applying requested changes

theano/sandbox/cuda/__init__.py

@@ -324,11 +324,6 @@ if cuda_available:
             ftensor3, ftensor4,
             scalar, vector, matrix, row, col,
             tensor3, tensor4)
-    warnings.warn(
-        "GpuFlatten class is deprecated, "
-        "please use gpu_flatten method instead.",
-        DeprecationWarning,
-        stacklevel=4)
     from .basic_ops import (host_from_gpu, gpu_from_host,
             as_cuda_array, as_cuda_ndarray_variable)
     import cuda_ndarray

theano/sandbox/cuda/basic_ops.py

@@ -3322,16 +3322,22 @@ class GpuIncSubtensor(tensor.IncSubtensor, GpuOp):
         return ()
 
 
-class GpuFlatten(gof.HideC, tensor.Reshape, GpuOp):
+class GpuFlatten(gof.HideC, tensor.Flatten, GpuOp):
     """
     Implement Flatten on the gpu.
 
-    Note: The interface GpuFlatten is deprecated, you should use gpu_flatten
+    .. note:: The interface GpuFlatten is deprecated, you should use gpu_flatten.
     """
+    def __init__(self):
+        warnings.warn(
+            "GpuFlatten class is deprecated, "
+            "please use gpu_flatten method instead.",
+            DeprecationWarning,
+            stacklevel=4)
 
     def make_node(self, x):
         assert isinstance(x.type, CudaNdarrayType)
-        rval = flatten(x)
+        rval = tensor.Flatten.make_node(self, x)
         host_out_broadcastable = rval.outputs[0].type.broadcastable
         out_type = CudaNdarrayType(broadcastable=host_out_broadcastable)
         return Apply(self, [x], [out_type()])
@@ -3341,14 +3347,23 @@ class GpuFlatten(gof.HideC, tensor.Reshape, GpuOp):
 def gpu_flatten(x, outdim=1):
     """
     Implement flatten on the gpu.
+    Reshapes the variable x by keeping
+    the first outdim-1 dimension size(s) of x the same,
+    and making the last dimension size of x equal to
+    the multiplication of its remaining dimension size(s).
 
-    :param x: the variable that should be reshaped.
-    :type x: theano.tensor.var.TensorVariable
+    Parameters
+    ----------
+        x : theano.tensor.var.TensorVariable
+            the variable that should be reshaped.
 
-    :param outdim: the number of dimensions of the returned variable
-    :type outdim: int
+        outdim : int
+            the number of dimensions of the returned variable
 
-    :returns: the flattend variable with dimensionality of outdim
+    Returns
+    -------
+    theano.tensor.var.TensorVariable
+        the flattend variable with dimensionality of outdim
     """
     x = as_cuda_ndarray_variable(x)
     if outdim > 1:

theano/sandbox/cuda/opt.py

@@ -981,14 +981,14 @@ def local_gpu_flatten(node):
         if host_input.owner and \
            isinstance(host_input.owner.op, tensor.Flatten):
             outdim = host_input.owner.op.outdim
-            return [gpu_flatten(outdim)(
+            return [gpu_flatten(host_input.owner.inputs[0], outdim)(
                 as_cuda_ndarray_variable(host_input.owner.inputs[0]))]
     if isinstance(node.op, tensor.Flatten):
         x, shp= node.inputs
         outdim = node.op.outdim
         if x.owner and isinstance(x.owner.op, HostFromGpu):
             gpu_x, = x.owner.inputs
-            return [host_from_gpu(gpu_flatten(outdim)(gpu_x))]
+            return [host_from_gpu(gpu_flatten(host_input.owner.inputs[0], outdim)(gpu_x))]
     return False
 
 

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -308,6 +308,7 @@ def test_flatten():
     f = theano.function([x], x.flatten(), mode=mode_with_gpu)
     assert any([node for node in f.maker.fgraph.toposort()
                 if isinstance(node.op, B.GpuReshape)])
+    assert theano.tensor.is_flat(x.flatten())
     assert len(f([[0., 0.], [0., 0.]]).shape) == 1
 
 

theano/tensor/basic.py

@@ -4506,7 +4506,7 @@ class Flatten(Op):
     Flattens a tensor to `outdim` dimensions by preserving the leading
     outdim - 1 shape components.
 
