Merge pull request #840 from lamblin/travis

theano/scan_module/tests/test_scan.py

@@ -841,7 +841,7 @@ class T_Scan(unittest.TestCase):
         (theano_x0, theano_x1) = f9(vu0, vu1, vu2, vx0, vx1)
         # assert that theano does what it should
         assert numpy.allclose(theano_x0, numpy_x0)
-        assert numpy.allclose(theano_x1, numpy_x1)
+        assert numpy.allclose(theano_x1, numpy_x1), (theano_x1, numpy_x1, theano_x1 - numpy_x1)
         # assert that it was done in place
 
         # !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

theano/tensor/extra_ops.py

@@ -3,7 +3,7 @@ import numpy
 
 import theano
 import basic
-from theano import gof, tensor, function, scalar
+from theano import gof, tensor, scalar
 from theano.sandbox.linalg.ops import diag
 
 
@@ -132,6 +132,21 @@ class BinCountOp(theano.Op):
 
         if x.dtype not in BinCountOp.compatible_type:
             raise TypeError("Inputs dtype must be an integer.")
+
+        # Some dtypes are not supported by numpy's implementation of bincount.
+        # Until another one is available, we should fail at graph construction
+        # time, not wait for execution.
+        int_bitwidth = theano.gof.cmodule.python_int_bitwidth()
+        if int_bitwidth == 64:
+            numpy_unsupported_dtypes = ('uint64',)
+        if int_bitwidth == 32:
+            numpy_unsupported_dtypes = ('uint32', 'int64', 'uint64')
+
+        if x.dtype in numpy_unsupported_dtypes:
+            raise TypeError(
+                    ("Input dtypes %s are not supported by numpy.bincount, "
+                    % numpy_unsupported_dtypes), x.dtype)
+
         if x.ndim != 1:
             raise TypeError("Inputs must be of dimension 1.")
 
@@ -286,6 +301,25 @@ class RepeatOp(theano.Op):
     def make_node(self, x, repeats):
         x = basic.as_tensor_variable(x)
         repeats = basic.as_tensor_variable(repeats)
+
+        if repeats.dtype not in tensor.discrete_dtypes:
+            raise TypeError("repeats.dtype must be an integer.")
+
+        # Some dtypes are not supported by numpy's implementation of repeat.
+        # Until another one is available, we should fail at graph construction
+        # time, not wait for execution.
+        int_bitwidth = theano.gof.cmodule.python_int_bitwidth()
+        if int_bitwidth == 64:
+            numpy_unsupported_dtypes = ('uint64',)
+        if int_bitwidth == 32:
+            numpy_unsupported_dtypes = ('uint32', 'int64', 'uint64')
+
+        if repeats.dtype in numpy_unsupported_dtypes:
+            raise TypeError(
+                    ("dtypes %s are not supported by numpy.repeat "
+                     "for the 'repeats' parameter, "
+                     % numpy_unsupported_dtypes), repeats.dtype)
+
         if self.axis is None:
             out_type = theano.tensor.TensorType(dtype=x.dtype,
                                                 broadcastable=[False])

theano/tensor/opt.py

@@ -970,7 +970,7 @@ class ShapeFeature(object):
                 # but this works with `local_useless_subtensor`, so for now we
                 # keep it this way. See #266 for a better long-term fix.
                 if getattr(d, 'dtype', 'int64') != 'int64':
-                    assert d.dtype in theano.tensor.int_dtypes
+                    assert d.dtype in theano.tensor.discrete_dtypes, d.dtype
                     new_shape += sh[len(new_shape):i + 1]
                     new_shape[i] = theano.tensor.cast(d, 'int64')
             if new_shape: