Make SparseVariable test of Theano memory contract use the generic test fct.…

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -802,7 +802,12 @@ def test_duplicate_arg_elemwise():
 
 
 import theano.tensor.tests.test_basic
-test_shared_options = theano.tensor.tests.test_basic.makeSharedTester(tcn.shared_constructor, 'float32', False, False, False, cuda_ndarray.CudaNdarray, theano.tensor.exp, numpy.exp)
+test_shared_options = theano.tensor.tests.test_basic.makeSharedTester(
+    tcn.shared_constructor, 'float32', False, False, False,
+    cuda_ndarray.CudaNdarray,
+    lambda a: isinstance(a,cuda_ndarray.CudaNdarray),
+    theano.tensor.exp, numpy.exp,
+    add_matrix_ = True)
 
 if __name__ == '__main__':
     test_many_arg_elemwise()

theano/sparse/tests/test_basic.py

@@ -440,99 +440,13 @@ class test_structureddot(unittest.TestCase):
             self.failUnless(numpy.allclose(theano_result, scipy_result))
             self.failIf(theano_time > overhead_rtol*scipy_time + overhead_tol)
 
-
-def test_shared_dont_alias():
-    rng = numpy.random.RandomState([3,5,17])
-    x_lil = random_lil((2,4), 'float64', 5)
-    x = sp.csr_matrix(x_lil) 
-    densifier = rng.randn(*x.shape)
-
-    x_shared = theano.shared(x, borrow = False)
-    prod = theano.sparse.mul_s_d(x_shared,densifier)
-
-    prod_func = theano.function([],prod)
-
-    prod_val = prod_func().todense()
-
-    x_dense_fake = x.todense()
-    x_dense = numpy.asarray(x_dense_fake)
-    scipy_prod_val = x_dense * densifier
-    assert numpy.allclose(scipy_prod_val, prod_val)
-
-    for i in xrange(x.shape[0]):
-        for j in xrange(x.shape[1]):
-            if x[i,j] != 0:
-                x[i,j] += 1
-
-    prod_val_2 = prod_func().todense()
-
-    #value used to construct should not alias with internal
-    assert numpy.allclose(prod_val_2,prod_val)
-
-    x = x_shared.get_value(borrow = False)
-
-    for i in xrange(x.shape[0]):
-        for j in xrange(x.shape[1]):
-            if x[i,j] != 0:
-                x[i,j] += 1
-
-    prod_val_3 = prod_func().todense()
-
-    #value returned by access should not alias with internal
-    assert numpy.allclose(prod_val, prod_val_3)
-
-    #in this case we can alias
-    x = x_shared.get_value(borrow = True)
-    
-    for i in xrange(x.shape[0]):
-        for j in xrange(x.shape[1]):
-            if x[i,j] != 0:
-                x[i,j] += 1
-
-    
-    x_dense_fake = x.todense()
-    x_dense = numpy.asarray(x_dense_fake)
-    scipy_prod_val = x_dense * densifier
-
-
-    #this is not required by the contract but it is a feature we've implemented
-    assert numpy.allclose(scipy_prod_val, prod_func().todense())
-
-def test_shared_do_alias():
-    rng = numpy.random.RandomState([2,4,16])
-    x_lil = random_lil((2,4), 'float64', 5)
-    x = sp.csr_matrix(x_lil)
-
-    x_shared = theano.shared(x, borrow = True)
-
-    densifier = rng.randn(*x.shape)
-
-    prod = theano.sparse.mul_s_d(x_shared,densifier)
-
-    prod_func = theano.function([],prod)
-
-    prod_val = prod_func().todense()
-
-    x_dense_fake = x.todense()
-    x_dense = numpy.asarray(x_dense_fake)
-    scipy_prod_val = x_dense * densifier
-
-    assert numpy.allclose(scipy_prod_val, prod_val)
-
-    for i in xrange(x.shape[0]):
-        for j in xrange(x.shape[1]):
-            if x[i,j] != 0:
-                x[i,j] += 1    
-
-
-    x_dense_fake = x.todense()
-    x_dense = numpy.asarray(x_dense_fake)
-    scipy_prod_val = x_dense * densifier
-
-
-    #not required by the contract but it is a feature we've implemented
-    assert numpy.allclose(scipy_prod_val, prod_func().todense())
-
+import theano.tensor.tests.test_basic
+test_shared_options=theano.tensor.tests.test_basic.makeSharedTester(
+    theano.sparse.shared, 'float64',
+    True, True, True, scipy.sparse.csc_matrix, scipy.sparse.issparse,
+    lambda a: dense_from_sparse(a*2.),
+    lambda a: numpy.asarray((a*2).todense()),
+    scipy.sparse.csr_matrix)
 
