第一章示例：从文本消息数据推断行为
我们希望在每日短信计数中找到一个开关点。 假设Serise可以分为两个具有两个泊松分布的段。
使用 pymc3：(基于 theano(
import pymc3 as pm
import theano.tensor as tt
with pm.Model() as model:
alpha = 1.0/count_data.mean() # Recall count_data is the
# variable that holds our txt counts
lambda_1 = pm.Exponential("lambda_1", alpha)
lambda_2 = pm.Exponential("lambda_2", alpha)
tau = pm.DiscreteUniform("tau", lower=0, upper=n_count_data - 1)
with model:
idx = np.arange(n_count_data) # Index
lambda_ = pm.math.switch(tau >= idx, lambda_1, lambda_2)
observation = pm.Poisson("obs", lambda_, observed=count_data)
step = pm.Metropolis()
trace = pm.sample(10000, tune=5000,step=step)
我使用爱德华：(基于张量流(
import edward as ed
import tensorflow as tf
from edward.models import Exponential,Uniform,Poisson,Empirical
from edward.models import PointMass
alpha_f = 1.0/count_data.mean()
alpha = tf.Variable(alpha_f, name="alpha", dtype=tf.float32)
# init
lambda_1 = Exponential(alpha)
lambda_2 = Exponential(alpha)
tau = Uniform(low=0.0,high=float(n_count_data - 1))
idx = np.arange(n_count_data)
lambda_ = tf.where(tau>=idx,tf.ones(shape=[n_count_data],dtype=tf.float32)*lambda_1,tf.ones(shape=[n_count_data],dtype=tf.float32)*lambda_2)
z = Poisson(lambda_,value=count_data)
T = 5000
qlambda_1 = Empirical(params=tf.Variable(tf.zeros([T])))
qlambda_2 = Empirical(params=tf.Variable(tf.zeros([T])))
qtau = Empirical(params=tf.Variable(tf.zeros([T])))
qz = Empirical(params=tf.Variable(tf.zeros([T,n_count_data])))
inference = ed.HMC({z:qz,lambda_1:qlambda_1,lambda_2:qlambda_2,tau:qtau})
inference.run()
for t in range(inference.n_iter):
info_dict = inference.update()
print(info_dict)
抛出这个例外：
InvalidArgumentError Traceback (most recent call last)
c:python35libsite-packagestensorflowpythonclientsession.py in _do_call(self, fn, *args)
1138 try:
-> 1139 return fn(*args)
1140 except errors.OpError as e:
c:python35libsite-packagestensorflowpythonclientsession.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1120 feed_dict, fetch_list, target_list,
-> 1121 status, run_metadata)
1122
c:python35libcontextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
c:python35libsite-packagestensorflowpythonframeworkerrors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
InvalidArgumentError: indices = 5000 is not in [0, 5000)
[[Node: ScatterUpdate_26 = ScatterUpdate[T=DT_FLOAT, Tindices=DT_INT32, _class=["loc:@Variable_77"], use_locking=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_77, iteration_17/read, cond_17/Merge_3)]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-107-2c42d8ad11c6> in <module>()
30
31 for t in range(inference.n_iter):
---> 32 info_dict = inference.update()
33 print(info_dict)
34
c:python35libsite-packagesedwardinferencesmonte_carlo.py in update(self, feed_dict)
135
136 sess = get_session()
--> 137 _, accept_rate = sess.run([self.train, self.n_accept_over_t], feed_dict)
138 t = sess.run(self.increment_t)
139
c:python35libsite-packagestensorflowpythonclientsession.py in run(self, fetches, feed_dict, options, run_metadata)
787 try:
788 result = self._run(None, fetches, feed_dict, options_ptr,
--> 789 run_metadata_ptr)
790 if run_metadata:
791 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
c:python35libsite-packagestensorflowpythonclientsession.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
995 if final_fetches or final_targets:
996 results = self._do_run(handle, final_targets, final_fetches,
--> 997 feed_dict_string, options, run_metadata)
998 else:
999 results = []
c:python35libsite-packagestensorflowpythonclientsession.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1130 if handle is None:
1131 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1132 target_list, options, run_metadata)
1133 else:
1134 return self._do_call(_prun_fn, self._session, handle, feed_dict,
c:python35libsite-packagestensorflowpythonclientsession.py in _do_call(self, fn, *args)
1150 except KeyError:
