fix pylint errors, unused imports

.pylintrc

@@ -323,7 +323,7 @@ ignore-on-opaque-inference=yes
 # List of class names for which member attributes should not be checked (useful
 # for classes with dynamically set attributes). This supports the use of
 # qualified names.
-ignored-classes=optparse.Values,thread._local,_thread._local
+ignored-classes=optparse.Values,thread._local,_thread._local, Context
 
 # List of module names for which member attributes should not be checked
 # (useful for modules/projects where namespaces are manipulated during runtime

pymc4/model.py

@@ -1,4 +1,3 @@
-import tensorflow as tf
 import threading
 
 __all__ = ["Model"]
@@ -19,7 +18,7 @@ def __exit__(self, typ, value, traceback):
 
 
 class Model(Context):
-    def __new__(cls, *args, **kwargs):
+    def __new__(cls, **kwargs):
         instance = super(Model, cls).__new__(cls)
         if kwargs.get('model') is not None:
             instance.parent = kwargs.get('model')
@@ -32,6 +31,7 @@ def __new__(cls, *args, **kwargs):
     def __init__(self, name="", model=None, ):
         self.name = name
         self.named_vars = {}
+        self.parent = model
 
     @property
     def model(self):

pymc4/random_variable.py

@@ -7,19 +7,19 @@
 class RandomVariable(ed.RandomVariable):
 
     def __init__(
-                self,
-                distribution,
-                sample_shape=(),
-                value=None,
-                name="RV"
-                ):
+            self,
+            name,
+            distribution,
+            sample_shape=(),
+            value=None,
+    ):
         self.model = Model.get_context()
         self.name = name
 
         super(RandomVariable, self).__init__(
-                                                distribution,
-                                                sample_shape,
-                                                value,
-                                                )
+            distribution,
+            sample_shape,
+            value,
+        )
 
         self.model.add_random_variable(self)

pymc4/sample.py

@@ -1,9 +1,8 @@
 import tensorflow as tf
-from pymc4 import Model
 import numpy as np
 import xarray as xr
-from pymc4 import Model
 import tqdm
+from pymc4 import Model
 
 __all__ = ["sample"]
 
@@ -14,17 +13,17 @@ def sample(draws=1000, tune=500, as_xarray=True):
     model = Model.get_context()
     array = []
     with tf.Session() as sess:
-        for i in tqdm.trange(draws+tune):
+        for _ in tqdm.trange(draws+tune):
 
             # Sampling methods are applied here.
             # Directly using tensorflow's default sampling method for now
             array.append([i.eval() for i in model.named_vars.values()])
     if as_xarray:
         return (xr.DataArray(
-                            data=array[tune:],
-                            dims=("Val", "RV"),
-                            coords={"RV": list(model.named_vars.keys())}
-                            )
-                )
+            data=array[tune:],
+            dims=("Val", "RV"),
+            coords={"RV": list(model.named_vars.keys())}
+                    )
+               )
     else:
-        return np.array(array[Tune])
+        return np.array(array[tune:])