Merge pull request #2728 from orhanf/register_local_remove_all_assert

doc/faq.txt

@@ -79,7 +79,7 @@ garbage collection will keep all intermediate results' memory space to allow to
 reuse them during the next call to the same Theano function, if they are of the
 correct shape. The shape could change if the shapes of the inputs change.
 
-.. unsafe_optimization:
+.. _unsafe_optimization:
 
 Unsafe optimization
 ===================

doc/optimizations.txt

@@ -54,6 +54,7 @@ Optimization                                              FAST_RUN  FAST_COMPILE
 :term:`elemwise fusion`                                   x
 :term:`GPU transfer`                                      x
 :term:`local_log_softmax`                                 x                      x
+:term:`local_remove_all_assert`                                                   
 ========================================================= ========= ============ =============
 
 
@@ -258,3 +259,13 @@ Optimization                                              FAST_RUN  FAST_COMPILE
         It can happen due to rounding errors that the softmax probability of one value gets to 0.
         Taking the log of 0 would generate -inf that will probably generate NaN later.
         We return a closer answer.
+
+    local_remove_all_assert
+        This is an unsafe optimization.
+        For the fastest possible Theano, this optimization can be enabled by
+	setting ``optimizer_including=local_remove_all_assert`` which will
+	remove all assertions in the graph for checking user inputs are valid.
+        Use this optimization if you are sure everthing is valid in your graph.
+	
+	See :ref:`unsafe_optimization`
+

theano/sandbox/cuda/opt.py

@@ -97,6 +97,11 @@ register_opt(name='gpu_constant_folding')(
     tensor.opt.constant_folding)
 register_opt()(theano.tensor.opt.local_subtensor_make_vector)
 
+# Register local_remove_all_assert as a global opt
+gpu_optimizer.register('local_remove_all_assert',
+                       theano.tensor.opt.local_remove_all_assert,
+                       'unsafe')
+
 
 # This is a partial list of CPU ops that can be in some circonstance
 # moved to the GPU. This list is used by an optimization.

theano/sandbox/cuda/tests/test_opt.py

@@ -56,6 +56,29 @@ def test_local_assert():
     assert isinstance(a_op[0].inputs[0].type, CudaNdarrayType)
 
 
+def test_local_remove_all_assert():
+    x = theano.tensor.fmatrix()
+    a = theano.tensor.opt.assert_op(x, theano.tensor.eq(x, 0).any())
+
+    # By default `unsafe` should not be there
+    f = theano.function([x], a, mode=mode_with_gpu)
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 1
+
+    # Put `unsafe`
+    f = theano.function([x], a, mode=mode_with_gpu.including('unsafe'))
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 0
+
+    # Remove `unsafe`
+    f = theano.function([x], a, mode=mode_with_gpu.excluding('unsafe'))
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 1
+
+
 def test_int_pow():
     a = CudaNdarrayType([False])()
 
@@ -609,3 +632,4 @@ if __name__ == '__main__':
     test_gpualloc()
     test_opt_gpujoin_onlyajoin()
     test_opt_gpujoin_joinvectors_elemwise_then_minusone()
+

theano/sandbox/gpuarray/opt.py

@@ -60,6 +60,10 @@ def register_opt(*tags, **kwargs):
 
 register_opt('fast_compile')(theano.tensor.opt.local_track_shape_i)
 
+gpu_optimizer.register('local_remove_all_assert',
+                       theano.tensor.opt.local_remove_all_assert,
+                       'unsafe')
+
 
 def safe_to_gpu(x):
     if isinstance(x.type, tensor.TensorType):

theano/sandbox/gpuarray/tests/test_opt.py

@@ -25,6 +25,29 @@ def test_local_assert():
     assert isinstance(a_op[0].inputs[0].type, GpuArrayType)
 
 
+def test_local_remove_all_assert():
+    x = theano.tensor.fmatrix()
+    a = theano.tensor.opt.assert_op(x, theano.tensor.eq(x, 0).any())
+
+    # By default `unsafe` should not be there
+    f = theano.function([x], a, mode=mode_with_gpu)
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 1
+
+    # Put `unsafe`
+    f = theano.function([x], a, mode=mode_with_gpu.including('unsafe'))
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 0
+
+    # Remove `unsafe`
+    f = theano.function([x], a, mode=mode_with_gpu.excluding('unsafe'))
+    topo = f.maker.fgraph.toposort()
+    a_op = [n for n in topo if isinstance(n.op, theano.tensor.opt.Assert)]
+    assert len(a_op) == 1
+
+
 def test_flatten():
     m = theano.tensor.fmatrix()
     f = theano.function([m], m.flatten(), mode=mode_with_gpu)

theano/tensor/opt.py

@@ -1670,12 +1670,15 @@ def local_remove_all_assert(node):
 # Disabled by default
 compile.optdb['canonicalize'].register('local_remove_all_assert',
                                        local_remove_all_assert,
+                                       'unsafe',
                                        use_db_name_as_tag=False)
 compile.optdb['stabilize'].register('local_remove_all_assert',
                                     local_remove_all_assert,
+                                    'unsafe',
                                     use_db_name_as_tag=False)
 compile.optdb['specialize'].register('local_remove_all_assert',
                                      local_remove_all_assert,
+                                     'unsafe',
                                      use_db_name_as_tag=False)
 
 

theano/tensor/tests/test_opt.py

@@ -3553,6 +3553,13 @@ class test_assert(utt.InferShapeTester):
         assert len(topo) == 1, topo
         assert topo[0].op == deep_copy_op, topo
 
+        mode = compile.mode.get_default_mode()
+        a = theano.tensor.opt.assert_op(x, T.eq(x, 0).any())
+        f = theano.function([x], a, mode=mode.excluding('unsafe'))
+        topo = f.maker.fgraph.toposort()
+        a_op = [n for n in topo if isinstance(n.op, T.opt.Assert)]
+        assert len(a_op) == 1
+
     def test_infer_shape(self):
 
         adscal = dscalar()