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# cython: boundscheck=False
# cython: wraparound=False
# cython: cdivision=True
# Author: Christopher Moody <chrisemoody@gmail.com>
# Author: Nick Travers <nickt@squareup.com>
# Implementation by Chris Moody & Nick Travers
# See http://homepage.tudelft.nl/19j49/t-SNE.html for reference
# implementations and papers describing the technique
from libc.stdlib cimport malloc, free
from libc.stdio cimport printf
from libc.math cimport sqrt, log
import numpy as np
cimport numpy as np
from sklearn.neighbors import quad_tree
from sklearn.neighbors cimport quad_tree
cdef char* EMPTY_STRING = ""
cdef extern from "math.h":
float fabsf(float x) nogil
# Smallest strictly positive value that can be represented by floating
# point numbers for different precision levels. This is useful to avoid
# taking the log of zero when computing the KL divergence.
cdef float FLOAT32_TINY = np.finfo(np.float32).tiny
# Useful to void division by zero or divergence to +inf.
cdef float FLOAT64_EPS = np.finfo(np.float64).eps
# This is effectively an ifdef statement in Cython
# It allows us to write printf debugging lines
# and remove them at compile time
cdef enum:
DEBUGFLAG = 0
cdef extern from "time.h":
# Declare only what is necessary from `tm` structure.
ctypedef long clock_t
clock_t clock() nogil
double CLOCKS_PER_SEC
cdef float compute_gradient(float[:] val_P,
float[:, :] pos_reference,
np.int64_t[:] neighbors,
np.int64_t[:] indptr,
float[:, :] tot_force,
quad_tree._QuadTree qt,
float theta,
int dof,
long start,
long stop,
bint compute_error) nogil:
# Having created the tree, calculate the gradient
# in two components, the positive and negative forces
cdef:
long i, coord
int ax
long n_samples = pos_reference.shape[0]
int n_dimensions = qt.n_dimensions
double[1] sum_Q
clock_t t1 = 0, t2 = 0
float sQ, error
int take_timing = 1 if qt.verbose > 15 else 0
if qt.verbose > 11:
printf("[t-SNE] Allocating %li elements in force arrays\n",
n_samples * n_dimensions * 2)
cdef float* neg_f = <float*> malloc(sizeof(float) * n_samples * n_dimensions)
cdef float* pos_f = <float*> malloc(sizeof(float) * n_samples * n_dimensions)
sum_Q[0] = 0.0
if take_timing:
t1 = clock()
compute_gradient_negative(pos_reference, neg_f, qt, sum_Q,
dof, theta, start, stop)
if take_timing:
t2 = clock()
printf("[t-SNE] Computing negative gradient: %e ticks\n", ((float) (t2 - t1)))
sQ = sum_Q[0]
if take_timing:
t1 = clock()
error = compute_gradient_positive(val_P, pos_reference, neighbors, indptr,
pos_f, n_dimensions, dof, sQ, start,
qt.verbose, compute_error)
if take_timing:
t2 = clock()
printf("[t-SNE] Computing positive gradient: %e ticks\n", ((float) (t2 - t1)))
for i in range(start, n_samples):
for ax in range(n_dimensions):
coord = i * n_dimensions + ax
tot_force[i, ax] = pos_f[coord] - (neg_f[coord] / sQ)
free(neg_f)
free(pos_f)
return error
cdef float compute_gradient_positive(float[:] val_P,
float[:, :] pos_reference,
np.int64_t[:] neighbors,
np.int64_t[:] indptr,
float* pos_f,
int n_dimensions,
int dof,
double sum_Q,
np.int64_t start,
int verbose,
bint compute_error) nogil:
# Sum over the following expression for i not equal to j
# grad_i = p_ij (1 + ||y_i - y_j||^2)^-1 (y_i - y_j)
# This is equivalent to compute_edge_forces in the authors' code
# It just goes over the nearest neighbors instead of all the data points
# (unlike the non-nearest neighbors version of `compute_gradient_positive')
cdef:
int ax
long i, j, k
long n_samples = indptr.shape[0] - 1
float dij, qij, pij
float C = 0.0
float exponent = (dof + 1.0) / 2.0
float float_dof = (float) (dof)
float[3] buff
clock_t t1 = 0, t2 = 0
float dt
if verbose > 10:
t1 = clock()
for i in range(start, n_samples):
# Init the gradient vector
for ax in range(n_dimensions):
pos_f[i * n_dimensions + ax] = 0.0
# Compute the positive interaction for the nearest neighbors
for k in range(indptr[i], indptr[i+1]):
j = neighbors[k]
dij = 0.0
pij = val_P[k]
for ax in range(n_dimensions):
buff[ax] = pos_reference[i, ax] - pos_reference[j, ax]
