def calc_pi_device(samples):
# Simple, array based API
# Generate uniformly distributed random numers
x = af.randu(samples)
y = af.randu(samples)
# Supports Just In Time Compilation
# The following line generates a single kernel
within_unit_circle = (x * x + y * y) < 1
# Intuitive function names
return 4 * af.count(within_unit_circle) / samples
def accuracy(predicted, target):
_, tlabels = af.imax(target, 1)
_, plabels = af.imax(predicted, 1)
return 100 * af.count(plabels == tlabels) / tlabels.elements()
def simple_algorithm(verbose = False):
display_func = _util.display_func(verbose)
print_func = _util.print_func(verbose)
a = af.randu(3, 3)
print_func(af.sum(a), af.product(a), af.min(a), af.max(a),
af.count(a), af.any_true(a), af.all_true(a))
display_func(af.sum(a, 0))
display_func(af.sum(a, 1))
display_func(af.product(a, 0))
display_func(af.product(a, 1))
display_func(af.min(a, 0))
display_func(af.min(a, 1))
display_func(af.max(a, 0))
display_func(af.max(a, 1))
display_func(af.count(a, 0))
display_func(af.count(a, 1))
display_func(af.any_true(a, 0))
display_func(af.any_true(a, 1))
display_func(af.all_true(a, 0))
display_func(af.all_true(a, 1))
display_func(af.accum(a, 0))
display_func(af.accum(a, 1))
display_func(af.sort(a, is_ascending=True))
display_func(af.sort(a, is_ascending=False))
b = (a > 0.1) * a
c = (a > 0.4) * a
d = b / c
print_func(af.sum(d));
print_func(af.sum(d, nan_val=0.0));
display_func(af.sum(d, dim=0, nan_val=0.0));
val,idx = af.sort_index(a, is_ascending=True)
display_func(val)
display_func(idx)
val,idx = af.sort_index(a, is_ascending=False)
display_func(val)
display_func(idx)
b = af.randu(3,3)
keys,vals = af.sort_by_key(a, b, is_ascending=True)
display_func(keys)
display_func(vals)
keys,vals = af.sort_by_key(a, b, is_ascending=False)
display_func(keys)
display_func(vals)
c = af.randu(5,1)
d = af.randu(5,1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
display_func(cc)
display_func(dd)
display_func(af.set_union(cc, dd, is_unique=True))
display_func(af.set_union(cc, dd, is_unique=False))
display_func(af.set_intersect(cc, cc, is_unique=True))
display_func(af.set_intersect(cc, cc, is_unique=False))
def accuracy2(predicted, target):
# print(plabels.dims())
# print(plabels[:, :10])
# _, tlabels = af.imax(target, 1)
return 100 * af.count(predicted == target) / target.elements()
