Original code http://deeplearning.net/tutorial/code/hmc/hmc.py
英語での説明(Original) http://deeplearning.net/tutorial/hmc.html
import numpy
from theano import function, shared
from theano import tensor as TT
import theano
Using gpu device 0: GeForce GT 620
sharedX = lambda X, name: \
shared(numpy.asarray(X, dtype=theano.config.floatX), name=name)
運動エネルギーとハミルトニアンの式 energy_fnはポテンシャルエネルギーの式で外から入力する。
def kinetic_energy(vel):
"""Returns the kinetic energy associated with the given velocity
and mass of 1.
Parameters
----------
vel: theano matrix
Symbolic matrix whose rows are velocity vectors.
Returns
-------
return: theano vector
Vector whose i-th entry is the kinetic entry associated with vel[i].
"""
return 0.5 * (vel ** 2).sum(axis=1)
def hamiltonian(pos, vel, energy_fn):
"""
Returns the Hamiltonian (sum of potential and kinetic energy) for the given
velocity and position.
Parameters
----------
pos: theano matrix
Symbolic matrix whose rows are position vectors.
vel: theano matrix
Symbolic matrix whose rows are velocity vectors.
energy_fn: python function
Python function, operating on symbolic theano variables, used tox
compute the potential energy at a given position.
Returns
-------
return: theano vector
Vector whose i-th entry is the Hamiltonian at position pos[i] and
velocity vel[i].
"""
# assuming mass is 1
return energy_fn(pos) + kinetic_energy(vel)
変動が受理されるかどうかの判定結果を返す(普通のMCMCと同じ)。
def metropolis_hastings_accept(energy_prev, energy_next, s_rng):
"""
Performs a Metropolis-Hastings accept-reject move.
Parameters
----------
energy_prev: theano vector
Symbolic theano tensor which contains the energy associated with the
configuration at time-step t.
energy_next: theano vector
Symbolic theano tensor which contains the energy associated with the
proposed configuration at time-step t+1.
s_rng: theano.tensor.shared_randomstreams.RandomStreams
Theano shared random stream object used to generate the random number
used in proposal.
Returns
-------
return: boolean
True if move is accepted, False otherwise
"""
ediff = energy_prev - energy_next
return (TT.exp(ediff) - s_rng.uniform(size=energy_prev.shape)) >= 0
leapflog法による積分の実行 最初と最後だけ処理を外側に書いている。
ポテンシャルエネルギーenergy_fnの微分dE_dpos = TT.grad(energy_fn(pos).sum(), pos)
theano.scanは同じ式を繰り返し実行するための関数
def simulate_dynamics(initial_pos, initial_vel, stepsize, n_steps, energy_fn):
"""
Return final (position, velocity) obtained after an `n_steps` leapfrog
updates, using Hamiltonian dynamics.
Parameters
----------
initial_pos: shared theano matrix
Initial position at which to start the simulation
initial_vel: shared theano matrix
Initial velocity of particles
stepsize: shared theano scalar
Scalar value controlling amount by which to move
energy_fn: python function
Python function, operating on symbolic theano variables, used to
compute the potential energy at a given position.
Returns
-------
rval1: theano matrix
Final positions obtained after simulation
rval2: theano matrix
Final velocity obtained after simulation
"""
def leapfrog(pos, vel, step):
"""
Inside loop of Scan. Performs one step of leapfrog update, using
Hamiltonian dynamics.
