2 bug fixes. Make choice on the GPU with replace work well.

theano/gpuarray/multinomial.py

@@ -507,7 +507,7 @@ def local_gpua_multinomial_wor(op, context_name, inputs, outputs):
     p, u, n = inputs
     m, = outputs
     if ((p.dtype == u.dtype == 'float32') and (m.dtype == 'int64')):
-        gpu_op = GPUAChoiceFromUniform(op.odtype)
+        gpu_op = GPUAChoiceFromUniform(**op._props_dict())
         return GpuDimShuffle([False, False], [1, 0])(
             gpu_op(p, u, n))
 

theano/gpuarray/tests/test_multinomial.py

@@ -327,30 +327,34 @@ def test_gpu_opt_wor():
     p = tensor.fmatrix()
     u = tensor.fvector()
     n = tensor.iscalar()
-    m = multinomial.ChoiceFromUniform(odtype='auto')(p, u, n)
-    assert m.dtype == 'int64', m.dtype
-
-    f = function([p, u, n], m, allow_input_downcast=True, mode=mode_with_gpu)
-    assert any([type(node.op) is GPUAChoiceFromUniform
-                for node in f.maker.fgraph.toposort()])
-    n_samples = 3
-    pval = np.arange(10000 * 4, dtype='float32').reshape((10000, 4)) + 0.1
-    pval = pval / pval.sum(axis=1)[:, None]
-    uval = np.ones(pval.shape[0] * n_samples) * 0.5
-    f(pval, uval, n_samples)
+    for replace in [False, True]:
+        m = multinomial.ChoiceFromUniform(odtype='auto',
+                                          replace=replace)(p, u, n)
+        assert m.dtype == 'int64', m.dtype
+
+        f = function([p, u, n], m, allow_input_downcast=True,
+                     mode=mode_with_gpu)
+        assert any([type(node.op) is GPUAChoiceFromUniform
+                    for node in f.maker.fgraph.toposort()])
+        n_samples = 3
+        pval = np.arange(10000 * 4, dtype='float32').reshape((10000, 4)) + 0.1
+        pval = pval / pval.sum(axis=1)[:, None]
+        uval = np.ones(pval.shape[0] * n_samples) * 0.5
+        f(pval, uval, n_samples)
 
-    # Test with a row, it was failing in the past.
-    r = tensor.frow()
-    m = multinomial.ChoiceFromUniform('auto')(r, u, n)
-    assert m.dtype == 'int64', m.dtype
+        # Test with a row, it was failing in the past.
+        r = tensor.frow()
+        m = multinomial.ChoiceFromUniform('auto', replace=replace)(r, u, n)
+        assert m.dtype == 'int64', m.dtype
 
-    f = function([r, u, n], m, allow_input_downcast=True, mode=mode_with_gpu)
-    assert any([type(node.op) is GPUAChoiceFromUniform
-                for node in f.maker.fgraph.toposort()])
-    pval = np.arange(1 * 4, dtype='float32').reshape((1, 4)) + 0.1
-    pval = pval / pval.sum(axis=1)[:, None]
-    uval = np.ones_like(pval[:, 0]) * 0.5
-    f(pval, uval, 1)
+        f = function([r, u, n], m, allow_input_downcast=True,
+                     mode=mode_with_gpu)
+        assert any([type(node.op) is GPUAChoiceFromUniform
+                    for node in f.maker.fgraph.toposort()])
+        pval = np.arange(1 * 4, dtype='float32').reshape((1, 4)) + 0.1
+        pval = pval / pval.sum(axis=1)[:, None]
+        uval = np.ones_like(pval[:, 0]) * 0.5
+        f(pval, uval, 1)
 
 
 def test_unpickle_legacy_op():

theano/sandbox/multinomial.py

@@ -212,7 +212,7 @@ class ChoiceFromUniform(MultinomialFromUniform):
 
     """
 
-    __props__ = ("replace",)
+    __props__ = ("odtype", "replace",)
 
     def __init__(self, odtype, replace=False, *args, **kwargs):
         self.replace = replace