Package vsql_core :: Package utils :: Module victor_utils

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Module victor_utils

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This module contains generic utilities that can be used by any model.

Functions

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double

dot(u, v)
Computes and returns the dot product of given two vectors

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grad(w, b, x, y)

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vector

scale(w, b)
Scales the given vector with the given scale factor and return it

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vector

scale_and_add(x, y, s)
Scales given vector y and add it to the x and return it

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double

dot_ds(dx, sy)
Computes and returns dot product of two vectors (at least one of them is sparse)

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double

sigma(v)
Returns sigma valu

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scale_i(x, c)
Scales the given vector

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scale_and_add_i(x, y, c)
Scales y and adds it to x x += y * c

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scale_and_add_ds(dx, sz, c)
Scales sz (which is sparse) and adds it to x dx += sz * c

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double

dot_dss(w, ks, vs)
Calculates and returns dot products of w and vs

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scale_and_add_dss(w, index, vectors, c)
Scales vectors and adds it to w

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l2_project(x, B)
l2 project function

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l1_shrink(x, u)
l1 shrink function

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l1_shrink_mask(x, u, indexes)
l1 shrink function

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incremental_average(w_hat, w, steps)
Incremental average function

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Function Details

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dot(u, v)

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Computes and returns the dot product of given two vectors

Parameters:

u (vector) - vector1
v (vector) - vector2

Returns: double

dot product value of the vectors

scale(w, b)

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Scales the given vector with the given scale factor and return it

Parameters:

w (vector) - vector to be scaled
b (double) - scale factor

Returns: vector

scaled vector

scale_and_add(x, y, s)

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Scales given vector y and add it to the x and return it

Parameters:

x (vector) - vector to be added with the scaled one
y (vector) - vector to be scaled
s (double) - scale factor

Returns: vector

x + y * s

dot_ds(dx, sy)

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Computes and returns dot product of two vectors (at least one of them is sparse)

Parameters:

dx (vector) - first component of the dot product
sy (vector) - second component of the dot product

Returns: double

dot product of dx and sy

sigma(v)

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Returns sigma valu

Parameters:

v (double) - v

Returns: double

sigma value of v

scale_i(x, c)

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Scales the given vector

Parameters:

x (vector) - vector to be scaled
c (double) - scale factor

scale_and_add_i(x, y, c)

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Scales y and adds it to x x += y * c

Parameters:

x (vector) - vector to be modified
y (vector) - vector to be scaled and added to x
c (double) - scale factor

scale_and_add_ds(dx, sz, c)

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Scales sz (which is sparse) and adds it to x dx += sz * c

Parameters:

dx (vector) - vector to be modified
sz (vector) - vector to be scaled and added to dx
c (double) - scale factor

dot_dss(w, ks, vs)

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Calculates and returns dot products of w and vs

Parameters:

w (vector) - first component of the dot product
ks (vector) - indexes of the sparse vector
vs (vector) - values of the sparse vector

Returns: double

dot product of two vectors

scale_and_add_dss(w, index, vectors, c)

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Scales vectors and adds it to w

Parameters:

w (vector) - vector to be modified
index (vector) - indexes of the sparse vector
vectors (vector) - values of the sparse vector
c (double) - scale factor

l2_project(x, B)

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l2 project function

Parameters:

x (vector) - x
B (double) - B

l1_shrink(x, u)

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l1 shrink function

Parameters:

x (vector) - x
u (double) - u

l1_shrink_mask(x, u, indexes)

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l1 shrink function

Parameters:

x (vector) - x
u (double) - B
indexes (vector) - indexes of the sparse vector

incremental_average(w_hat, w, steps)

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Incremental average function

Parameters:

w_hat (vector) - w hat
w (vector) - model vector
steps (number) - steps