Parameters
----------
pos: theano matrix
in leapfrog update equations, represents pos(t), position at time t
vel: theano matrix
in leapfrog update equations, represents vel(t - stepsize/2),
velocity at time (t - stepsize/2)
step: theano scalar
scalar value controlling amount by which to move
Returns
-------
rval1: [theano matrix, theano matrix]
Symbolic theano matrices for new position pos(t + stepsize), and
velocity vel(t + stepsize/2)
rval2: dictionary
Dictionary of updates for the Scan Op
"""
# from pos(t) and vel(t-stepsize/2), compute vel(t+stepsize/2)
dE_dpos = TT.grad(energy_fn(pos).sum(), pos)
new_vel = vel - step * dE_dpos
# from vel(t+stepsize/2) compute pos(t+stepsize)
new_pos = pos + step * new_vel
return [new_pos, new_vel], {}
# compute velocity at time-step: t + stepsize/2
initial_energy = energy_fn(initial_pos)
dE_dpos = TT.grad(initial_energy.sum(), initial_pos)
vel_half_step = initial_vel - 0.5 * stepsize * dE_dpos
# compute position at time-step: t + stepsize
pos_full_step = initial_pos + stepsize * vel_half_step
# perform leapfrog updates: the scan op is used to repeatedly compute
# vel(t + (m-1/2)*stepsize) and pos(t + m*stepsize) for m in [2,n_steps].
(all_pos, all_vel), scan_updates = theano.scan(leapfrog,
outputs_info=[
dict(initial=pos_full_step),
dict(initial=vel_half_step),
],
non_sequences=[stepsize],
n_steps=n_steps - 1)
final_pos = all_pos[-1]
final_vel = all_vel[-1]
# NOTE: Scan always returns an updates dictionary, in case the
# scanned function draws samples from a RandomStream. These
# updates must then be used when compiling the Theano function, to
# avoid drawing the same random numbers each time the function is
# called. In this case however, we consciously ignore
# "scan_updates" because we know it is empty.
assert not scan_updates
# The last velocity returned by scan is vel(t +
# (n_steps - 1 / 2) * stepsize) We therefore perform one more half-step
# to return vel(t + n_steps * stepsize)
energy = energy_fn(final_pos)
final_vel = final_vel - 0.5 * stepsize * TT.grad(energy.sum(), final_pos)
# return new proposal state
return final_pos, final_vel
速度(運動量)をランダムに初期化し、n_stepsだけ積分をsimulate_dynamicsで繰り返し、accecptを判定する。
def hmc_move(s_rng, positions, energy_fn, stepsize, n_steps):
"""
This function performs one-step of Hybrid Monte-Carlo sampling. We start by
sampling a random velocity from a univariate Gaussian distribution, perform
`n_steps` leap-frog updates using Hamiltonian dynamics and accept-reject
using Metropolis-Hastings.
Parameters
----------
s_rng: theano shared random stream
Symbolic random number generator used to draw random velocity and
perform accept-reject move.
positions: shared theano matrix
Symbolic matrix whose rows are position vectors.
energy_fn: python function
Python function, operating on symbolic theano variables, used to
compute the potential energy at a given position.
stepsize: shared theano scalar
Shared variable containing the stepsize to use for `n_steps` of HMC
simulation steps.
n_steps: integer
Number of HMC steps to perform before proposing a new position.
Returns
-------
rval1: boolean
True if move is accepted, False otherwise
rval2: theano matrix
Matrix whose rows contain the proposed "new position"
"""
# sample random velocity
initial_vel = s_rng.normal(size=positions.shape)
# perform simulation of particles subject to Hamiltonian dynamics
final_pos, final_vel = simulate_dynamics(
initial_pos=positions,
initial_vel=initial_vel,
stepsize=stepsize,
n_steps=n_steps,
energy_fn=energy_fn)
# accept/reject the proposed move based on the joint distribution
accept = metropolis_hastings_accept(
energy_prev=hamiltonian(positions, initial_vel, energy_fn),
energy_next=hamiltonian(final_pos, final_vel, energy_fn),
s_rng=s_rng)
return accept, final_pos
step幅、acceptの比率(温度?)を適応的に変えている。
def hmc_updates(positions, stepsize, avg_acceptance_rate, final_pos, accept,
target_acceptance_rate, stepsize_inc, stepsize_dec,
stepsize_min, stepsize_max, avg_acceptance_slowness):
"""This function is executed after `n_steps` of HMC sampling
(`hmc_move` function). It creates the updates dictionary used by
the `simulate` function. It takes care of updating: the position
(if the move is accepted), the stepsize (to track a given target
acceptance rate) and the average acceptance rate (computed as a
moving average).