dij += buff[ax] * buff[ax]
qij = float_dof / (float_dof + dij)
if dof != 1: # i.e. exponent != 1
qij **= exponent
dij = pij * qij
# only compute the error when needed
if compute_error:
qij /= sum_Q
C += pij * log(max(pij, FLOAT32_TINY) / max(qij, FLOAT32_TINY))
for ax in range(n_dimensions):
pos_f[i * n_dimensions + ax] += dij * buff[ax]
if verbose > 10:
t2 = clock()
dt = ((float) (t2 - t1))
printf("[t-SNE] Computed error=%1.4f in %1.1e ticks\n", C, dt)
return C
cdef void compute_gradient_negative(float[:, :] pos_reference,
float* neg_f,
quad_tree._QuadTree qt,
double* sum_Q,
int dof,
float theta,
long start,
long stop) nogil:
if stop == -1:
stop = pos_reference.shape[0]
cdef:
int ax
int n_dimensions = qt.n_dimensions
long i, j, idx
long n = stop - start
long dta = 0
long dtb = 0
long offset = n_dimensions + 2
float size, dist2s, mult
float exponent = (dof + 1.0) / 2.0
float float_dof = (float) (dof)
double qijZ
float[1] iQ
float[3] force, neg_force, pos
clock_t t1 = 0, t2 = 0, t3 = 0
int take_timing = 1 if qt.verbose > 20 else 0
summary = <float*> malloc(sizeof(float) * n * offset)
for i in range(start, stop):
# Clear the arrays
for ax in range(n_dimensions):
force[ax] = 0.0
neg_force[ax] = 0.0
pos[ax] = pos_reference[i, ax]
iQ[0] = 0.0
# Find which nodes are summarizing and collect their centers of mass
# deltas, and sizes, into vectorized arrays
if take_timing:
t1 = clock()
idx = qt.summarize(pos, summary, theta*theta)
if take_timing:
t2 = clock()
# Compute the t-SNE negative force
# for the digits dataset, walking the tree
# is about 10-15x more expensive than the
# following for loop
for j in range(idx // offset):
dist2s = summary[j * offset + n_dimensions]
size = summary[j * offset + n_dimensions + 1]
qijZ = float_dof / (float_dof + dist2s) # 1/(1+dist)
if dof != 1: # i.e. exponent != 1
qijZ **= exponent
sum_Q[0] += size * qijZ # size of the node * q
mult = size * qijZ * qijZ
for ax in range(n_dimensions):
neg_force[ax] += mult * summary[j * offset + ax]
if take_timing:
t3 = clock()
for ax in range(n_dimensions):
neg_f[i * n_dimensions + ax] = neg_force[ax]
if take_timing:
dta += t2 - t1
dtb += t3 - t2
if take_timing:
printf("[t-SNE] Tree: %li clock ticks | ", dta)
printf("Force computation: %li clock ticks\n", dtb)
# Put sum_Q to machine EPSILON to avoid divisions by 0
sum_Q[0] = max(sum_Q[0], FLOAT64_EPS)
free(summary)
def gradient(float[:] val_P,
float[:, :] pos_output,
np.int64_t[:] neighbors,
np.int64_t[:] indptr,
float[:, :] forces,
float theta,
int n_dimensions,
int verbose,
int dof=1,
long skip_num_points=0,
bint compute_error=1):
# This function is designed to be called from external Python
# it passes the 'forces' array by reference and fills thats array
# up in-place
cdef float C
cdef int n
n = pos_output.shape[0]
assert val_P.itemsize == 4
assert pos_output.itemsize == 4
assert forces.itemsize == 4
m = "Forces array and pos_output shapes are incompatible"
assert n == forces.shape[0], m
m = "Pij and pos_output shapes are incompatible"
assert n == indptr.shape[0] - 1, m
if verbose > 10:
printf("[t-SNE] Initializing tree of n_dimensions %i\n", n_dimensions)
cdef quad_tree._QuadTree qt = quad_tree._QuadTree(pos_output.shape[1],
verbose)
if verbose > 10:
printf("[t-SNE] Inserting %li points\n", pos_output.shape[0])
qt.build_tree(pos_output)
if verbose > 10:
# XXX: format hack to workaround lack of `const char *` type
# in the generated C code that triggers error with gcc 4.9
# and -Werror=format-security
printf("[t-SNE] Computing gradient\n%s", EMPTY_STRING)
C = compute_gradient(val_P, pos_output, neighbors, indptr, forces,
qt, theta, dof, skip_num_points, -1, compute_error)
if verbose > 10:
# XXX: format hack to workaround lack of `const char *` type
# in the generated C code
# and -Werror=format-security
printf("[t-SNE] Checking tree consistency\n%s", EMPTY_STRING)
m = "Tree consistency failed: unexpected number of points on the tree"
assert qt.cells[0].cumulative_size == qt.n_points, m
if not compute_error:
C = np.nan
return C
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