1151 pass
-> 1152 raise type(e)(node_def, op, message)
1153
1154 def _extend_graph(self):
InvalidArgumentError: indices = 5000 is not in [0, 5000)
[[Node: ScatterUpdate_26 = ScatterUpdate[T=DT_FLOAT, Tindices=DT_INT32, _class=["loc:@Variable_77"], use_locking=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_77, iteration_17/read, cond_17/Merge_3)]]
Caused by op 'ScatterUpdate_26', defined at:
File "c:python35librunpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "c:python35librunpy.py", line 85, in _run_code
exec(code, run_globals)
File "c:python35libsite-packagesipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "c:python35libsite-packagestraitletsconfigapplication.py", line 658, in launch_instance
app.start()
File "c:python35libsite-packagesipykernelkernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "c:python35libsite-packageszmqeventloopioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "c:python35libsite-packagestornadoioloop.py", line 888, in start
handler_func(fd_obj, events)
File "c:python35libsite-packagestornadostack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "c:python35libsite-packageszmqeventloopzmqstream.py", line 440, in _handle_events
self._handle_recv()
File "c:python35libsite-packageszmqeventloopzmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "c:python35libsite-packageszmqeventloopzmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "c:python35libsite-packagestornadostack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "c:python35libsite-packagesipykernelkernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "c:python35libsite-packagesipykernelkernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "c:python35libsite-packagesipykernelkernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "c:python35libsite-packagesipykernelipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "c:python35libsite-packagesipykernelzmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "c:python35libsite-packagesIPythoncoreinteractiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "c:python35libsite-packagesIPythoncoreinteractiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "c:python35libsite-packagesIPythoncoreinteractiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-107-2c42d8ad11c6>", line 27, in <module>
inference.run()
File "c:python35libsite-packagesedwardinferencesinference.py", line 123, in run
self.initialize(*args, **kwargs)
File "c:python35libsite-packagesedwardinferenceshmc.py", line 64, in initialize
return super(HMC, self).initialize(*args, **kwargs)
File "c:python35libsite-packagesedwardinferencesmonte_carlo.py", line 98, in initialize
self.train = self.build_update()
File "c:python35libsite-packagesedwardinferenceshmc.py", line 116, in build_update
assign_ops.append(tf.scatter_update(variable, self.t, sample[z]))
File "c:python35libsite-packagestensorflowpythonopsgen_state_ops.py", line 599, in scatter_update
name=name)
File "c:python35libsite-packagestensorflowpythonframeworkop_def_library.py", line 767, in apply_op
op_def=op_def)
File "c:python35libsite-packagestensorflowpythonframeworkops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "c:python35libsite-packagestensorflowpythonframeworkops.py", line 1269, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): indices = 5000 is not in [0, 5000)
[[Node: ScatterUpdate_26 = ScatterUpdate[T=DT_FLOAT, Tindices=DT_INT32, _class=["loc:@Variable_77"], use_locking=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_77, iteration_17/read, cond_17/Merge_3)]]
--------------------------------------------------------------------------------
这个来自Probabilistic-Programming-and-Bayesian-Methods-for-Hackers-master的pymc源代码： 在此处输入链接说明
查看文档，我认为这不是运行推理的正确方法。您可以选择控制该过程，就像最后所做的那样，也可以使用为您执行的inference.run()，但不能两者兼而有之。此外，您已经设置了要近似的分布，但您没有将任何数据传递给 HMC，例如HMC(latent_vars = {z:q_z.....},data= {?}).这是Torsten Scholak在PyCon2017上的笔记本链接，它有很多例子