Parameters
----------
positions: shared variable, theano matrix
Shared theano matrix whose rows contain the old position
stepsize: shared variable, theano scalar
Shared theano scalar containing current step size
avg_acceptance_rate: shared variable, theano scalar
Shared theano scalar containing the current average acceptance rate
final_pos: shared variable, theano matrix
Shared theano matrix whose rows contain the new position
accept: theano scalar
Boolean-type variable representing whether or not the proposed HMC move
should be accepted or not.
target_acceptance_rate: float
The stepsize is modified in order to track this target acceptance rate.
stepsize_inc: float
Amount by which to increment stepsize when acceptance rate is too high.
stepsize_dec: float
Amount by which to decrement stepsize when acceptance rate is too low.
stepsize_min: float
Lower-bound on `stepsize`.
stepsize_min: float
Upper-bound on `stepsize`.
avg_acceptance_slowness: float
Average acceptance rate is computed as an exponential moving average.
(1-avg_acceptance_slowness) is the weight given to the newest
observation.
Returns
-------
rval1: dictionary-like
A dictionary of updates to be used by the `HMC_Sampler.simulate`
function. The updates target the position, stepsize and average
acceptance rate.
"""
## POSITION UPDATES ##
# broadcast `accept` scalar to tensor with the same dimensions as
# final_pos.
accept_matrix = accept.dimshuffle(0, *(('x',) * (final_pos.ndim - 1)))
# if accept is True, update to `final_pos` else stay put
new_positions = TT.switch(accept_matrix, final_pos, positions)
## STEPSIZE UPDATES ##
# if acceptance rate is too low, our sampler is too "noisy" and we reduce
# the stepsize. If it is too high, our sampler is too conservative, we can
# get away with a larger stepsize (resulting in better mixing).
_new_stepsize = TT.switch(avg_acceptance_rate > target_acceptance_rate,
stepsize * stepsize_inc, stepsize * stepsize_dec)
# maintain stepsize in [stepsize_min, stepsize_max]
new_stepsize = TT.clip(_new_stepsize, stepsize_min, stepsize_max)
## ACCEPT RATE U+PDATES ##
# perform exponential moving average
mean_dtype = theano.scalar.upcast(accept.dtype, avg_acceptance_rate.dtype)
new_acceptance_rate = TT.add(
avg_acceptance_slowness * avg_acceptance_rate,
(1.0 - avg_acceptance_slowness) * accept.mean(dtype=mean_dtype))
return [(positions, new_positions),
(stepsize, new_stepsize),
(avg_acceptance_rate, new_acceptance_rate)]
HMCのクラス
hmc_moveが出力した式を hmc_updateへ入力し、式を組み立てている。その出力式をコンパイルする。 ( simulate = function([], [], updates=simulate_updates))
s_rng = TT.shared_randomstreams.RandomStreams(seed) は乱数生成器
描画(draw)はsimulation実行を含む。
class HMC_sampler(object):
"""
Convenience wrapper for performing Hybrid Monte Carlo (HMC). It creates the
symbolic graph for performing an HMC simulation (using `hmc_move` and
`hmc_updates`). The graph is then compiled into the `simulate` function, a
theano function which runs the simulation and updates the required shared
variables.
Users should interface with the sampler thorugh the `draw` function which
advances the markov chain and returns the current sample by calling
`simulate` and `get_position` in sequence.
The hyper-parameters are the same as those used by Marc'Aurelio's
'train_mcRBM.py' file (available on his personal home page).
"""
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
@classmethod
def new_from_shared_positions(cls, shared_positions, energy_fn,
initial_stepsize=0.01, target_acceptance_rate=.9, n_steps=20,
stepsize_dec=0.98,
stepsize_min=0.001,
stepsize_max=0.25,
stepsize_inc=1.02,
# used in geometric avg. 1.0 would be not moving at all
avg_acceptance_slowness=0.9,
seed=12345):
"""
:param shared_positions: theano ndarray shared var with
many particle [initial] positions
:param energy_fn:
callable such that energy_fn(positions)
returns theano vector of energies.
