -676,16 +676,16 @@ class Executor(object): ...@@ -676,16 +676,16 @@ class Executor(object):
if not provided, then default_main_program (not compiled) will be used. if not provided, then default_main_program (not compiled) will be used.
dataset(paddle.fluid.Dataset): dataset created outside this function, dataset(paddle.fluid.Dataset): dataset created outside this function,
a user should provide a well-defined dataset before calling this function. a user should provide a well-defined dataset before calling this function.
Please check the document of Dataset if needed. Please check the document of Dataset if needed. default is None
scope(Scope): the scope used to run this program, you can switch it to different scope scope(Scope): the scope used to run this program, you can switch it to different scope
for each run. default is global_scope for each run. default is global_scope
thread(int): number of thread a user wants to run in this function. The actual number thread(int): number of thread a user wants to run in this function. The actual number
of thread will be min(Dataset.thread_num, thread) of thread will be min(Dataset.thread_num, thread) if thread > 0, default is 0
debug(bool): whether a user wants to run infer_from_dataset debug(bool): whether a user wants to run infer_from_dataset, default is False
fetch_list(Variable List): fetch variable list, each variable fetch_list(Variable List): fetch variable list, each variable
will be printed during training will be printed during training, default is None
fetch_info(String List): print information for each variable fetch_info(String List): print information for each variable, default is None
print_period(int): the number of mini-batches for each print print_period(int): the number of mini-batches for each print, default is 100
Returns: Returns:
None None
...@@ -693,6 +693,7 @@ class Executor(object): ...@@ -693,6 +693,7 @@ class Executor(object):
Examples: Examples:
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
place = fluid.CPUPlace() place = fluid.CPUPlace()
exe = fluid.Executor(place) exe = fluid.Executor(place)
...@@ -707,6 +708,9 @@ class Executor(object): ...@@ -707,6 +708,9 @@ class Executor(object):
dataset=dataset) dataset=dataset)
""" """
if dataset == None:
raise RuntimeError("dataset is needed and should be initialized")
if self.place == paddle.fluid.CUDAPlace(): if self.place == paddle.fluid.CUDAPlace():
raise RuntimeError("infer_from_dataset is verified on CPUPlace" raise RuntimeError("infer_from_dataset is verified on CPUPlace"
"We will open CUDAPlace in the future") "We will open CUDAPlace in the future")
...@@ -788,6 +792,9 @@ class Executor(object): ...@@ -788,6 +792,9 @@ class Executor(object):
dataset=dataset) dataset=dataset)
""" """
if dataset == None:
raise RuntimeError("dataset is need and should be initialized")
if self.place == paddle.fluid.CUDAPlace(): if self.place == paddle.fluid.CUDAPlace():
raise RuntimeError("train_from_dataset is verified on CPUPlace" raise RuntimeError("train_from_dataset is verified on CPUPlace"
"We will open CUDAPlace in the future") "We will open CUDAPlace in the future")
......
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