我正在尝试运行以下模型，但在编译过程中失败：
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。我在运行现有的 PyMC3 示例时没有看到这些错误。我怀疑我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这种格式(我可能会强加我对 Stan 的熟悉)。
通常，我很难了解如何实现具有多个维度的多级模型。
知道是什么导致了我看到的错误吗？
版本
- 蟒蛇 3.6.3
- numpy 1.14.5
- 泰亚诺 1.0.2
- PYMC3 3.4.1
- Mac OS 10.13.5
更新
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 @colcarroll 建议的模型的修改版本。 但是，在我的OS X机器上，即使模型发生了变化，我仍然看到上面指示的Theano编译错误。这可能是一个clang问题吗？可以指定Theano使用的编译器吗？
一种解决方法是禁止显示编译警告：
import theano
theano.config.gcc.cxxflags = "-Wno-c++11-narrowing"
这些警告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明确检查它们)。在有抑制错误的Mac OS X和没有抑制错误的CentOS上的采样结果相当。
我仍然希望看到一个解释根本问题的答案。
是的- 你必须对更高维度的形状更明确一点。该库做了一些"聪明"的事情，但如果你提供shape参数，它将使用它。
您这里的示例通过设置
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概率为 0。这是因为sd_g太宽，PyMC3 试图将其初始化为 0.8，这是出于对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))允许您从模型中采样，尽管这可能不是您想要的先验！