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Niketan Pansare updated SYSTEMML-547: ------------------------------------- Assignee: Nakul Jindal > Implement built-in functions for max and average pooling > -------------------------------------------------------- > > Key: SYSTEMML-547 > URL: https://issues.apache.org/jira/browse/SYSTEMML-547 > Project: SystemML > Issue Type: New Feature > Components: Parser, Runtime > Reporter: Niketan Pansare > Assignee: Nakul Jindal > Priority: Minor > Original Estimate: 168h > Remaining Estimate: 168h > > pool2d(input, pool_size, stride_length, border_mode="valid", pool_mode="max") > Performs downscaling of the input matrix. > The arguments to this function are: > 1. input is a 2-dimensional matrix. > 2. pool_size is a required integer parameter. > 3. stride_length is an optional Int parameter. The default value is 1. > 4. border_mode is an optional String parameter. The valid values are "same" > and "valid". > 5. pool_mode is an optional String parameter. The valid values are "max" and > "avg". We can later add additional operators here (such as sum). > For detailed documentation, see Theano's pool_2d function: > https://github.com/Theano/Theano/blob/master/theano/tensor/signal/pool.py#L40 > An an example, our pool2d(input=X, pool_size=2, stride_length=1, > border_mode="valid", pool_mode="avg") invocation is similar to Theano's > pool_2d(X, ds=(2,2), st=(1,1), ignore_border=True, padding=(0, 0), > mode="average_exc_pad") > Since padding=(0,0) is the most common padding (probably the only one most > people will use), I thought of simplifying the interface by borrowing > concepts from TensorFlow's functions max_pool and avg_pool. See > https://www.tensorflow.org/versions/r0.7/api_docs/python/nn.html#avg_pool > The above example will translate into following TensorFlow code: > tf.nn.avg_pool(X, pool_size=(1,2,2,1), strides=(1,1,1,1), padding="VALID") > Another good reference to understanding pooling operation is > http://cs231n.github.io/convolutional-networks/#pool > [~mwdus...@us.ibm.com], [~nakul02], [~prithvi_r_s], [~reinw...@us.ibm.com] -- This message was sent by Atlassian JIRA (v6.3.4#6332)