diff --git a/.gitignore b/.gitignore
index 1aa2ce47da11..d62c63f403e9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -53,3 +53,6 @@ Debug
 # Emacs
 .clang_complete
 .dir-locals.el
+__pycache__
+*.pkl
+*
\ No newline at end of file
diff --git a/.travis.yml b/.travis.yml
index ec2aa8dab0a3..f01653aec86f 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -8,6 +8,8 @@ env:
     - TASK=lint LINT_LANG=python
     - TASK=doc
     - TASK=build CXX=g++
+    - TASK=python CXX=g++
+    - TASK=python3 CXX=g++
     - TASK=unittest_gtest CXX=g++
 
 # dependent apt packages
@@ -27,12 +29,18 @@ addons:
       - g++-4.8
       - clang
       - python-numpy
+      - python-nose
+      - python3-numpy
+      - python3-dev
+      - python3-nose
+
 
 before_install:
   - export NVCC_PREFIX=${HOME}
   - if [ "$CXX" = "g++" ]; then export CXX="g++-4.8" CC="gcc-4.8"; fi
   - scripts/build_dmlc.sh
   - export TRAVIS=dmlc-core/scripts/travis
+  - export PYTHONPATH=${PYTHONPATH}:${PWD}/python
   - source ${TRAVIS}/travis_setup_env.sh
 
 
@@ -40,7 +48,6 @@ install:
   - pip install cpplint pylint --user `whoami`
   - if [ "$CXX" = "g++" ]; then export CXX="g++-4.8" CC="gcc-4.8"; fi
 
-
 script:
   - scripts/travis_script.sh
 
diff --git a/doc/Doxyfile b/doc/Doxyfile
index aeef012f2384..407ea96e95ab 100644
--- a/doc/Doxyfile
+++ b/doc/Doxyfile
@@ -1925,7 +1925,7 @@ PERLMOD_MAKEVAR_PREFIX =
 # C-preprocessor directives found in the sources and include files.
 # The default value is: YES.
 
-ENABLE_PREPROCESSING   = YES
+ENABLE_PREPROCESSING   = NO
 
 # If the MACRO_EXPANSION tag is set to YES doxygen will expand all macro names
 # in the source code. If set to NO only conditional compilation will be
diff --git a/doc/index.md b/doc/index.md
index 54c20e37c729..9d3b7c0e8805 100644
--- a/doc/index.md
+++ b/doc/index.md
@@ -5,6 +5,7 @@ Contents
 --------
 * [Python User Guide](python/python_guide.md)
 * [C++ Developer Guide](cpp/cpp_guide.md)
+* [Doxygen Version of C++ API](https://mxnet.readthedocs.org/en/latest/doxygen)
 
 Indices and tables
 ------------------
diff --git a/python/mxnet/__init__.py b/python/mxnet/__init__.py
index 77748dd1950c..c7720dcbd935 100644
--- a/python/mxnet/__init__.py
+++ b/python/mxnet/__init__.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python
-# pylint: disable=invalid-name, protected-access
 # coding: utf-8
 """MXNet: a concise, fast and flexible framework for deep learning
 
@@ -10,6 +9,7 @@
 from __future__ import absolute_import
 
 from .context import Context, current_context
+from .base import MXNetError
 from . import narray
 from . import symbol
 
diff --git a/python/mxnet/base.py b/python/mxnet/base.py
index c514d6939988..6cf8c616f805 100644
--- a/python/mxnet/base.py
+++ b/python/mxnet/base.py
@@ -9,13 +9,18 @@
 import platform
 import numpy as np
 
+__all__ = ['MXNetError']
 #----------------------------
 # library loading
 #----------------------------
 if sys.version_info[0] == 3:
     string_types = str,
+    # this function is needed for python3
+    # to convert ctypes.char_p .value back to python str
+    py_str = lambda x: x.decode('utf-8')
 else:
     string_types = basestring,
+    py_str = lambda x: x
 
 
 class MXNetError(Exception):
@@ -86,8 +91,7 @@ def check_call(ret):
         return value from API calls
     """
     if ret != 0:
-        raise MXNetError(_LIB.MXGetLastError())
-
+        raise MXNetError(py_str(_LIB.MXGetLastError()))
 
 def c_str(string):
     """Create ctypes char * from a python string
@@ -98,7 +102,8 @@ def c_str(string):
 
     Returns
     -------
-    a char pointer that can be passed to C API
+    str : c_char_p
+        A char pointer that can be passed to C API
     """
     return ctypes.c_char_p(string.encode('utf-8'))
 
@@ -116,7 +121,8 @@ def c_array(ctype, values):
 
     Returns
     -------
-    created ctypes array
+    out : ctypes array
+        Created ctypes array
     """
     return (ctype * len(values))(*values)
 
@@ -136,7 +142,8 @@ def ctypes2numpy_shared(cptr, shape):
 
