paddle 基础函数 conv2d 卷积操作

官方文档：https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/conv2d_cn.html

 

示例：

import paddle.fluid as fluid
import numpy as np

data = fluid.data(name='data', shape=[-1, 3, 4, 4], dtype='float32')
param_attr = fluid.ParamAttr(name='conv2d.weight', \
                             initializer=fluid.initializer.Xavier(uniform=False), \
                             learning_rate=0.001)
res = fluid.layers.conv2d(input=data, num_filters=5, filter_size=3, act="relu", param_attr=param_attr)

place = fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())

x = np.random.rand(2, 3, 4, 4).astype("float32")
print(x)
output = exe.run(feed={"data": x}, fetch_list=[res])
print(output)

结果：

[[[[0.5087496  0.7041155  0.803204   0.7463352 ]
   [0.7735792  0.6693252  0.9050084  0.66902024]
   [0.61370426 0.8947696  0.10490164 0.23426855]
   [0.03776363 0.9701155  0.16354166 0.03877337]]

  [[0.43141097 0.4325962  0.7552632  0.4175699 ]
   [0.82959193 0.29775426 0.11804868 0.98603547]
   [0.47543335 0.67431146 0.33452708 0.30459923]
   [0.8601018  0.4596342  0.73562324 0.02880552]]

  [[0.6077263  0.2229377  0.08738393 0.3110199 ]
   [0.9336773  0.16735514 0.38200915 0.07737117]
   [0.37466565 0.91293067 0.83331645 0.6757968 ]
   [0.89134467 0.39544025 0.74072474 0.9375356 ]]]


 [[[0.23173703 0.39239067 0.8614188  0.6754454 ]
   [0.9554946  0.8584714  0.2632353  0.2825664 ]
   [0.21315546 0.8459132  0.2556982  0.26026046]
   [0.91332084 0.45665127 0.91489136 0.04556087]]

  [[0.22302757 0.26607528 0.7861403  0.87475955]
   [0.90069216 0.5976185  0.32480258 0.12278948]
   [0.55071807 0.7877879  0.37637177 0.00199596]
   [0.2452881  0.9161675  0.5198959  0.81285113]]

  [[0.8335489  0.03425184 0.6305808  0.8300988 ]
   [0.20777652 0.6059211  0.93811506 0.84582675]
   [0.41290218 0.2219187  0.3509429  0.0840489 ]
   [0.9862689  0.31428847 0.29119077 0.02785959]]]]

[array([[[[0.        , 0.        ],
         [0.        , 0.        ]],

        [[0.41131574, 0.31667483],
         [0.58022946, 0.53619456]],

        [[0.        , 0.        ],
         [0.        , 0.        ]],

        [[0.6091093 , 0.5029663 ],
         [0.5317466 , 0.56629765]],

        [[0.        , 0.        ],
         [0.        , 0.        ]]],


       [[[0.        , 0.        ],
         [0.        , 0.        ]],

        [[0.42338365, 0.20286646],
         [0.        , 0.        ]],

        [[0.        , 0.        ],
         [0.        , 0.        ]],

        [[0.09722605, 0.2907472 ],
         [0.20087919, 0.14951111]],

        [[0.        , 0.        ],
         [0.        , 0.        ]]]], dtype=float32)]