The len of this vector is the batchsize.
The sum of this energy vector must be differentiable (with
theano.tensor.grad) with respect to the positions for HMC
sampling to work.
"""
batchsize = shared_positions.shape[0]
# allocate shared variables
stepsize = sharedX(initial_stepsize, 'hmc_stepsize')
avg_acceptance_rate = sharedX(target_acceptance_rate,
'avg_acceptance_rate')
s_rng = TT.shared_randomstreams.RandomStreams(seed)
# define graph for an `n_steps` HMC simulation
accept, final_pos = hmc_move(
s_rng,
shared_positions,
energy_fn,
stepsize,
n_steps)
# define the dictionary of updates, to apply on every `simulate` call
simulate_updates = hmc_updates(
shared_positions,
stepsize,
avg_acceptance_rate,
final_pos=final_pos,
accept=accept,
stepsize_min=stepsize_min,
stepsize_max=stepsize_max,
stepsize_inc=stepsize_inc,
stepsize_dec=stepsize_dec,
target_acceptance_rate=target_acceptance_rate,
avg_acceptance_slowness=avg_acceptance_slowness)
# compile theano function
simulate = function([], [], updates=simulate_updates)
# create HMC_sampler object with the following attributes ...
return cls(
positions=shared_positions,
stepsize=stepsize,
stepsize_min=stepsize_min,
stepsize_max=stepsize_max,
avg_acceptance_rate=avg_acceptance_rate,
target_acceptance_rate=target_acceptance_rate,
s_rng=s_rng,
_updates=simulate_updates,
simulate=simulate)
def draw(self, **kwargs):
"""
Returns a new position obtained after `n_steps` of HMC simulation.
Parameters
----------
kwargs: dictionary
The `kwargs` dictionary is passed to the shared variable
(self.positions) `get_value()` function. For example, to avoid
copying the shared variable value, consider passing `borrow=True`.
Returns
-------
rval: numpy matrix
Numpy matrix whose of dimensions similar to `initial_position`.
"""
self.simulate()
return self.positions.get_value(borrow=False)
from IPython.display import display
from sympy.interactive import printing
printing.init_printing(use_latex='mathjax')
from __future__ import division
import sympy as sym
from sympy import *
x, y, z, mu,C= symbols("x y z mu C")
gaussian_energy(多変量正規分布)を式として入力、Testする。
def sampler_on_nd_gaussian(sampler_cls, burnin, n_samples, dim=10):
batchsize=3
rng = np.random.RandomState(123)
# Define a covariance and mu for a gaussian
mu = np.array(rng.rand(dim) * 10, dtype=theano.config.floatX)
cov = np.array(rng.rand(dim, dim), dtype=theano.config.floatX)
cov = (cov + cov.T) / 2.
