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# Reference Python code:
#
# import tensorflow as tf
#
# inp = tf.placeholder(tf.float32, [1,3,3,2])
# mean = tf.math.reduce_mean(inp, keepdims=True, axis=[1,2])
#
# print(tf.get_default_graph().as_graph_def())
#
# WARNING! Below GraphDef is modified to make it easy to read
node {
name: "Placeholder"
op: "Placeholder"
attr {
key: "dtype"
value { type: DT_FLOAT }
}
attr {
key: "shape"
value {
shape {
dim { size: 1 }
dim { size: 3 }
dim { size: 3 }
dim { size: 2 }
}
}
}
}
node {
name: "Mean/reduction_indices"
op: "Const"
attr {
key: "dtype"
value { type: DT_INT32 }
}
attr {
key: "value"
value {
tensor {
dtype: DT_INT32
tensor_shape {
dim { size: 2 }
}
int_val: 1
int_val: 2
}
}
}
}
node {
name: "Mean"
op: "Mean"
input: "Placeholder"
input: "Mean/reduction_indices"
attr {
key: "T"
value { type: DT_FLOAT }
}
attr {
key: "Tidx"
value { type: DT_INT32 }
}
attr {
key: "keep_dims"
value { b: true }
}
}
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