#!/usr/bin/python
#######################################################
# Copyright (c) 2015, ArrayFire
# All rights reserved.
#
# This file is distributed under 3-clause BSD license.
# The complete license agreement can be obtained at:
# http://arrayfire.com/licenses/BSD-3-Clause
########################################################
import arrayfire as af
a = af.randu(3, 3)
print(af.sum(a), af.product(a), af.min(a), af.max(a), af.count(a),
af.any_true(a), af.all_true(a))
af.display(af.sum(a, 0))
af.display(af.sum(a, 1))
af.display(af.product(a, 0))
af.display(af.product(a, 1))
af.display(af.min(a, 0))
af.display(af.min(a, 1))
af.display(af.max(a, 0))
af.display(af.max(a, 1))
af.display(af.count(a, 0))
af.display(af.count(a, 1))
def count_nonzero(a: ndarray,
axis: tp.Optional[int] = None) \
-> tp.Union[int, ndarray]:
return _wrap_af_array(af.count(a._af_array, dim=axis))
#!/usr/bin/python import arrayfire as af a = af.randu(3, 3) print(af.sum(a), af.product(a), af.min(a), af.max(a), af.count(a), af.any_true(a), af.all_true(a)) af.print_array(af.sum(a, 0)) af.print_array(af.sum(a, 1)) af.print_array(af.product(a, 0)) af.print_array(af.product(a, 1)) af.print_array(af.min(a, 0)) af.print_array(af.min(a, 1)) af.print_array(af.max(a, 0)) af.print_array(af.max(a, 1)) af.print_array(af.count(a, 0)) af.print_array(af.count(a, 1)) af.print_array(af.any_true(a, 0)) af.print_array(af.any_true(a, 1)) af.print_array(af.all_true(a, 0)) af.print_array(af.all_true(a, 1)) af.print_array(af.accum(a, 0)) af.print_array(af.accum(a, 1))
def simple_algorithm(verbose=False):
display_func = _util.display_func(verbose)
print_func = _util.print_func(verbose)
a = af.randu(3, 3)
k = af.constant(1, 3, 3, dtype=af.Dtype.u32)
af.eval(k)
print_func(af.sum(a), af.product(a), af.min(a), af.max(a), af.count(a),
af.any_true(a), af.all_true(a))
display_func(af.sum(a, 0))
display_func(af.sum(a, 1))
rk = af.constant(1, 3, dtype=af.Dtype.u32)
rk[2] = 0
af.eval(rk)
display_func(af.sumByKey(rk, a, dim=0))
display_func(af.sumByKey(rk, a, dim=1))
display_func(af.productByKey(rk, a, dim=0))
display_func(af.productByKey(rk, a, dim=1))
display_func(af.minByKey(rk, a, dim=0))
display_func(af.minByKey(rk, a, dim=1))
display_func(af.maxByKey(rk, a, dim=0))
display_func(af.maxByKey(rk, a, dim=1))
display_func(af.anyTrueByKey(rk, a, dim=0))
display_func(af.anyTrueByKey(rk, a, dim=1))
display_func(af.allTrueByKey(rk, a, dim=0))
display_func(af.allTrueByKey(rk, a, dim=1))
display_func(af.countByKey(rk, a, dim=0))
display_func(af.countByKey(rk, a, dim=1))
display_func(af.product(a, 0))
display_func(af.product(a, 1))
display_func(af.min(a, 0))
display_func(af.min(a, 1))
display_func(af.max(a, 0))
display_func(af.max(a, 1))
display_func(af.count(a, 0))
display_func(af.count(a, 1))
display_func(af.any_true(a, 0))
display_func(af.any_true(a, 1))
display_func(af.all_true(a, 0))
display_func(af.all_true(a, 1))
display_func(af.accum(a, 0))
display_func(af.accum(a, 1))
display_func(af.scan(a, 0, af.BINARYOP.ADD))
display_func(af.scan(a, 1, af.BINARYOP.MAX))
display_func(af.scan_by_key(k, a, 0, af.BINARYOP.ADD))
display_func(af.scan_by_key(k, a, 1, af.BINARYOP.MAX))
display_func(af.sort(a, is_ascending=True))
display_func(af.sort(a, is_ascending=False))
b = (a > 0.1) * a
c = (a > 0.4) * a
d = b / c
print_func(af.sum(d))
print_func(af.sum(d, nan_val=0.0))
display_func(af.sum(d, dim=0, nan_val=0.0))
val, idx = af.sort_index(a, is_ascending=True)
display_func(val)
display_func(idx)
val, idx = af.sort_index(a, is_ascending=False)
display_func(val)
display_func(idx)
b = af.randu(3, 3)
keys, vals = af.sort_by_key(a, b, is_ascending=True)
display_func(keys)
display_func(vals)
keys, vals = af.sort_by_key(a, b, is_ascending=False)
display_func(keys)
display_func(vals)
c = af.randu(5, 1)
d = af.randu(5, 1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
display_func(cc)
display_func(dd)
display_func(af.set_union(cc, dd, is_unique=True))
display_func(af.set_union(cc, dd, is_unique=False))
display_func(af.set_intersect(cc, cc, is_unique=True))
display_func(af.set_intersect(cc, cc, is_unique=False))