cov[numpy.arange(dim), numpy.arange(dim)] = 1.0
cov_inv = linalg.inv(cov)
# Define energy function for a multi-variate Gaussian
def gaussian_energy(x):
return 0.5 * (TT.dot((x - mu), cov_inv) * (x - mu)).sum(axis=1)
# Declared shared random variable for positions
position = shared(rng.randn(batchsize, dim).astype(theano.config.floatX))
# Create HMC sampler
sampler = sampler_cls(position, gaussian_energy,
initial_stepsize=1e-3, stepsize_max=0.5)
# Start with a burn-in process
garbage = [sampler.draw() for r in xrange(burnin)] #burn-in
# Draw `n_samples`: result is a 3D tensor of dim [n_samples, batchsize, dim]
_samples = np.asarray([sampler.draw() for r in xrange(n_samples)])
# Flatten to [n_samples * batchsize, dim]
samples = _samples.T.reshape(dim, -1).T
print '****** TARGET VALUES ******'
print 'target mean:', mu
print 'target cov:\n', cov
print '****** EMPIRICAL MEAN/COV USING HMC ******'
print 'empirical mean: ', samples.mean(axis=0)
print 'empirical_cov:\n', np.cov(samples.T)
print '****** HMC INTERNALS ******'
print 'final stepsize', sampler.stepsize.get_value()
print 'final acceptance_rate', sampler.avg_acceptance_rate.get_value()
return sampler
def test_hmc():
sampler = sampler_on_nd_gaussian(HMC_sampler.new_from_shared_positions,
burnin=1000, n_samples=1000, dim=5)
assert abs(sampler.avg_acceptance_rate.get_value() -
sampler.target_acceptance_rate) < .1
assert sampler.stepsize.get_value() >= sampler.stepsize_min
assert sampler.stepsize.get_value() <= sampler.stepsize_max
targetとempiricalの平均、分散が近いことを確認する。
test_hmc()
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nvcc STDOUT tmpxft_00001668_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpbc2txg/21b45d3b456ca805c8174c0cd415d1d0.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpbc2txg/21b45d3b456ca805c8174c0cd415d1d0.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001a1c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpwhqznw/6d3d177771405c8553790efdaefe218d.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpwhqznw/6d3d177771405c8553790efdaefe218d.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001204_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxhhf5v/9545ace9247b8a41dce5d4a537389f08.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxhhf5v/9545ace9247b8a41dce5d4a537389f08.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001458_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp022tza/6abc49f260f2dc095651555016e5b8a0.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp022tza/6abc49f260f2dc095651555016e5b8a0.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001460_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmplydwbr/0ef32c1cf8d7c236d19dadf70411180e.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmplydwbr/0ef32c1cf8d7c236d19dadf70411180e.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000f2c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpn50lil/9b72d9e9a85baace3f2b14bd9b7781c6.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpn50lil/9b72d9e9a85baace3f2b14bd9b7781c6.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000013ac_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpodkazg/406131ae89134f8d170001cd441504bc.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpodkazg/406131ae89134f8d170001cd441504bc.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001418_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmprszspo/b31a6ab4861a29fd8ec22fef84c8b57c.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmprszspo/b31a6ab4861a29fd8ec22fef84c8b57c.exp を作成中 C:\Python27\lib\site-packages\theano\scan_module\scan_perform_ext.py:85: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility from scan_perform.scan_perform import * INFO (theano.gof.compilelock): Waiting for existing lock by unknown process (I am process '7336') INFO (theano.gof.compilelock): To manually release the lock, delete C:\Users\xiangze\AppData\Local\Theano\compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32\lock_dir DEBUG: nvcc STDOUT tmpxft_00001a80_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpdvbcnw/b092474c94639a3000af125668a962c0.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpdvbcnw/b092474c94639a3000af125668a962c0.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000e1c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmply_cdy/1ad2a899b94c1f6caff069faeac6d032.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmply_cdy/1ad2a899b94c1f6caff069faeac6d032.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000006c0_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmphz5miz/e3dc00dfcae861eac09e1dbcd79d00be.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmphz5miz/e3dc00dfcae861eac09e1dbcd79d00be.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001ab4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp5hxcdl/e2503a31a640e61317bdd7591f15883a.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp5hxcdl/e2503a31a640e61317bdd7591f15883a.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001ccc_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp745ogw/f09c5fa3874da6cb187bcb78b9a7d960.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp745ogw/f09c5fa3874da6cb187bcb78b9a7d960.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001e90_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpuhnjs8/348daf882bdf2f0d21d46f5fadd45e63.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpuhnjs8/348daf882bdf2f0d21d46f5fadd45e63.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000ea0_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpycpeqv/6cd8b7ed3ee0c01bdb1d3ab25d33e99d.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpycpeqv/6cd8b7ed3ee0c01bdb1d3ab25d33e99d.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001ab4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpqjinvl/9963ba5f019bfae76961610c819912a1.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpqjinvl/9963ba5f019bfae76961610c819912a1.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000011b0_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpgj1jlc/d54c2666ed4dd7f37bcdc379fc6248d8.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpgj1jlc/d54c2666ed4dd7f37bcdc379fc6248d8.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001c54_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmptelwdl/4b5032b889417fb550c256001246cdaa.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmptelwdl/4b5032b889417fb550c256001246cdaa.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001b8c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp4uglhl/5d21044a7b9bd64dda39fa9c69ed1908.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp4uglhl/5d21044a7b9bd64dda39fa9c69ed1908.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001264_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpaaaw1m/968449afc2da0f3aca289a63edeb9828.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpaaaw1m/968449afc2da0f3aca289a63edeb9828.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001b08_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxw_fuy/7b1c3d04fbd4ebac50907e840155bc66.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxw_fuy/7b1c3d04fbd4ebac50907e840155bc66.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000012b4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxazagg/bd72952f9b7815bde4a4bcb01d0cc519.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxazagg/bd72952f9b7815bde4a4bcb01d0cc519.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000fe4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpg4zgtn/03f7b5fe47452cd28bd26ced6ce904e1.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpg4zgtn/03f7b5fe47452cd28bd26ced6ce904e1.exp を作成中 DEBUG: nvcc STDOUT tmpxft_0000106c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpqxravf/f871de19cf074c767d96444cfcda3814.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpqxravf/f871de19cf074c767d96444cfcda3814.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001430_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpp3h6cy/68952e664e05c3179ad5a075bb3a038d.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpp3h6cy/68952e664e05c3179ad5a075bb3a038d.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001e2c_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpfnfyuj/95729b1fa0d9f8886050c51ba23f1dc4.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpfnfyuj/95729b1fa0d9f8886050c51ba23f1dc4.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001e98_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpkdhoal/567ef094f4b8ef2dcaed704cc1aef872.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpkdhoal/567ef094f4b8ef2dcaed704cc1aef872.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000b88_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp7imwof/f003457c35f8c7750567cdb25827cc8c.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp7imwof/f003457c35f8c7750567cdb25827cc8c.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000958_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp23ub3x/86fa8a9c974c4fbb456492979952ae1d.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp23ub3x/86fa8a9c974c4fbb456492979952ae1d.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001d44_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpznqnsk/7b65a460dfc562c82cace5913d63dfab.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpznqnsk/7b65a460dfc562c82cace5913d63dfab.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000ed4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmppirnfs/7fec88975f33b34e199845cc57f2a142.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmppirnfs/7fec88975f33b34e199845cc57f2a142.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001ba0_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxwwbf9/50bfae5a161f8119166e4bc1734ae545.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpxwwbf9/50bfae5a161f8119166e4bc1734ae545.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000f20_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpiurxxq/23f89df2058637a5410eddc1fc265588.