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# Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
search blog_post {
document blog_post {
field date_gmt type string {
indexing: summary
}
field language type string {
indexing: summary
}
field author type string {
indexing: summary
}
field url type string {
indexing: summary
}
field title type string {
indexing: summary | index
}
field blog type string {
indexing: summary
}
field post_id type string {
indexing: summary
}
field tags type array<string> {
indexing: summary
}
field blogname type string {
indexing: summary
}
field content type string {
indexing: summary | index
}
field categories type array<string> {
indexing: summary | index
}
field user_item_cf type tensor {
indexing: summary | attribute
attribute: tensor(user_item_cf[10])
}
field has_user_item_cf type byte {
indexing: summary | attribute
attribute: fast-search
}
}
rank-profile tensor {
first-phase {
expression {
sum(query(user_item_cf) * attribute(user_item_cf))
}
}
}
constant W_hidden {
file: constants/W_hidden.json
type: tensor(input[20],hidden[40])
}
constant b_hidden {
file: constants/b_hidden.json
type: tensor(hidden[40])
}
constant W_final {
file: constants/W_final.json
type: tensor(hidden[40], final[1])
}
constant b_final {
file: constants/b_final.json
type: tensor(final[1])
}
constant input_transform_1 {
file: constants/input_transform_1.json
type: tensor(user_item_cf[10], input[20])
}
constant input_transform_2 {
file: constants/input_transform_2.json
type: tensor(user_item_cf[10], input[20])
}
rank-profile nn_tensor {
# Why no work?
macro inline matmul(x, y, dim) {
expression: sum(x * y, dim)
}
macro matmul_user_item_cf(x, y) {
expression: sum(x * y, user_item_cf)
}
macro matmul_hidden(x, y) {
expression: sum(x * y, hidden)
}
macro matmul_input(x, y) {
expression: sum(x * y, input)
}
macro add(x,y) {
expression: x + y
}
# The input to the neural network is the concatenation of the document and query vectors
macro nn_input() {
expression {
matmul_user_item_cf(attribute(user_item_cf), constant(input_transform_1))
+
matmul_user_item_cf(query(user_item_cf), constant(input_transform_2))
}
}
macro hidden_layer() {
expression {
relu(add(matmul_input(nn_input, constant(W_hidden)), constant(b_hidden)))
# The '+' causes an error. Why?
# relu(matmul(nn_input, constant(W_hidden), "input") + constant(b_hidden))
}
}
macro final_layer() {
expression{
sigmoid(add(matmul_hidden(hidden_layer, constant(W_final)), constant(b_final)))
# Same as above
# sigmoid(matmul(hidden_layer, constant(W_final), "hidden") + constant(b_final))
}
}
first-phase {
expression: sum(query(user_item_cf) * attribute(user_item_cf))
}
second-phase {
rerank-count: 200
expression: sum(final_layer)
}
}
}
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