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94 lines
3.3 KiB
94 lines
3.3 KiB
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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from . import core
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from .layer_helper import LayerHelper
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__all__ = ['data']
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def data(name, shape, dtype='float32'):
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"""
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**Data Layer**
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This function creates a variable on the global block. The global variable
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can be accessed by all the following operators in the graph. The variable
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is a placeholder that could be feeded with input, such as Executor can feed
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input into the variable.
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Note:
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`paddle.fluid.layers.data` is deprecated. It will be removed in a future
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version. Please use this `paddle.fluid.data`.
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The `paddle.fluid.layers.data` set shape and dtype at compile time but
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does NOT check the shape or the dtype of feeded data, this
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`paddle.fluid.data` checks the shape and the dtype of data feeded by
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Executor or ParallelExecutor during run time.
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Args:
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name (str): The name/alias of the variable, see :ref:`api_guide_Name`
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for more details.
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shape (list|tuple): List|Tuple of integers declaring the shape.
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dtype (np.dtype|VarType|str): The type of the data. Supported dtype:
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bool, float16, float32, float64, int8, int16, int32, int64, uint8.
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Returns:
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Variable: The global variable that gives access to the data.
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Examples:
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.. code-block:: python
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import paddle.fluid as fluid
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import numpy as np
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# Creates a variable with fixed size [3, 2, 1]
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# User can only feed data of the same shape to x
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x = fluid.data(name='x', shape=[3, 2, 1], dtype='float32')
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# Creates a variable with changable batch size -1.
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# Users can feed data of any batch size into y,
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# but size of each data sample has to be [2, 1]
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y = fluid.data(name='y', shape=[-1, 2, 1], dtype='float32')
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z = x + y
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# In this example, we will feed x and y with np-ndarry "1"
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# and fetch z, like implementing "1 + 1 = 2" in PaddlePaddle
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feed_data = np.ones(shape=[3, 2, 1], dtype=np.float32)
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exe = fluid.Executor(fluid.CPUPlace())
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out = exe.run(fluid.default_main_program(),
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feed={
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'x': feed_data,
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'y': feed_data
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},
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fetch_list=[z.name])
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# np-ndarray of shape=[3, 2, 1], dtype=float32, whose elements are 2
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print(out)
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"""
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helper = LayerHelper('data', **locals())
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return helper.create_global_variable(
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name=name,
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shape=shape,
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dtype=dtype,
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type=core.VarDesc.VarType.LOD_TENSOR,
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stop_gradient=True,
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lod_level=0,
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is_data=True,
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need_check_feed=True)
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