-    Note: The interface Flatten(Op) is deprecated, you should use flatten
+    .. note:: The interface Flatten(Op) is deprecated, you should use flatten.
     """
     view_map = {0: [0]}
 
@@ -4659,16 +4659,26 @@ class Flatten(Op):
 
 def is_flat(node, outdim=1):
     """
-    verifies the dimensionality of variable is correct.
+    Verifies the dimensionality of the node's variable is equal to
+    outdim. This method is usually called after flatten method on a
+    variable, where the first outdim-1 dimension size(s) of the variable
+    is kept intact, and the last dimension size of the variable is made
+    equal to the multiplication of its remaining dimension size(s), such that
+    the variable would end up with as many dimension as outdim.
 
-    :param node: the theano node on which the dimensionality is checked.
-    :type node: theano.tensor.var.TensorVariable
+    Parameters
+    ----------
+        node : theano.tensor.var.TensorVariable
+            the theano node on which the dimensionality is checked.
 
-    :param outdim: the expected dimensionality of node.
-    :type outdim: int
+        outdim : int
+            the expected dimensionality of node.
 
-    :returns: the comparison result of node's dim
-              and the expected outdim.
+    Returns
+    -------
+    bool
+        the comparison result of node's dim
+        and the expected outdim.
     """
     return node.ndim == outdim
 
@@ -4676,19 +4686,23 @@ def is_flat(node, outdim=1):
 def flatten(x, outdim=1):
     """
     Reshapes the variable x by keeping
-    the first outdim-1 dimension(s) of x the same,
-    and making the last dimension of x equal to
-    the multiplication of its remaining dimensions.
+    the first outdim-1 dimension size(s) of x the same,
+    and making the last dimension size of x equal to
+    the multiplication of its remaining dimension size(s).
 
-    :param x: the theano variable that should be reshaped.
-    :type x: theano.tensor.var.TensorVariable
+    Parameters
+    ----------
+        x : theano.tensor.var.TensorVariable
+            the variable that should be reshaped.
 
-    :param outdim: the number of dimensions of the returned variable
-    :type outdim: int
+        outdim : int
+            the number of dimensions of the returned variable
 
-    :returns: the flattend variable with dimensionality of outdim
+    Returns
+    -------
+    theano.tensor.var.TensorVariable
+        the flattend variable with dimensionality of outdim
     """
-    outdim = int(outdim)
     # Any input variable can be flattened to have outdim of 1,
     # even if it's a scalar. Otherwise, outdim must be positive
     # and smaller than x.ndim.

theano/tensor/nnet/tests/test_sigm.py

@@ -377,7 +377,7 @@ class T_softplus_opts(unittest.TestCase):
         f = theano.function([x], out, mode=self.m)
         topo = f.maker.fgraph.toposort()
         assert len(topo) == 3
-        assert tensor.is_flat(topo[0])
+        assert tensor.is_flat(topo[0].outputs[0])
         assert isinstance(topo[1].op.scalar_op,
                           theano.tensor.nnet.sigm.ScalarSoftplus)
         assert isinstance(topo[2].op.scalar_op, theano.scalar.Neg)

theano/tensor/tests/test_basic.py

@@ -18,6 +18,7 @@ from nose.plugins.skip import SkipTest
 import numpy
 from numpy.testing import dec, assert_array_equal, assert_allclose
 from distutils.version import LooseVersion
+from functools import partial
 
 import theano
 from theano.compat import PY3, exc_message, operator_div
@@ -5194,7 +5195,6 @@ def test_flatten_outdim2():
     f = inplace_func([a], c)
     assert numpy.all(f(a_val) == a_val)
 
-    from functools import partial
     flatten_2 = partial(flatten, outdim=2)
     utt.verify_grad(flatten_2, [a_val])
 
@@ -5210,7 +5210,6 @@ def test_flatten_outdim2_of_3():
     f = inplace_func([a], c)
     assert numpy.all(f(a_val) == c_val)
 
-    from functools import partial
     flatten_2 = partial(flatten, outdim=2)
     utt.verify_grad(flatten_2, [a_val])