diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index ba2e3007aa002c7ccac992b66110cd275f365b9e..0b3e428b2217eeddc024bcc277d79107227b6035 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -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.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.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.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.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')) @@ -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.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.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.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_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] diff --git a/python/paddle/fluid/dataset.py b/python/paddle/fluid/dataset.py index fae4d5c73f2d330109d03265fe5d4287c0abfbb8..e90c36da9aa5cb88a34cbdd5e8486143d3e885ef 100644 --- a/python/paddle/fluid/dataset.py +++ b/python/paddle/fluid/dataset.py @@ -220,9 +220,11 @@ class InMemoryDataset(DatasetBase): def global_shuffle(self, fleet=None): """ 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.incubate.fleet.parameter_server as fleet >>> dataset = fluid.DatasetFactory.create_dataset("InMemoryDataset") diff --git a/python/paddle/fluid/device_worker.py b/python/paddle/fluid/device_worker.py index 21d50749f6cdcf9c3fa13e687d59ada67334355d..43d07637b9d612e0ea1842f267b69e9066cff703 100644 --- a/python/paddle/fluid/device_worker.py +++ b/python/paddle/fluid/device_worker.py @@ -11,7 +11,6 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -import sys __all__ = ['DeviceWorker', 'Hogwild', 'DownpourSGD'] @@ -117,7 +116,7 @@ class DownpourSGD(DeviceWorker): program_id = str(id(self.program_)) if self.program_ == None: print("program of current device worker is not configured") - sys.exit(-1) + exit(-1) opt_info = self.program_._fleet_opt program_configs = opt_info["program_configs"] downpour = trainer_desc.downpour_param diff --git a/python/paddle/fluid/distributed/node.py b/python/paddle/fluid/distributed/node.py index 60035b6e8da3e40158f8be0bafdd911f6bd6f543..41e0d64e0b788b0e354f7635c3d3e52d6bba7e23 100644 --- a/python/paddle/fluid/distributed/node.py +++ b/python/paddle/fluid/distributed/node.py @@ -112,30 +112,6 @@ class DownpourServer(Server): fea_dim += reduce(lambda x, y: x * y, param.shape, 1) 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): """ Return downpour server program_desc diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py index fb0b45581b7e4f542cd1da8615c1f3b3756dd6ad..76f06023c80e0b5c4d17083a317b3500ea0d924e 100644 --- a/python/paddle/fluid/executor.py +++ b/python/paddle/fluid/executor.py @@ -676,16 +676,16 @@ class Executor(object): if not provided, then default_main_program (not compiled) will be used. dataset(paddle.fluid.Dataset): dataset created outside 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 for each run. default is global_scope 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) - debug(bool): whether a user wants to run infer_from_dataset + 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, default is False fetch_list(Variable List): fetch variable list, each variable - will be printed during training - fetch_info(String List): print information for each variable - print_period(int): the number of mini-batches for each print + will be printed during training, default is None + fetch_info(String List): print information for each variable, default is None + print_period(int): the number of mini-batches for each print, default is 100 Returns: None @@ -693,6 +693,7 @@ class Executor(object): Examples: .. code-block:: python + import paddle.fluid as fluid place = fluid.CPUPlace() exe = fluid.Executor(place) @@ -707,6 +708,9 @@ class Executor(object): dataset=dataset) """ + if dataset == None: + raise RuntimeError("dataset is needed and should be initialized") + if self.place == paddle.fluid.CUDAPlace(): raise RuntimeError("infer_from_dataset is verified on CPUPlace" "We will open CUDAPlace in the future") @@ -788,6 +792,9 @@ class Executor(object): dataset=dataset) """ + if dataset == None: + raise RuntimeError("dataset is need and should be initialized") + if self.place == paddle.fluid.CUDAPlace(): raise RuntimeError("train_from_dataset is verified on CPUPlace" "We will open CUDAPlace in the future")