From 04293dc307ecc28d463b2e8664ee0a701893d625 Mon Sep 17 00:00:00 2001 From: lijianshe02 Date: Tue, 24 Sep 2019 06:14:53 +0000 Subject: [PATCH] fix Print_op api_cn docs test=develop --- doc/fluid/api_cn/layers_cn/Print_cn.rst | 54 +++++++++++++------------ 1 file changed, 29 insertions(+), 25 deletions(-) diff --git a/doc/fluid/api_cn/layers_cn/Print_cn.rst b/doc/fluid/api_cn/layers_cn/Print_cn.rst index a812a7971..40c656bc8 100644 --- a/doc/fluid/api_cn/layers_cn/Print_cn.rst +++ b/doc/fluid/api_cn/layers_cn/Print_cn.rst @@ -14,13 +14,13 @@ Print 参数： - **input** (Variable)-将要打印的Tensor - **summarize** (int)-打印Tensor中的元素数目，如果值为-1则打印所有元素 - - **message** (str)-字符串类型消息，作为前缀打印 - - **first_n** (int)-只记录first_n次数 - - **print_tensor_name** (bool)-指明是否打印Tensor名称，默认为True - - **print_tensor_type** (bool)-指明是否打印Tensor类型，默认为True - - **print_tensor_shape** (bool)-指明是否打印Tensor维度信息，默认为True - - **print_tensor_lod** (bool)-指明是否打印Tensor的lod信息，默认为True - - **print_phase** (str)-指明打印的阶段，包括 ``forward`` , ``backward`` 和 ``both`` ，默认为 ``both`` 。若设置为 ``backward`` 或者 ``both`` ,则打印输入Tensor的梯度。 + - **message** (str)-打印Tensor信息前自定义的字符串类型消息，作为前缀打印 + - **first_n** (int)-打印Tensor的次数 + - **print_tensor_name** (bool)-可选，指明是否打印Tensor名称，默认为True + - **print_tensor_type** (bool)-可选，指明是否打印Tensor类型，默认为True + - **print_tensor_shape** (bool)-可选，指明是否打印Tensor维度信息，默认为True + - **print_tensor_lod** (bool)-可选，指明是否打印Tensor的lod信息，默认为True + - **print_phase** (str)-可选，指明打印的阶段，包括 ``forward`` , ``backward`` 和 ``both`` 。默认为 ``both`` 。设置为 ``forward`` 时，只打印Tensor的前向信息；设置为 ``backward`` 时，只打印Tensor的梯度信息；设置为 ``both`` 时，则同时打印Tensor的前向信息以及梯度信息。 返回：输出Tensor @@ -34,28 +34,32 @@ Print .. code-block:: python import paddle.fluid as fluid - - input = fluid.layers.fill_constant(shape=[10,2], value=3, dtype='int64') - input = fluid.layers.Print(input, message="The content of input layer:") - - main_program = fluid.default_main_program() - exe = fluid.Executor(fluid.CPUPlace()) - exe.run(main_program) - + import paddle + import numpy as np + + x = fluid.layers.data(name='x', shape=[1], dtype='float32', lod_level=1) + x = fluid.layers.Print(x, message="The content of input layer:") + + y = fluid.layers.data(name='y', shape=[1], dtype='float32', lod_level=2) + out = fluid.layers.sequence_expand(x=x, y=y, ref_level=0) + place = fluid.CPUPlace() + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + x_d = fluid.create_lod_tensor(np.array([[1.1], [2.2],[3.3],[4.4]]).astype('float32'), [[1,3]], place) + y_d = fluid.create_lod_tensor(np.array([[1.1],[1.1],[1.1],[1.1],[1.1],[1.1]]).astype('float32'), [[1,3], [1,2,1,2]], place) + results = exe.run(fluid.default_main_program(), + feed={'x':x_d, 'y': y_d }, + fetch_list=[out],return_numpy=False) **运行输出**: .. code-block:: bash - 1564546375 输出层内容: place:CPUPlace - Tensor[fill_constant_0.tmp_0] - shape: [10,2,] - dtype: x - data: 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, - - # 不同的环境中运行时信息的类型可能不相同. - # 比如: - # 如果Tensor y dtype='int64', 相应的 c++ 类型为 int64_t. - # 在 MacOS 和 gcc4.8.2的环境中输出的dtype为 "x" ("x" is typeid(int64_t).name()) 。 + The content of input layer: The place is:CPUPlace + Tensor[x] + shape: [4,1,] + dtype: f + LoD: [[ 0,1,4, ]] + data: 1.1,2.2,3.3,4.4, -- GitLab