Simplify comparisons

theano/sandbox/cuda/dnn.py

@@ -105,7 +105,7 @@ if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
                         " This isn't supported anymore."
                         " Update to CuDNN v2 final version.")
                     raise RuntimeError(dnn_available.msg)
-                if v[0] >= 3000 and v[0] < 3007:
+                if 3000 <= v[0] < 3007:
                     # 3007 is the final release of cudnn v3
                     dnn_available.avail = False
                     dnn_available.msg = (

theano/sandbox/gpuarray/dnn.py

@@ -74,7 +74,7 @@ def _dnn_check_version():
             "You have an old release of CuDNN (or a release candidate) "
             "that isn't supported.  Please update to at least v2 final "
             "version.")
-    if v >= 3000 and v < 3007:
+    if 3000 <= v < 3007:
         return False, (
             "You have installed a release candidate of CuDNN v3. This "
             "isn't supported. Please update to v3 final version.")

theano/scan_module/scan_opt.py

@@ -1444,8 +1444,7 @@ class ScanSaveMem(gof.Optimizer):
                         last_sitsot_idx = (node.op.n_mit_mot +
                                            node.op.n_mit_sot +
                                            node.op.n_sit_sot - 1)
-                        preallocable_output = (i >= first_mitsot_idx and
-                                               i <= last_sitsot_idx)
+                        preallocable_output = (first_mitsot_idx <= i <= last_sitsot_idx)
 
                         if (prealloc_outs and preallocable_output):
                             pval = select_max(nw_steps - start + init_l[i],

theano/sparse/tests/test_basic.py

@@ -117,7 +117,7 @@ def sparse_random_inputs(format, shape, n=1, out_dtype=None, p=0.5, gap=None,
     if out_dtype is None:
         out_dtype = theano.config.floatX
 
-    assert 0 <= p and p <= 1
+    assert 0 <= p <= 1
     assert len(shape) == 2
     assert out_dtype in sparse.all_dtypes
     assert gap is None or isinstance(gap, (tuple, list))

theano/tensor/basic.py

@@ -432,7 +432,7 @@ def constant(x, name=None, ndim=None, dtype=None):
         return ret
     sig = ret.signature()
     if (sig not in constant_cache and ret.data.size == 1 and
-        ret.data <= 10 and ret.data >= -10 and
+        (-10) <= ret.data <= 10 and
         (ret.dtype in int_dtypes or ret.dtype in uint_dtypes or
          (ret.dtype in float_dtypes and int(ret.data) == ret.data))):
         constant_cache[sig] = ret

theano/tensor/elemwise.py

@@ -527,7 +527,7 @@ class Elemwise(OpenMPOp):
         self.nfunc = None
         if getattr(self, 'nfunc_spec', None):
             self.nfunc = getattr(numpy, self.nfunc_spec[0])
-        elif self.scalar_op.nin > 0 and self.scalar_op.nin < 32:
+        elif 0 < self.scalar_op.nin < 32:
             self.ufunc = numpy.frompyfunc(self.scalar_op.impl,
                                           self.scalar_op.nin,
                                           self.scalar_op.nout)