pyro/infer/abstract_infer.py

Survived

Mutant 1

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -61,7 +61,7 @@
         else:
             return torch.stack(samples_by_chain, dim=0), torch.stack(weights_by_chain, dim=0)
 
-    def _add_sample(self, value, log_weight=None, chain_id=0):
+    def _add_sample(self, value, log_weight=None, chain_id=1):
         """
         Adds a new data point to the sample. The values in successive calls to
         ``add`` must have the same tensor shape and size. Optionally, an

Mutant 2

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -127,7 +127,7 @@
         self._marginals = {site: EmpiricalMarginal(trace_posterior, site, validate)
                            for site in self.sites}
 
-    def support(self, flatten=False):
+    def support(self, flatten=True):
         """
         Gets support of this marginal distribution.
 

Mutant 3

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -146,7 +146,6 @@
                 support[site] = samples.reshape(flattened_shape)
         return support
 
-    @property
     def empirical(self):
         """
         A dictionary of sites' names and their corresponding :class:`EmpiricalMarginal`

Mutant 4

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -164,7 +164,7 @@
     This is designed to be used by other utility classes like `EmpiricalMarginal`,
     that need access to the collected execution traces.
     """
-    def __init__(self, num_chains=1):
+    def __init__(self, num_chains=2):
         self.num_chains = num_chains
         self._reset()
 

Mutant 6

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -169,7 +169,7 @@
         self._reset()
 
     def _reset(self):
-        self.log_weights = []
+        self.log_weights = None
         self.exec_traces = []
         self.chain_ids = []  # chain id corresponding to the sample
         self._idx_by_chain = [[] for _ in range(self.num_chains)]  # indexes of samples by chain id

Mutant 7

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -170,7 +170,7 @@
 
     def _reset(self):
         self.log_weights = []
-        self.exec_traces = []
+        self.exec_traces = None
         self.chain_ids = []  # chain id corresponding to the sample
         self._idx_by_chain = [[] for _ in range(self.num_chains)]  # indexes of samples by chain id
         self._categorical = None

Mutant 8

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -171,7 +171,7 @@
     def _reset(self):
         self.log_weights = []
         self.exec_traces = []
-        self.chain_ids = []  # chain id corresponding to the sample
+        self.chain_ids = None  # chain id corresponding to the sample
         self._idx_by_chain = [[] for _ in range(self.num_chains)]  # indexes of samples by chain id
         self._categorical = None
 

Mutant 9

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -172,7 +172,7 @@
         self.log_weights = []
         self.exec_traces = []
         self.chain_ids = []  # chain id corresponding to the sample
-        self._idx_by_chain = [[] for _ in range(self.num_chains)]  # indexes of samples by chain id
+        self._idx_by_chain = None  # indexes of samples by chain id
         self._categorical = None
 
     def marginal(self, sites=None):

Mutant 10

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -173,7 +173,7 @@
         self.exec_traces = []
         self.chain_ids = []  # chain id corresponding to the sample
         self._idx_by_chain = [[] for _ in range(self.num_chains)]  # indexes of samples by chain id
-        self._categorical = None
+        self._categorical = ""
 
     def marginal(self, sites=None):
         """

Mutant 11

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -186,7 +186,6 @@
         """
         return Marginals(self, sites)
 
-    @abstractmethod
     def _traces(self, *args, **kwargs):
         """
         Abstract method implemented by classes that inherit from `TracePosterior`.

Mutant 12

--- pyro/infer/abstract_infer.py
+++ pyro/infer/abstract_infer.py
@@ -232,7 +232,7 @@
         self._categorical = Categorical(logits=torch.tensor(self.log_weights))
         return self
 
-    def information_criterion(self, pointwise=False):
+    def information_criterion(self, pointwise=True):
         """
         Computes information criterion of the model. Currently, returns only "Widely
         Applicable/Watanabe-Akaike Information Criterion" (WAIC) and the corresponding