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# HOW TO GENERATE:
#
# import tensorflow as tf
# value = tf.placeholder(dtype=tf.float32, shape=[1, 7, 7, 1], name='placeholder')
# output = tf.nn.max_pool(value, [1, 3, 3, 1], [1, 2, 2, 1], 'VALID', name='maxpool2d')
# tf.get_default_graph().as_graph_def()
#
# NOTE 1. The output shape is 1x3x3x1
#
# >>> tf.graph_util.tensor_shape_from_node_def_name(tf.get_default_graph(), 'maxpool2d')
# TensorShape([Dimension(1), Dimension(3), Dimension(3), Dimension(1)])
#
# NOTE 2. All the MaxPool nodes in inception v3 2018.04.27 use this configuration.
# - InceptionV3/InceptionV3/MaxPool_3a_3x3/MaxPool
# - InceptionV3/InceptionV3/MaxPool_5a_3x3/MaxPool
# - InceptionV3/InceptionV3/Mixed_6a/Branch_2/MaxPool_1a_3x3/MaxPool
# - InceptionV3/InceptionV3/Mixed_7a/Branch_2/MaxPool_1a_3x3/MaxPool
node {
name: "placeholder"
op: "Placeholder"
attr {
key: "dtype"
value { type: DT_FLOAT }
}
attr {
key: "shape"
value {
shape {
dim { size: 1 }
dim { size: 7 }
dim { size: 7 }
dim { size: 1 }
}
}
}
}
node {
name: "maxpool2d"
op: "MaxPool"
input: "placeholder"
attr {
key: "T"
value { type: DT_FLOAT }
}
attr {
key: "data_format"
value { s: "NHWC" }
}
attr {
key: "ksize"
value {
list { i: 1 i: 3 i: 3 i: 1 }
}
}
attr {
key: "padding"
value { s: "VALID" }
}
attr {
key: "strides"
value {
list { i: 1 i: 2 i: 2 i: 1 }
}
}
}
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