def param(name, *args, **kwargs):
"""
Saves the variable as a parameter in the param store.
To interact with the param store or write to disk,
see `Parameters <parameters.html>`_.
:param name: name of parameter
:returns: parameter
"""
if len(_PYRO_STACK) == 0:
return _PYRO_PARAM_STORE.get_param(name, *args, **kwargs)
else:
msg = {
"type": "param",
"name": name,
"args": args,
"kwargs": kwargs,
"scale": 1.0,
"cond_indep_stack": [],
"value": None,
"done": False,
"stop": False,
}
# apply the stack and return its return value
out_msg = apply_stack(msg)
return out_msg["value"]
def param(name, *args, **kwargs):
"""
Saves the variable as a parameter in the param store.
To interact with the param store or write to disk,
see `Parameters <parameters.html>`_.
:param name: name of parameter
:returns: parameter
"""
if len(_PYRO_STACK) == 0:
return _PYRO_PARAM_STORE.get_param(name, *args, **kwargs)
else:
msg = {
"type": "param",
"name": name,
"args": args,
"kwargs": kwargs,
"scale": 1.0,
"cond_indep_stack": [],
"value": None,
"done": False,
"stop": False,
}
# apply the stack and return its return value
out_msg = apply_stack(msg)
return out_msg["value"]
def sample(name, fn, *args, **kwargs):
"""
Calls the stochastic function `fn` with additional side-effects depending
on `name` and the enclosing context (e.g. an inference algorithm).
See `Intro I <http://pyro.ai/examples/intro_part_i.html>`_ and
`Intro II <http://pyro.ai/examples/intro_part_ii.html>`_ for a discussion.
:param name: name of sample
:param fn: distribution class or function
:param obs: observed datum (optional; should only be used in context of
inference) optionally specified in kwargs
:param dict baseline: Optional dictionary of baseline parameters specified
in kwargs. See inference documentation for details.
:returns: sample
"""
obs = kwargs.pop("obs", None)
baseline = kwargs.pop("baseline", {})
# check if stack is empty
# if stack empty, default behavior (defined here)
if len(_PYRO_STACK) == 0:
if obs is not None:
warnings.warn(
"trying to observe a value outside of inference at " + name,
RuntimeWarning)
return obs
return fn(*args, **kwargs)
# if stack not empty, apply everything in the stack?
else:
# initialize data structure to pass up/down the stack
msg = {
"type": "sample",
"name": name,
"fn": fn,
"is_observed": False,
"args": args,
"kwargs": kwargs,
"value": None,
"baseline": baseline,
"scale": 1.0,
"cond_indep_stack": [],
"done": False,
"stop": False,
}
# handle observation
if obs is not None:
msg["value"] = obs
msg["is_observed"] = True
# apply the stack and return its return value
out_msg = apply_stack(msg)
return out_msg["value"]
def sample(name, fn, *args, **kwargs):
"""
Calls the stochastic function `fn` with additional side-effects depending
on `name` and the enclosing context (e.g. an inference algorithm).
See `Intro I <http://pyro.ai/examples/intro_part_i.html>`_ and
`Intro II <http://pyro.ai/examples/intro_part_ii.html>`_ for a discussion.
:param name: name of sample
:param fn: distribution class or function
:param obs: observed datum (optional; should only be used in context of
inference) optionally specified in kwargs
:param dict baseline: Optional dictionary of baseline parameters specified
in kwargs. See inference documentation for details.
:returns: sample
"""
obs = kwargs.pop("obs", None)
baseline = kwargs.pop("baseline", {})
# check if stack is empty
# if stack empty, default behavior (defined here)
if len(_PYRO_STACK) == 0:
if obs is not None:
warnings.warn("trying to observe a value outside of inference at " + name,
RuntimeWarning)
return obs
return fn(*args, **kwargs)
# if stack not empty, apply everything in the stack?
else:
# initialize data structure to pass up/down the stack
msg = {
"type": "sample",
"name": name,
"fn": fn,
"is_observed": False,
"args": args,
"kwargs": kwargs,
"value": None,
"baseline": baseline,
"scale": 1.0,
"cond_indep_stack": [],
"done": False,
"stop": False,
}
# handle observation
if obs is not None:
msg["value"] = obs
msg["is_observed"] = True
# apply the stack and return its return value
out_msg = apply_stack(msg)
return out_msg["value"]