Apply isort to theano.scalar sub-package modules

theano/scalar/__init__.py

 from .basic import *
-
 from .basic_scipy import *

theano/scalar/basic.py

@@ -19,13 +19,16 @@ from textwrap import dedent
 
 import numpy as np
 import six
+
 import theano
 from theano import config, gof, printing
 from theano.compat import Callable
 from theano.gof import Apply, Constant, FunctionGraph, Op, Type, Variable, utils
 from theano.gradient import DisconnectedType, grad_undefined
+from theano.misc.safe_asarray import _asarray
 from theano.printing import pprint
 
+
 builtin_bool = bool
 builtin_complex = complex
 builtin_int = int
@@ -181,7 +184,7 @@ class NumpyAutocaster(object):
                 and rval.dtype in ("float64", "float32")
                 and rval.dtype != config.floatX
             ):
-                rval = theano._asarray(rval, dtype=config.floatX)
+                rval = _asarray(rval, dtype=config.floatX)
             return rval
 
         # The following is the original code, corresponding to the 'custom'
@@ -207,7 +210,7 @@ class NumpyAutocaster(object):
             and config.floatX in self.dtypes
             and config.floatX != "float64"
         ):
-            return theano._asarray(x, dtype=config.floatX)
+            return _asarray(x, dtype=config.floatX)
 
         # Don't autocast to float16 unless config.floatX is float16
         try_dtypes = [
@@ -215,7 +218,7 @@ class NumpyAutocaster(object):
         ]
 
         for dtype in try_dtypes:
-            x_ = theano._asarray(x, dtype=dtype)
+            x_ = _asarray(x, dtype=dtype)
             if np.all(x == x_):
                 break
         # returns either an exact x_==x, or the last cast x_
@@ -272,7 +275,7 @@ def convert(x, dtype=None):
     """
     if dtype is not None:
         # in this case, the semantics are that the caller is forcing the dtype
-        x_ = theano._asarray(x, dtype=dtype)
+        x_ = _asarray(x, dtype=dtype)
     else:
         # In this case, this function should infer the dtype according to the
         # autocasting rules. See autocasting above.
@@ -283,7 +286,7 @@ def convert(x, dtype=None):
             except OverflowError:
                 # This is to imitate numpy behavior which tries to fit
                 # bigger numbers into a uint64.
-                x_ = theano._asarray(x, dtype="uint64")
+                x_ = _asarray(x, dtype="uint64")
         elif isinstance(x, builtin_float):
             x_ = autocast_float(x)
         elif isinstance(x, np.ndarray):

theano/scalar/basic_scipy.py

 # Definitions of theano.scalar ops that have their python implementation taken
 # from SciPy. As SciPy is not always available, we treat them separately.
 
-import numpy as np
 import os
 
+import numpy as np
+
 import theano
 from theano.gradient import grad_not_implemented
 from theano.scalar.basic import (
-    UnaryScalarOp,
     BinaryScalarOp,
+    UnaryScalarOp,
+    complex_types,
+    discrete_types,
     exp,
+    float_types,
+    upcast,
     upgrade_to_float,
     upgrade_to_float64,
-    float_types,
-)
-from theano.scalar.basic import (
     upgrade_to_float_no_complex,
-    complex_types,
-    discrete_types,
-    upcast,
 )
 
+
 imported_scipy_special = False
 try:
     import scipy.special

theano/scalar/basic_sympy.py

 import itertools as it
 
-from theano.scalar.basic import Apply, ScalarOp, as_scalar, float64, float32, int64
 from theano.gof.utils import remove
+from theano.scalar.basic import Apply, ScalarOp, as_scalar, float32, float64, int64
+
 
 imported_sympy = False
 try:
-    from sympy.utilities.codegen import get_default_datatype, codegen
+    from sympy.utilities.codegen import codegen, get_default_datatype
 
     imported_sympy = True
 except ImportError:

theano/scalar/sharedvar.py

@@ -20,8 +20,10 @@ import numpy as np
 from six import integer_types
 
 from theano.compile import SharedVariable
+
 from .basic import Scalar, _scalar_py_operators
 
+
 __authors__ = "James Bergstra"
 __copyright__ = "(c) 2010, Universite de Montreal"
 __license__ = "3-clause BSD License"