 if __name__ == '__main__':
     unittest.main()

theano/tensor/tests/test_basic.py

@@ -3390,16 +3390,21 @@ def test_dimshuffle_duplicate():
     assert success
 
 def makeSharedTester(shared_constructor_,
-                              dtype_,
-                              get_value_borrow_true_alias_,
-                              shared_borrow_true_alias_,
-                              set_value_borrow_true_alias_,
-                              internal_type_,
-                              theano_fct_,
-                              ref_fct_):
+                     dtype_,
+                     get_value_borrow_true_alias_,
+                     shared_borrow_true_alias_,
+                     set_value_borrow_true_alias_,
+                     internal_type_,
+                     test_internal_type_,
+                     theano_fct_,
+                     ref_fct_,
+                     cast_value_ = numpy.asarray,
+                     add_matrix_ = False):
     """
     This is a generic fct to allow reusing the same test function
     for many shared variable of many types.
+
+    We must use /= as sparse type don't support other inplace operation.
     """
     class SharedTester(unittest.TestCase):
         shared_constructor = staticmethod(shared_constructor_)
@@ -3407,9 +3412,12 @@ def makeSharedTester(shared_constructor_,
         get_value_borrow_true_alias = get_value_borrow_true_alias_
         shared_borrow_true_alias = shared_borrow_true_alias_
         internal_type = internal_type_
+        test_internal_type = staticmethod(test_internal_type_)
         theano_fct = staticmethod(theano_fct_)
         ref_fct = staticmethod(ref_fct_)
         set_value_borrow_true_alias = set_value_borrow_true_alias_
+        cast_value = staticmethod(cast_value_)
+        add_matrix = add_matrix_
 
         def test_shared_dont_alias(self):
             dtype = self.dtype
@@ -3418,6 +3426,8 @@ def makeSharedTester(shared_constructor_,
 
             rng = numpy.random.RandomState([3,5,17])
             x = numpy.asarray(rng.uniform(0,1,[2,4]),dtype=dtype)
+            x = self.cast_value(x)
+
             x_ref = self.ref_fct(x)
             x_shared = self.shared_constructor(x, borrow = False)
             total = self.theano_fct(x_shared)
@@ -3428,7 +3438,7 @@ def makeSharedTester(shared_constructor_,
 
             assert numpy.allclose(self.ref_fct(x), total_val)
 
-            x += 1
+            x /= .5
 
             total_val_2 = total_func()
 
@@ -3437,7 +3447,7 @@ def makeSharedTester(shared_constructor_,
 
             x = x_shared.get_value(borrow = False)
 
-            x += 1
+            x /= .5
 
             total_val_3 = total_func()
 
@@ -3446,7 +3456,7 @@ def makeSharedTester(shared_constructor_,
 
             #in this case we can alias
             x = x_shared.get_value(borrow = True)
-            x += 1
+            x /= .5
 
             #this is not required by the contract but it is a feature we've 
             #implemented for some type of SharedVariable.
@@ -3463,6 +3473,8 @@ def makeSharedTester(shared_constructor_,
 
             rng = numpy.random.RandomState([3,5,17])
             x = numpy.asarray(rng.uniform(0,1,[2,4]),dtype=dtype)
+            x = self.cast_value(x)
+
             x_ref = self.ref_fct(x)
             x_shared = self.shared_constructor(x, borrow = False)
             total = self.theano_fct(x_shared)
@@ -3471,21 +3483,21 @@ def makeSharedTester(shared_constructor_,
 
             #in this case we can alias with the internal value
             x = x_shared.get_value(borrow = True, return_internal_type = True)
-            assert isinstance(x, self.internal_type)
+            assert self.test_internal_type(x)
             
-            values_to_add = numpy.ones(x.shape,dtype=dtype)
-            if not isinstance(values_to_add, self.internal_type):
-                values_to_add = self.internal_type(values_to_add)#supported for cudandarray, but not ndarray.
-            x += values_to_add#supported by ndarray and CudaNdarray
+            values_to_add = .5
+            if self.add_matrix:
+                values_to_add = self.internal_type(numpy.ones(x.shape,dtype=dtype)/2)#supported for cudandarray, but not ndarray.
+            x /= values_to_add#supported by ndarray and CudaNdarray
 
