bayerj

[... snipped away lotsof Quadtree inserts ...]

#104785 0x00000001000021ae in QuadTree::insert (this=0x1021d6e00, new_index=553) at quadtree.cpp:154
#104786 0x0000000100002235 in QuadTree::insert (this=0x1021d6a10, new_index=553) at quadtree.cpp:157
#104787 0x00000001000021ae in QuadTree::insert (this=0x1021d6980, new_index=553) at quadtree.cpp:154
#104788 0x0000000100002235 in QuadTree::insert (this=0x1021d6590, new_index=553) at quadtree.cpp:157
#104789 0x00000001000021ae in QuadTree::insert (this=0x1021d63e0, new_index=553) at quadtree.cpp:154
#104790 0x00000001000021dc in QuadTree::insert (this=0x1021d61a0, new_index=553) at quadtree.cpp:155
#104791 0x00000001000021dc in QuadTree::insert (this=0x1021d5ff0, new_index=553) at quadtree.cpp:155
#104792 0x0000000100002207 in QuadTree::insert (this=0x1021d5e40, new_index=553) at quadtree.cpp:156

bayerj

import time

import numpy as np
from numba import jit, float64, int64


def mean_filter(X, window_size):
    filtered = np.empty(X.shape)
    starts = window_size * [0] + range(1, X.shape[0] - window_size + 1)
    for i in range(X.shape[0]):

bayerj

/Users/bayerj/devel/Theano/theano/compile/function.pyc in function(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)
    204                 allow_input_downcast=allow_input_downcast,
    205                 on_unused_input=on_unused_input,
--> 206                 profile=profile)
    207     # We need to add the flag check_aliased inputs if we have any mutable or
    208     # borrowed used defined inputs

/Users/bayerj/devel/Theano/theano/compile/pfunc.pyc in pfunc(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)
    480     return orig_function(inputs, cloned_outputs, mode,
    481             accept_inplace=accept_inplace, name=name, profile=profile,

bayerj

.../Users/bayerj/devel/Theano/theano/compile/debugmode.py:1610: UserWarning: FunctionGraph.nodes is deprecated, it has been renamed 'apply_nodes'
  e.toposort = lambda: e.nodes  # WARNING: STOCHASTIC ORDER
...........S........................K............../Users/bayerj/devel/Theano/theano/compile/tests/test_inplace_opt_for_value.py:170: UserWarning: theano modules are deprecated and will be removed in release 0.7
  super(ExampleRNN, self).__init__()
.............................................................................................WARNING (theano.gof.cmodule): Cache leak due to unpickle-able key data set([(((1,), (10, '1.8.0.dev-dff8c94'), (10, '1.8.0.dev-dff8c94')), ('CLinker.cmodule_key', ('-O3', '-Wno-unused-label', '-Wno-unused-variable', '-Wno-write-strings', '-fno-math-errno'), (), (), 'NPY_ABI_VERSION=0x1000009', 'c_compiler_str=g++ 4.2.1', 'md5:b9113ad2b1dcb7629164b394f0809469', (<theano.gof.tests.test_compute_test_value.IncOneC object at 0x109c0cb10>, ((Scalar(int32), ((-1, 0), False)),), 

bayerj

import theano
import theano.tensor as T
import gnumpy
import theano.misc.gnumpy_utils as gput

g = gnumpy.zeros((1, 2))
g += np.array([[2, 1]])

x = T.matrix()
expr = 2 * x

bayerj

def q_mult(q1, q2):
    w1, x1, y1, z1 = q1[:, 0], q1[:, 1], q1[:, 2], q1[:, 3]
    w2, x2, y2, z2 = q2[:, 0], q2[:, 1], q2[:, 2], q2[:, 3]
    w = w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2
    x = w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2
    y = w1 * y2 + y1 * w2 + z1 * x2 - x1 * z2
    z = w1 * z2 + z1 * w2 + x1 * y2 - y1 * x2
    
    if isinstance(q1, np.ndarray):
        w = w[:, np.newaxis]

bayerj

Traceback (most recent call last):
  File "theanorngclone.py", line 12, in <module>
    f = theano.function([x_sub], samples_sub)
  File "/Users/bayerj/devel/Theano/theano/compile/function.py", line 222, in function
    profile=profile)
  File "/Users/bayerj/devel/Theano/theano/compile/pfunc.py", line 506, in pfunc
    on_unused_input=on_unused_input)
  File "/Users/bayerj/devel/Theano/theano/compile/function_module.py", line 1298, in orig_function
    on_unused_input=on_unused_input).create(
  File "/Users/bayerj/devel/Theano/theano/compile/function_module.py", line 994, in __init__

bayerj

numpydoc>=0.4

bayerj

dot = (target[:, :, 3:7] * prediction[:, :, 6:10]).sum(axis=2).dimshuffle(0, 1, 'x')
dot = T.clip(dot, -.99, .99)
angle_loss = T.arccos(dot)
return  residuals ** 2 + c * angle_loss

bayerj

import theano, theano.tensor as T
from theano.tensor.shared_randomstreams import RandomStreams


def theano_expr_bfs(expr):
    stack = [expr]
    while True:
        if not stack:
            break
        expr = stack.pop()