Merge pull request #5086 from nouiz/mixed

doc/library/index.txt

@@ -27,6 +27,7 @@ Types and Ops that you can use to build and compile expression graphs.
    sparse/sandbox
    tensor/index
    typed_list
+   tests
 
 There are also some top-level imports that you might find more convenient:
 

doc/library/tests.txt

+.. _libdoc_tests:
+
+=====================
+:mod:`tests` -- Tests
+=====================
+
+.. automodule:: theano.tests.breakpoint
+    :members:

doc/tutorial/debug_faq.txt

@@ -573,4 +573,8 @@ the Ops from Theano and Pylearn2.
 Then send us filename.
 
 
-.. autoclass:: theano.tests.breakpoint.PdbBreakpoint
+Breakpoint during Theano function execution
+-------------------------------------------
+
+You can set breakpoing during the execution of a Theano function with
+:class:`PdbBreakpoint <theano.tests.breakpoint.PdbBreakpoint>`.

doc/tutorial/using_gpu.txt

@@ -369,6 +369,9 @@ Consider again the logistic regression:
     print("prediction on D")
     print(predict(D[0]))
 
+    print("floatX=", theano.config.floatX)
+    print("device=", theano.config.device)
+
 .. testoutput::
    :hide:
    :options: + ELLIPSIS

theano/compile/ops.py

@@ -450,7 +450,7 @@ def shape_i(var, i, fgraph=None):
                     if inp.owner:
                         recur(inp.owner)
                 # If the output var isn't marked as being in the graph,
-                # we need to att it in the ShapeFeature.
+                # we need to add it in the ShapeFeature.
                 shape_feature.on_import(fgraph, node,
                                         'gof.ops.shape_i')
         if var not in shape_of:

theano/sandbox/cuda/opt.py

@@ -2199,7 +2199,7 @@ else:
                    "fast_run"))
     optdb.register('gpu_elemwise_fusion',
                    tensor.opt.FusionOptimizer(gpu_local_elemwise_fusion),
-                   71.00, 'fusion', 'local_elemwise_fusion')
+                   49, 'fusion', 'local_elemwise_fusion')
 
 # GpuElemwise inplace
 gpu_inplace_elemwise_optimizer = tensor.opt.InplaceElemwiseOptimizer(

theano/tensor/subtensor.py

@@ -573,11 +573,15 @@ class Subtensor(Op):
         gz, = grads
         x = inputs[0]
         rest = inputs[1:]
-        output = self(*inputs)
-        if output.dtype.find('int') != -1:
+        if x.dtype.find('int') != -1:
             first = x.zeros_like().astype(theano.config.floatX)
         else:
-            first = IncSubtensor(self.idx_list)(x.zeros_like(), gz, *rest)
+            # For best optimization, we let this as an inc.
+            # This allow the opt local_IncSubtensor_serialize to apply first.
+            # We need to implement an optimization that will convert this to a
+            # set subtensor.
+            first = IncSubtensor(self.idx_list)(x.zeros_like(),
+                                                gz, *rest)
         return ([first] + [DisconnectedType()()] * len(rest))
 
     def connection_pattern(self, node):

theano/tests/test_flake8.py

@@ -85,12 +85,6 @@ whitelist_flake8 = [
     "sandbox/cuda/__init__.py",
     "sandbox/cuda/tests/__init__.py",
     "sandbox/gpuarray/__init__.py",
-    "sandbox/scan_module/scan_utils.py",
-    "sandbox/scan_module/scan.py",
-    "sandbox/scan_module/scan_op.py",
-    "sandbox/scan_module/__init__.py",
-    "sandbox/scan_module/tests/test_utils.py",
-    "sandbox/scan_module/tests/test_scan.py",
     "sandbox/linalg/ops.py",
     "sandbox/linalg/__init__.py",
     "sandbox/linalg/tests/__init__.py",