diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 9e1c909115f0daf7c69be82ab9caf3be53edfdf2..775429e0c0657221af8950a5acb5829be3cfde88 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -242,7 +242,7 @@ paddle.fluid.layers.open_files (ArgSpec(args=['filenames', 'shapes', 'lod_levels paddle.fluid.layers.read_file (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', '32181f6037e387fb6e68a5beaafe33b6')) paddle.fluid.layers.shuffle (ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None), ('document', 'f967a73426db26f970bc70bfb03cffca')) paddle.fluid.layers.batch (ArgSpec(args=['reader', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', 'fcb24383c6eef2ca040ee824c26e22fd')) -paddle.fluid.layers.double_buffer (ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '07e5b796674796eb1ef3fee9c10d24e3')) +paddle.fluid.layers.double_buffer (ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'c13b8a8521bea5f8123b925ae2a5d5db')) paddle.fluid.layers.random_data_generator (ArgSpec(args=['low', 'high', 'shapes', 'lod_levels', 'for_parallel'], varargs=None, keywords=None, defaults=(True,)), ('document', '9b7f0f86ec24bbc97643cadcb6499cff')) paddle.fluid.layers.py_reader (ArgSpec(args=['capacity', 'shapes', 'dtypes', 'lod_levels', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', '5c54493d96c7e0760dc6758af1c8dd72')) paddle.fluid.layers.create_py_reader_by_data (ArgSpec(args=['capacity', 'feed_list', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, True)), ('document', 'b42332b894e1e0962c6a43f0151c2640')) diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index af9b27533dab9ffca56be3ff2ef4cbfb0aec2285..67496d738f6f5df41379226a20db010f7b2dbe17 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -1334,14 +1334,9 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python - build_strategy = fluid.BuildStrategy() - build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce - - train_exe = fluid.ParallelExecutor(use_cuda=True, - loss_name=loss.name, - build_strategy=build_strategy) - - train_loss, = train_exe.run([loss.name], feed=feed_dict) + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce )DOC"); py::enum_(build_strategy, "ReduceStrategy") @@ -1363,11 +1358,19 @@ All parameter, weight, gradient are variables in Paddle. self.reduce_ = strategy; }, R"DOC(The type is STR, there are two reduce strategies in ParallelExecutor, - 'AllReduce' and 'Reduce'. If you want that all the parameters' - optimization are done on all devices independently, you should choose 'AllReduce'; - if you choose 'Reduce', all the parameters' optimization will be evenly distributed - to different devices, and then broadcast the optimized parameter to other devices. - In some models, `Reduce` is faster. Default 'AllReduce'. )DOC") + 'AllReduce' and 'Reduce'. If you want that all the parameters' + optimization are done on all devices independently, you should choose 'AllReduce'; + if you choose 'Reduce', all the parameters' optimization will be evenly distributed + to different devices, and then broadcast the optimized parameter to other devices. + In some models, `Reduce` is faster. Default 'AllReduce'. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce + )DOC") .def_property( "gradient_scale_strategy", [](const BuildStrategy &self) { return self.gradient_scale_; }, @@ -1377,10 +1380,18 @@ All parameter, weight, gradient are variables in Paddle. self.gradient_scale_ = strategy; }, R"DOC(The type is STR, there are three ways of defining :math:`loss@grad` in - ParallelExecutor, 'CoeffNumDevice', 'One' and 'Customized'. By default, - ParallelExecutor sets the :math:`loss@grad` according to the number of devices. - If you want to customize :math:`loss@grad`, you can choose 'Customized'. - Default 'CoeffNumDevice'.)DOC") + ParallelExecutor, 'CoeffNumDevice', 'One' and 'Customized'. By default, + ParallelExecutor sets the :math:`loss@grad` according to the number of devices. + If you want to customize :math:`loss@grad`, you can choose 'Customized'. + Default 'CoeffNumDevice'. