Merge pull request #5105 from nouiz/32bit

theano/gof/cmodule.py

@@ -535,14 +535,24 @@ class KeyData(object):
         """
         entry = self.get_entry()
         for key in self.keys:
+            try:
                 del entry_from_key[key]
+            except KeyError:
+                # This happen if the compiledir was deleted during
+                # this process execution.
+                pass
         if do_manual_check:
             to_del = []
             for key, key_entry in iteritems(entry_from_key):
                 if key_entry == entry:
                     to_del.append(key)
             for key in to_del:
+                try:
                     del entry_from_key[key]
+                except KeyError:
+                    # This happen if the compiledir was deleted during
+                    # this process execution.
+                    pass
 
 
 class ModuleCache(object):

theano/tensor/opt.py

@@ -1336,7 +1336,11 @@ class ShapeFeature(object):
                     assert d.dtype in theano.tensor.discrete_dtypes, (node, d.dtype)
                     assert str(d.dtype) != 'uint64', node
                     new_shape += sh[len(new_shape):i + 1]
-                    new_shape[i] = theano.tensor.cast(d, 'int64')
+                    if isinstance(d, T.Constant):
+                        casted_d = T.constant(d.data, dtype='int64')
+                    else:
+                        casted_d = theano.tensor.cast(d, 'int64')
+                    new_shape[i] = casted_d
             if new_shape:
                 # We replace the shape with wrong dtype by the one with
                 # 'int64'.

theano/tensor/signal/pool.py

@@ -560,9 +560,9 @@ class Pool(OpenMPOp):
             // index for iterating over the pooling regions
             int r_idx[%(nd)s];
             // placeholder for PyArray indexing (output)
-            long int o_idx[%(total_ndim)s];
+            npy_intp o_idx[%(total_ndim)s];
             // placeholder for PyArray indexing (input)
-            long int i_idx[%(total_ndim)s];
+            npy_intp i_idx[%(total_ndim)s];
             // loop over non-pooling dimensions
             int non_pooling_prod = 1;
             for (int i=0; i<%(non_pool_ndim)s; i++)
@@ -1040,9 +1040,9 @@ class MaxPoolGrad(PoolGrad):
             // index for iterating over the pooling regions
             int r_idx[%(nd)s];
             // placeholder for PyArray indexing (output)
-            long int o_idx[%(total_ndim)s];
+            npy_intp o_idx[%(total_ndim)s];
             // placeholder for PyArray indexing (input)
-            long int i_idx[%(total_ndim)s];
+            npy_intp i_idx[%(total_ndim)s];
             // loop over non-pooling dimensions
             int non_pooling_prod = 1;
             for (int i=0; i<%(non_pool_ndim)s; i++)
@@ -1367,9 +1367,9 @@ class AveragePoolGrad(PoolGrad):
             // index for iterating over the pooling regions
             int r_idx[%(nd)s];
             // placeholder for PyArray indexing (output)
-            long int o_idx[%(total_ndim)s];
+            npy_intp o_idx[%(total_ndim)s];
             // placeholder for PyArray indexing (input)
-            long int i_idx[%(total_ndim)s];
+            npy_intp i_idx[%(total_ndim)s];
             // loop over non-pooling dimensions
             int non_pooling_prod = 1;
             for (int i=0; i<%(non_pool_ndim)s; i++)
@@ -1671,9 +1671,9 @@ class DownsampleFactorMaxGradGrad(OpenMPOp):
         // index for iterating over the pooling regions
         int r_idx[%(nd)s];
         // placeholder for PyArray indexing (output)
-        long int o_idx[%(total_ndim)s];
+        npy_intp o_idx[%(total_ndim)s];
         // placeholder for PyArray indexing (input)
-        long int i_idx[%(total_ndim)s];
+        npy_intp i_idx[%(total_ndim)s];
         // loop over non-pooling dimensions
         int non_pooling_prod;
         non_pooling_prod = 1;

theano/tensor/type.py

@@ -511,18 +511,18 @@ class TensorType(Type):
                              (long int) %(type_num)s,
                              (long int) PyArray_TYPE((PyArrayObject*) py_%(name)s),
                              (long int) PyArray_NDIM(tmp),
-                             (long int) PyArray_NDIM(tmp) >= 3 ?
-            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-3] : -1,
-                             (long int) PyArray_NDIM(tmp) >= 2 ?
-            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-2] : -1,
-                             (long int) PyArray_NDIM(tmp) >= 1 ?
-            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-1] : -1,
-                             (long int) PyArray_NDIM(tmp) >= 3 ?
-            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-3] : -1,
-                             (long int) PyArray_NDIM(tmp) >= 2 ?
-            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-2] : -1,
-                             (long int) PyArray_NDIM(tmp) >= 1 ?
-            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-1] : -1
+                             (long int) (PyArray_NDIM(tmp) >= 3 ?
+            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-3] : -1),
+                             (long int) (PyArray_NDIM(tmp) >= 2 ?
+            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-2] : -1),
+                             (long int) (PyArray_NDIM(tmp) >= 1 ?
+            PyArray_DIMS(tmp)[PyArray_NDIM(tmp)-1] : -1),
+                             (long int) (PyArray_NDIM(tmp) >= 3 ?
+            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-3] : -1),
+                             (long int) (PyArray_NDIM(tmp) >= 2 ?
+            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-2] : -1),
+                             (long int) (PyArray_NDIM(tmp) >= 1 ?
+            PyArray_STRIDES(tmp)[PyArray_NDIM(tmp)-1] : -1)
             );
                 %(fail)s
             }
@@ -580,18 +580,18 @@ class TensorType(Type):
                          " and 3 last strides %%ld %%ld, %%ld.",
                          (long int) PyArray_TYPE((PyArrayObject*) py_%(name)s),
                          (long int) PyArray_NDIM(%(name)s),
-                         (long int) PyArray_NDIM(%(name)s) >= 3 ?
-        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-3] : -1,
-                         (long int) PyArray_NDIM(%(name)s) >= 2 ?
-        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-2] : -1,
-                         (long int) PyArray_NDIM(%(name)s) >= 1 ?
-        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-1] : -1,
-                         (long int) PyArray_NDIM(%(name)s) >= 3 ?
-        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-3] : -1,
-                         (long int) PyArray_NDIM(%(name)s) >= 2 ?
-        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-2] : -1,
-                         (long int) PyArray_NDIM(%(name)s) >= 1 ?
-        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-1] : -1
+                         (long int) (PyArray_NDIM(%(name)s) >= 3 ?
+        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-3] : -1),
+                         (long int) (PyArray_NDIM(%(name)s) >= 2 ?
+        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-2] : -1),
+                         (long int) (PyArray_NDIM(%(name)s) >= 1 ?
+        PyArray_DIMS(%(name)s)[PyArray_NDIM(%(name)s)-1] : -1),
+                         (long int) (PyArray_NDIM(%(name)s) >= 3 ?
+        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-3] : -1),
+                         (long int) (PyArray_NDIM(%(name)s) >= 2 ?
+        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-2] : -1),
+                         (long int) (PyArray_NDIM(%(name)s) >= 1 ?
+        PyArray_STRIDES(%(name)s)[PyArray_NDIM(%(name)s)-1] : -1)
         );
             %(fail)s
         }