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpiurxxq/23f89df2058637a5410eddc1fc265588.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001c48_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpid4_ww/f5f6d67d6c073bbaf0927d17d9ee26b9.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpid4_ww/f5f6d67d6c073bbaf0927d17d9ee26b9.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001f10_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpyf37ld/6000ed57bf37bb47ad0d2bc2c184c42b.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpyf37ld/6000ed57bf37bb47ad0d2bc2c184c42b.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000012a4_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpy9qcza/aac6a2728b13a008be1ca93ffffccdc9.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpy9qcza/aac6a2728b13a008be1ca93ffffccdc9.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000ee0_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpo0rbvd/6456ea7e9e64a733e2ba342ff9b4fb91.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpo0rbvd/6456ea7e9e64a733e2ba342ff9b4fb91.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001e18_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpplf7kb/ad32f95becacecb314cf78ee55605a19.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpplf7kb/ad32f95becacecb314cf78ee55605a19.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001da8_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpovkwgz/9f1f22cb2f13df9a11ea0b2884d23304.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpovkwgz/9f1f22cb2f13df9a11ea0b2884d23304.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000e94_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpypp0v9/9ca54b5b3fc607736cb6f645b2f629d5.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpypp0v9/9ca54b5b3fc607736cb6f645b2f629d5.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001d20_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpi7tsxn/afea08d6efe2c85a1669bca54080eddf.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpi7tsxn/afea08d6efe2c85a1669bca54080eddf.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00000b88_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpl_t54q/9c2a4e37bf6644ecea8a893045e5d224.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmpl_t54q/9c2a4e37bf6644ecea8a893045e5d224.exp を作成中 DEBUG: nvcc STDOUT tmpxft_000014d8_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmptfepfb/4fc5113248e1d403bfd24cb77a103834.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmptfepfb/4fc5113248e1d403bfd24cb77a103834.exp を作成中 DEBUG: nvcc STDOUT tmpxft_00001264_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp9y2s88/d9bf31d3fb63e934e726d665f63b9d7b.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp9y2s88/d9bf31d3fb63e934e726d665f63b9d7b.exp を作成中 DEBUG: nvcc STDOUT
****** TARGET VALUES ****** target mean: [ 6.96469164 2.86139345 2.26851463 5.51314783 7.19468975] target cov: [[ 1. 0.66197109 0.71141255 0.55766642 0.35753822] [ 0.66197109 1. 0.310532 0.45455486 0.37991646] [ 0.71141255 0.310532 1. 0.62800336 0.38004541] [ 0.55766642 0.45455486 0.62800336 1. 0.50807869] [ 0.35753822 0.37991646 0.38004541 0.50807869 1. ]] ****** EMPIRICAL MEAN/COV USING HMC ****** empirical mean: [ 6.94154644 2.81526279 2.26301646 5.46536922 7.19413471] empirical_cov: [[ 1.05153009 0.68393536 0.76038656 0.59930262 0.37478737] [ 0.68393536 0.97708145 0.37351452 0.48362406 0.38395561] [ 0.76038656 0.37351452 1.0379712 0.67342964 0.41529149] [ 0.59930262 0.48362406 0.67342964 1.02865042 0.53613662] [ 0.37478737 0.38395561 0.41529149 0.53613662 0.98721462]] ****** HMC INTERNALS ****** final stepsize 0.460446625948 final acceptance_rate 0.922501862049
tmpxft_000013ac_00000000-14_mod.ii c:\python27\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION ライブラリ C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp0ipxsw/c5074836466020b381dcc25dcf0e3b8b.lib とオブジェクト C:/Users/xiangze/AppData/Local/Theano/compiledir_Windows-7-6.1.7601-SP1-Intel64_Family_6_Model_58_Stepping_9_GenuineIntel-2.7.3-32/tmp0ipxsw/c5074836466020b381dcc25dcf0e3b8b.exp を作成中
****** TARGET VALUES ****** target mean: [ 6.96469164 2.86139345 2.26851463 5.51314783 7.19468975] target cov: [[ 1. 0.66197109 0.71141255 0.55766642 0.35753822] [ 0.66197109 1. 0.310532 0.45455486 0.37991646] [ 0.71141255 0.310532 1. 0.62800336 0.38004541] [ 0.55766642 0.45455486 0.62800336 1. 0.50807869] [ 0.35753822 0.37991646 0.38004541 0.50807869 1. ]] ****** EMPIRICAL MEAN/COV USING HMC ****** empirical mean: [ 6.94154644 2.81526279 2.26301646 5.46536922 7.19413471] empirical_cov: [[ 1.05153009 0.68393536 0.76038656 0.59930262 0.37478737] [ 0.68393536 0.97708145 0.37351452 0.48362406 0.38395561] [ 0.76038656 0.37351452 1.0379712 0.67342964 0.41529149] [ 0.59930262 0.48362406 0.67342964 1.02865042 0.53613662] [ 0.37478737 0.38395561 0.41529149 0.53613662 0.98721462]] ****** HMC INTERNALS ****** final stepsize 0.460446625948 final acceptance_rate 0.922501862049