             #this is not required by the contract but it is a feature we can 
             #implement for some type of SharedVariable.
             assert numpy.allclose(self.ref_fct(x), total_func())
             
             x = x_shared.get_value(borrow = False, return_internal_type = True)
-            assert isinstance(x, self.internal_type)
-            
-            x += values_to_add#supported by ndarray and CudaNdarray
+            assert self.test_internal_type(x)
+            assert x is not x_shared.container.value
+            x /= values_to_add#supported by ndarray and CudaNdarray
 
             #this is required by the contract
             assert not numpy.allclose(self.ref_fct(x), total_func())
@@ -3497,6 +3509,8 @@ def makeSharedTester(shared_constructor_,
 
             rng = numpy.random.RandomState([3,5,17])
             x = numpy.asarray(rng.uniform(0,1,[2,4]),dtype=dtype)
+            x = self.cast_value(x)
+
             x_orig = x
             x_orig_copy = x.copy()
             x_ref = self.ref_fct(x)
@@ -3508,29 +3522,29 @@ def makeSharedTester(shared_constructor_,
             #test if that theano shared variable optimize set_value(borrow=True)
             get_x = x_shared.get_value(borrow=True)
             assert get_x is not x_orig#borrow=False to shared_constructor
-            get_x +=1
+            get_x /= .5
             x_shared.set_value(get_x, borrow=True)
             x = x_shared.get_value(borrow=True)
             if self.set_value_borrow_true_alias:
                 assert x is get_x
             else:
                 assert x is not get_x
-            assert numpy.allclose(self.ref_fct(x_orig+1),self.ref_fct(x))
+            assert numpy.allclose(self.ref_fct(x_orig/.5),self.ref_fct(x))
 
             #test optimized get set value on the gpu(don't pass data to the cpu)
             get_x = x_shared.get_value(borrow=True, return_internal_type=True)
             assert get_x is not x_orig#borrow=False to shared_constructor
-            assert isinstance(get_x, self.internal_type)
-            values_to_add = numpy.ones(x.shape,dtype=dtype)
-            if not isinstance(values_to_add, self.internal_type):
-                values_to_add = self.internal_type(values_to_add)#supported for cudandarray, but not ndarray.
-            assert isinstance(values_to_add, self.internal_type)
-
-            get_x += values_to_add#supported by ndarray and CudaNdarray
-            assert isinstance(get_x, self.internal_type)
+            assert self.test_internal_type(get_x)
+            values_to_add = .5
+            if self.add_matrix:
+                values_to_add = self.internal_type(numpy.ones(x.shape,dtype=dtype)/2)#supported for cudandarray, but not ndarray.
+                assert self.test_internal_type(values_to_add)
+
+            get_x /= values_to_add#supported by ndarray and CudaNdarray
+            assert self.test_internal_type(get_x)
             x_shared.set_value(get_x, borrow=True)
             x = x_shared.get_value(borrow=True, return_internal_type=True)
-            assert isinstance(x, self.internal_type)
+            assert self.test_internal_type(x)
             assert x is get_x
 
             ################ TODO test Out.
@@ -3541,6 +3555,7 @@ def makeSharedTester(shared_constructor_,
 
             rng = numpy.random.RandomState([2,4,16])
             x = numpy.asarray(rng.uniform(1,2,[4,2]),dtype=dtype)
+            x = self.cast_value(x)
             x_ref = self.ref_fct(x)
 
             x_shared = self.shared_constructor(x, borrow = True)
@@ -3553,7 +3568,7 @@ def makeSharedTester(shared_constructor_,
 
             assert numpy.allclose(self.ref_fct(x), total_val)
 
-            x += 1
+            x /= .5
 
             #not required by the contract but it is a feature we've implemented
             if self.shared_borrow_true_alias:
@@ -3564,8 +3579,10 @@ def makeSharedTester(shared_constructor_,
     return SharedTester
 
 test_shared_options=makeSharedTester(tensor.shared, 'float64',
-                                              True, True, True, numpy.ndarray,
-                                              theano.tensor.sum, numpy.sum)
+                                     True, True, True,
+                                     numpy.ndarray,
+                                     lambda a: isinstance(a,numpy.ndarray),
+                                     theano.tensor.sum, numpy.sum)
 
 
 if __name__ == '__main__':