我正在尝试运行以下模型，但是在编译过程中失败：
import numpy as np
import pymc3 as pm
def sample_data(G=1, K=2):
# mean proportion ([0,1]) for each g
p_g = np.random.beta(2, 2, size=G)
# concentration around each p_g
c_g = np.random.lognormal(mean=0.5, sigma=1, size=G)
# reparameterization for standard Beta(a,b)
a_g = c_g * p_g / np.sqrt(p_g**2 + (1.-p_g)**2)
b_g = c_g*(1.-p_g) / np.sqrt(p_g**2 + (1.-p_g)**2)
# for each p_g, sample K proportions
p_gk = np.random.beta(a_g[:, np.newaxis], b_g[:, np.newaxis], size=(G, K))
return p_gk
# Data size
G = 3
K = 5
# obtain a G x K array of proportions p_gk in [0,1]
data = sample_data(G, K)
with pm.Model() as m:
# Parameters
p_g = pm.Beta('p_g', 1., 1., shape=G)
sd_g = pm.HalfNormal('sd_g', sd=1., shape=G)
# Observed proportions
p_gk = pm.Beta('p_gk', mu=p_g, sd=sd_g, shape=(G, K), observed=data)
trace = pm.sample(2000)
出现以下错误：
Exception: ("Compilation failed (return status=1):
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:400:27:
error: non-constant-expression cannot be narrowed from type 'npy_intp' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
int init_totals[2] = {V3_n0, V3_n1};.
^~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:400:27:
note: insert an explicit cast to silence this issue.
int init_totals[2] = {V3_n0, V3_n1};.
^~~~~.
static_cast<int>( ).
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:400:34:
error: non-constant-expression cannot be narrowed from type 'npy_intp' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
int init_totals[2] = {V3_n0, V3_n1};.
^~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:400:34:
note: insert an explicit cast to silence this issue.
int init_totals[2] = {V3_n0, V3_n1};.
^~~~~.
static_cast<int>( ).
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:412:9:
error: non-constant-expression cannot be narrowed from type 'ssize_t' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
V3_stride0, V3_stride1, .
^~~~~~~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:412:9:
note: insert an explicit cast to silence this issue.
V3_stride0, V3_stride1, .
^~~~~~~~~~.
static_cast<int>( ).
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:412:21:
error: non-constant-expression cannot be narrowed from type 'ssize_t' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
V3_stride0, V3_stride1, .
^~~~~~~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:412:21:
note: insert an explicit cast to silence this issue.
V3_stride0, V3_stride1, .
^~~~~~~~~~.
static_cast<int>( ).
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:413:1:
error: non-constant-expression cannot be narrowed from type 'ssize_t' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
V1_stride0, V1_stride1.
^~~~~~~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:413:1:
note: insert an explicit cast to silence this issue.
V1_stride0, V1_stride1.
^~~~~~~~~~.
static_cast<int>( ).
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:413:13:
error: non-constant-expression cannot be narrowed from type 'ssize_t' (aka 'long') to 'int' in initializer list [-Wc++11-narrowing].
V1_stride0, V1_stride1.
^~~~~~~~~~.
/Users/mfansler/.theano/compiledir_Darwin-17.6.0-x86_64-i386-64bit-i386-3.6.3-64/tmpr58gulp2/mod.cpp:413:13:
note: insert an explicit cast to silence this issue.
V1_stride0, V1_stride1.
^~~~~~~~~~.
static_cast<int>( ).
6 errors generated.. ", '[Elemwise{log,no_inplace}(TensorConstant{[[0.297343..76841722]]})]')
我是PyMC3的新手。运行现有的PyMC3示例时，我没有看到这些错误。我怀疑看到这些是因为我使用的是多维格式（即(G,K)），因为我还没有看到其他人使用此格式（可能是我对Stan的熟悉）。
通常，我很难理解如何实现具有多个维度的多级模型。
您知道什么原因导致了我看到的错误吗？
我在HPC节点（CentOS 7）上安装了相同的软件包版本（通过conda），并且能够运行the modified version of the model suggested by @colcarroll。但是，在OS X机器上，即使更改了模型，我仍然看到上面指出的Theano编译错误。这可能是clang问题吗？可以指定Theano使用的编译器吗？
答案 0 :(得分：1)
是的-您必须对更高尺寸的形状更加明确。该库有点“聪明”，但是如果您提供shape参数，它将使用该参数。
您的示例在语法上通过设置
得到了固定with pm.Model() as m:
# Parameters
p_g = pm.Beta('p_g', 1., 1., shape=(G, 1))
sd_g = pm.HalfNormal('sd_g', sd=1, shape=(G, 1))
# Observed proportions
p_gk = pm.Beta('p_gk', mu=p_g.dot(np.ones((1,K))), sd=sd_g.dot(np.ones((1, K))), shape=(G, K), observed=data)
trace = pm.sample()
请注意，运行m.check_test_point()将表明p_gk的概率为0。这是因为sd_g太宽，PyMC3试图将其初始化为0.8，这超出了mu, sd参数化beta分布的支持。
设置sd_g = pm.HalfNormal('sd_g', sd=0.1, shape=(G, 1))还可以从模型中进行采样，尽管这可能不是您想要的！
答案 1 :(得分：1)
一种解决方法是抑制编译错误：
import theano
theano.config.gcc.cxxflags = "-Wno-c++11-narrowing"
这些错误对程序正确性的影响程度尚不清楚。当我在CentOS 7上编译时，它们不会出现（即使使用-Wc++11-narrowing对其进行显式检查也是如此）。在Mac OS X上具有减少的错误的采样结果与在没有CentOS的情况下的采样结果具有可比性。
我还是希望看到一个可以解释根本问题的答案。