o Me@stddlZddlZddlmZddlmZddlmZm Z ddl m Z ddl m Z dgZe e d d d dd dZdS)N)core) LayerHelper) check_dtype check_type) deprecated) static_onlydataz2.0.0zpaddle.static.data)ZsinceZ update_tofloat32c Cstdit}t|dtjtjfdt|dttfdt|}tj t |D] }||dur4d||<q(|j |||t j jjd|dddS) a3 **Data Layer** This function creates a variable on the global block. The global variable can be accessed by all the following operators in the graph. The variable is a placeholder that could be fed with input, such as Executor can feed input into the variable. Note: `paddle.fluid.layers.data` is deprecated. It will be removed in a future version. Please use this `paddle.fluid.data`. The `paddle.fluid.layers.data` set shape and dtype at compile time but does NOT check the shape or the dtype of fed data, this `paddle.fluid.data` checks the shape and the dtype of data fed by Executor or ParallelExecutor during run time. To feed variable size inputs, users can set None or -1 on the variable dimension when using :code:`paddle.fluid.data`, or feed variable size inputs directly to :code:`paddle.fluid.layers.data` and PaddlePaddle will fit the size accordingly. The default :code:`stop_gradient` attribute of the Variable created by this API is true, which means the gradient won't be passed backward through the data Variable. Set :code:`var.stop_gradient = False` If user would like to pass backward gradient. Args: name (str): The name/alias of the variable, see :ref:`api_guide_Name` for more details. shape (list|tuple): List|Tuple of integers declaring the shape. You can set "None" or -1 at a dimension to indicate the dimension can be of any size. For example, it is useful to set changeable batch size as "None" or -1. dtype (np.dtype|VarType|str, optional): The type of the data. Supported dtype: bool, float16, float32, float64, int8, int16, int32, int64, uint8. Default: float32. lod_level (int, optional): The LoD level of the LoDTensor. Usually users don't have to set this value. For more details about when and how to use LoD level, see :ref:`user_guide_lod_tensor` . Default: 0. Returns: Variable: The global variable that gives access to the data. Examples: .. code-block:: python import paddle import paddle.fluid as fluid import numpy as np paddle.enable_static() # Creates a variable with fixed size [3, 2, 1] # User can only feed data of the same shape to x x = fluid.data(name='x', shape=[3, 2, 1], dtype='float32') # Creates a variable with changeable batch size -1. # Users can feed data of any batch size into y, # but size of each data sample has to be [2, 1] y = fluid.data(name='y', shape=[-1, 2, 1], dtype='float32') z = x + y # In this example, we will feed x and y with np-ndarray "1" # and fetch z, like implementing "1 + 1 = 2" in PaddlePaddle feed_data = np.ones(shape=[3, 2, 1], dtype=np.float32) exe = fluid.Executor(fluid.CPUPlace()) out = exe.run(fluid.default_main_program(), feed={ 'x': feed_data, 'y': feed_data }, fetch_list=[z.name]) # np-ndarray of shape=[3, 2, 1], dtype=float32, whose elements are 2 print(out) r nameshapeNT)r r dtypetypeZ stop_gradient lod_levelZis_dataZneed_check_feed)r )rlocalsrsix binary_type text_typelisttuplemovesrangelenZcreate_global_variablerZVarDescZVarTypeZ LOD_TENSOR)r r rrhelperirAD:\Projects\ConvertPro\env\Lib\site-packages\paddle/fluid/data.pyr s"Q )r r)numpynprZ paddle.fluidrZpaddle.fluid.layer_helperrZpaddle.fluid.data_feederrrutilsrZpaddle.fluid.frameworkr__all__r rrrrs