Merge pull request #2157 from sebastien-j/issue_2076

theano/sandbox/rng_mrg.py

@@ -734,6 +734,13 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
             unsigned int threads_per_block = std::min((unsigned int)n_streams_used_in_this_call, (unsigned int)NUM_VECTOR_OP_THREADS_PER_BLOCK);
             unsigned int n_blocks = std::min(ceil_intdiv((unsigned int)n_streams_used_in_this_call, threads_per_block), (unsigned int)NUM_VECTOR_OP_BLOCKS);
 
+            if (n_streams > (unsigned int)NUM_VECTOR_OP_THREADS_PER_BLOCK * (unsigned int)NUM_VECTOR_OP_BLOCKS)
+            {
+                PyErr_Format(PyExc_ValueError, "On GPU, n_streams should be at most %%u",
+                    (unsigned int)NUM_VECTOR_OP_THREADS_PER_BLOCK * (unsigned int)NUM_VECTOR_OP_BLOCKS);
+                %(fail)s;
+            }
+
             if (threads_per_block * n_blocks < n_streams)
             {
                 if (! %(nodename)s_printed_warning)
@@ -761,7 +768,7 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (8,)
+        return (9,)
 
 
 class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):

theano/sandbox/test_rng_mrg.py

@@ -17,6 +17,7 @@ import unittest
 from theano.tests import unittest_tools as utt
 from nose.plugins.skip import SkipTest
 from nose.plugins.attrib import attr
+from nose.tools import assert_raises
 
 #TODO: test gpu
 # Done in test_consistency_GPU_{serial,parallel}
@@ -305,6 +306,22 @@ def test_consistency_GPU_parallel():
     samples = numpy.array(samples).flatten()
     assert(numpy.allclose(samples, java_samples))
 
+def test_GPU_nstreams_limit():
+    """Verify that a ValueError is raised when n_streams
+    is greater than 2**20 on GPU. This is the value of
+    (NUM_VECTOR_OP_THREADS_PER_BLOCK * NUM_VECTOR_OP_BLOCKS).
+    """
+    if not cuda_available:
+        raise SkipTest('Optional package cuda not available')
+
+    seed = 12345
+    R = MRG_RandomStreams(seed=seed, use_cuda=True)
+    
+    def eval_uniform(size, nstreams):
+        return R.uniform(size=size, nstreams=nstreams, dtype='float32').eval()
+    
+    eval_uniform((10,), 2**20)
+    assert_raises(ValueError, eval_uniform, (10,), 2**20 + 1)
 
 def test_consistency_GPUA_serial():
     '''Verify that the random numbers generated by GPUA_mrg_uniform, serially,