Merge pull request #2654 from Saizheng/dev1

theano/tensor/extra_ops.py

@@ -647,9 +647,47 @@ def repeat(x, repeats, axis=None):
 
     .. versionadded:: 0.6
     """
-    return RepeatOp(axis=axis)(x, repeats)
+    repeats = tensor.as_tensor_variable(repeats)
 
+    if repeats.ndim > 1:
+        raise ValueError('The dimension of repeats should not exceed 1.')
 
+    if repeats.ndim == 1:
+        return RepeatOp(axis=axis)(x, repeats)
+    else:
+        if axis == None:
+           axis = 0 
+           x = x.flatten()
+        else:
+            if axis >= x.ndim:
+                raise ValueError('Axis should not exceed x.ndim-1.')
+            if axis < 0:
+                axis = x.ndim+axis
+
+        shape = [x.shape[i] for i in xrange(x.ndim)]
+        
+        # shape_ is the shape of the intermediate tensor which has
+        # an additional dimension comparing to x. We use alloc to
+        # allocate space for this intermediate tensor to replicate x
+        # along that additional dimension.
+        shape_ = shape[:]
+        shape_.insert(axis+1, repeats)
+
+        # shape is now the shape of output, where shape[axis] becomes
+        # shape[axis]*repeats.
+        shape[axis] = shape[axis]*repeats
+
+        # dims_ is the dimension of that intermediate tensor. 
+        dims_ = list(numpy.arange(x.ndim))
+        dims_.insert(axis+1, 'x')
+
+        # After the original tensor is duplicated along the additional
+        # dimension, we reshape it to the expected output shape, and 
+        # return the output z.
+        z = tensor.alloc(x.dimshuffle(*dims_), *shape_).reshape(shape) 
+        return z
+
+ 
 class Bartlett(gof.Op):
     # See function bartlett for docstring
     def __eq__(self, other):