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.gradient_scale_strategy = True + )DOC") .def_property( "debug_graphviz_path", [](const BuildStrategy &self) { return self.debug_graphviz_path_; }, @@ -1389,8 +1400,16 @@ All parameter, weight, gradient are variables in Paddle. self.debug_graphviz_path_ = path; }, R"DOC(The type is STR, debug_graphviz_path indicate the path that - writing the SSA Graph to file in the form of graphviz, you. - It is useful for debugging. Default "")DOC") + writing the SSA Graph to file in the form of graphviz. + It is useful for debugging. Default "" + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.debug_graphviz_path = "" + )DOC") .def_property( "enable_sequential_execution", [](const BuildStrategy &self) { @@ -1400,7 +1419,15 @@ All parameter, weight, gradient are variables in Paddle. PADDLE_ENFORCE(!self.IsFinalized(), "BuildStrategy is finlaized."); self.enable_sequential_execution_ = b; }, - R"DOC(The type is BOOL. If set True, the execution order of ops would be the same as what is in the program. Default False.)DOC") + R"DOC(The type is BOOL. If set True, the execution order of ops would be the same as what is in the program. Default False. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.enable_sequential_execution = True + )DOC") .def_property( "remove_unnecessary_lock", [](const BuildStrategy &self) { @@ -1410,7 +1437,15 @@ All parameter, weight, gradient are variables in Paddle. PADDLE_ENFORCE(!self.IsFinalized(), "BuildStrategy is finlaized."); self.remove_unnecessary_lock_ = b; }, - R"DOC(The type is BOOL. If set True, some locks in GPU ops would be released and ParallelExecutor would run faster. Default True.)DOC") + R"DOC(The type is BOOL. If set True, some locks in GPU ops would be released and ParallelExecutor would run faster. Default True. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.remove_unnecessary_lock = True + )DOC") .def_property( "num_trainers", [](const BuildStrategy &self) { return self.num_trainers_; }, @@ -1439,8 +1474,16 @@ All parameter, weight, gradient are variables in Paddle. self.fuse_elewise_add_act_ops_ = b; }, R"DOC(The type is BOOL, fuse_elewise_add_act_ops indicate whether - to fuse elementwise_add_op and activation_op, - it may make the execution faster. Default False)DOC") + to fuse elementwise_add_op and activation_op, + it may make the execution faster. Default False + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.fuse_elewise_add_act_ops = True + )DOC") .def_property( "fuse_relu_depthwise_conv", [](const BuildStrategy &self) { @@ -1451,10 +1494,18 @@ All parameter, weight, gradient are variables in Paddle. self.fuse_relu_depthwise_conv_ = b; }, R"DOC(The type is BOOL, fuse_relu_depthwise_conv indicate whether - to fuse relu and depthwise_conv2d, - it will save GPU memory and may make the execution faster. - This options is only available in GPU devices. - Default False.)DOC") + to fuse relu and depthwise_conv2d, + it will save GPU memory and may make the execution faster. + This options is only available in GPU devices. + Default False. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.fuse_relu_depthwise_conv = True + )DOC") .def_property( "fuse_broadcast_ops", [](const BuildStrategy &self) { return self.fuse_broadcast_ops_; }, @@ -1491,7 +1542,15 @@ All parameter, weight, gradient are variables in Paddle. Current implementation doesn't support FP16 training and CPU. And only synchronous on one machine, not all machines. - Default False)DOC") + Default False + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + build_strategy = fluid.BuildStrategy() + build_strategy.sync_batch_norm = True + )DOC") .def_property( "memory_optimize", [](const BuildStrategy &self) { return self.memory_optimize_; }, diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index db1b5599ab4650a51dee565d4f728495fdf96729..200b48978501d5406a52e1f2bcbb8fa7b801ead3 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -1055,7 +1055,8 @@ def double_buffer(reader, place=None, name=None): Examples: - >>> reader = fluid.layers.open_files(filenames=['somefile'], + >>> import paddle.fluid as fluid + >>> reader = fluid.layers.open_files(filenames=['mnist.recordio'], >>> shapes=[[-1, 784], [-1, 1]], >>> dtypes=['float32', 'int64']) >>> reader = fluid.layers.double_buffer(reader)