     Returns
     -------
-    a numpy array : numpy array
+    out : numpy_array
+        A numpy array : numpy array
     """
     if not isinstance(cptr, ctypes.POINTER(mx_float)):
         raise RuntimeError('expected float pointer')
@@ -145,3 +152,5 @@ def ctypes2numpy_shared(cptr, shape):
         size *= s
     dbuffer = (mx_float * size).from_address(ctypes.addressof(cptr.contents))
     return np.frombuffer(dbuffer, dtype=np.float32).reshape(shape)
+
+
diff --git a/python/mxnet/narray.py b/python/mxnet/narray.py
index 0693c2fa2cb4..78ac5e0471fa 100644
--- a/python/mxnet/narray.py
+++ b/python/mxnet/narray.py
@@ -1,12 +1,11 @@
 # coding: utf-8
-# pylint: disable=invalid-name, protected-access, too-many-locals, fixme, no-member
 """NArray interface of mxnet"""
 from __future__ import absolute_import
 
 import ctypes
 import sys
 from .base import _LIB
-from .base import c_array
+from .base import c_array, py_str
 from .base import mx_uint, mx_float, NArrayHandle, FunctionHandle
 from .base import ctypes2numpy_shared
 from .base import check_call
@@ -49,7 +48,7 @@ class NArray(object):
 
     NArray is basic ndarray/Tensor like data structure in mxnet.
     """
-
+    # pylint: disable= no-member
     def __init__(self, handle):
         """initialize a new NArray
 
@@ -165,7 +164,7 @@ def copyto(self, other):
             return NArray._copyto(self, out=hret)
         else:
             raise TypeError('copyto do not support type ' + type(other))
-
+    # pylint: enable= no-member
 
 def create(shape, ctx=Context.default_ctx):
     """Create a new NArray, with specified shape.
@@ -181,10 +180,9 @@ def create(shape, ctx=Context.default_ctx):
     """
     return NArray(handle=_new_alloc_handle(shape, ctx, False))
 
-
+# pylint: disable=too-many-locals, invalid-name
 def _make_narray_function(handle):
     """Create a NArray function from the FunctionHandle."""
-    # Constants for type masks.
     NARRAY_ARG_BEFORE_SCALAR = 1
     ACCEPT_EMPTY_MUTATE_TARGET = 1 << 2
     # Get the property of NArray
@@ -193,12 +191,12 @@ def _make_narray_function(handle):
     n_scalars = mx_uint()
     n_mutate_vars = mx_uint()
     type_mask = ctypes.c_int()
-    check_call(_LIB.MXFuncDescribe( \
-            handle, \
-            ctypes.byref(n_used_vars), \
-            ctypes.byref(n_scalars), \
-            ctypes.byref(n_mutate_vars), \
-            ctypes.byref(type_mask)))
+    check_call(_LIB.MXFuncDescribe(
+        handle,
+        ctypes.byref(n_used_vars),
+        ctypes.byref(n_scalars),
+        ctypes.byref(n_mutate_vars),
+        ctypes.byref(type_mask)))
     n_mutate_vars = n_mutate_vars.value
     n_used_vars = n_used_vars.value
     n_scalars = n_scalars.value
@@ -220,19 +218,19 @@ def _make_narray_function(handle):
     arg_types = ctypes.POINTER(ctypes.c_char_p)()
     arg_descs = ctypes.POINTER(ctypes.c_char_p)()
 
-    check_call(_LIB.MXFuncGetInfo( \
-            handle, ctypes.byref(name), ctypes.byref(desc), \
-            ctypes.byref(num_args), \
-            ctypes.byref(arg_names), \
-            ctypes.byref(arg_types), \
-            ctypes.byref(arg_descs)))
-    func_name = name.value
+    check_call(_LIB.MXFuncGetInfo(
+        handle, ctypes.byref(name), ctypes.byref(desc),
+        ctypes.byref(num_args),
+        ctypes.byref(arg_names),
+        ctypes.byref(arg_types),
+        ctypes.byref(arg_descs)))
+    func_name = py_str(name.value)
 
     param_str = []
     for i in range(num_args.value):
-        ret = '%s : %s' % (arg_names[i], arg_types[i])
+        ret = '%s : %s' % (py_str(arg_names[i]), py_str(arg_types[i]))
         if len(arg_descs[i]) != 0:
-            ret += '\n    ' + arg_descs[i]
+            ret += '\n    ' + py_str(arg_descs[i])
         param_str.append(ret)
 
     doc_str = ('%s\n\n' +
@@ -245,7 +243,7 @@ def _make_narray_function(handle):
                '-------\n' +
                'out : NArray\n'+
                '    The output of binary function.')
-    doc_str = doc_str % (desc.value, '\n'.join(param_str))
+    doc_str = doc_str % (py_str(desc.value), '\n'.join(param_str))
 
     # Definition of internal functions.
     def binary_narray_function(lhs, rhs, out=None):
@@ -258,11 +256,10 @@ def binary_narray_function(lhs, rhs, out=None):
             if not accept_empty_mutate:
                 raise TypeError('argument out is required to call %s' % func_name)
             out = NArray(_new_empty_handle())
-        check_call(_LIB.MXFuncInvoke( \
-                handle, \
-                c_array(NArrayHandle, (lhs.handle, rhs.handle)), \
-                c_array(mx_float, ()), \
-                c_array(NArrayHandle, (out.handle,))))
+        check_call(_LIB.MXFuncInvoke(handle,
+                                     c_array(NArrayHandle, (lhs.handle, rhs.handle)),
+                                     c_array(mx_float, ()),
+                                     c_array(NArrayHandle, (out.handle,))))
         return out
 
     def unary_narray_function(src, out=None):
@@ -327,7 +324,7 @@ def generic_narray_function(*args, **kwargs):
     ret_function.__name__ = func_name
     ret_function.__doc__ = doc_str
     return ret_function
-
+# pylint: enable=too-many-locals, invalid-name
 
 def _init_narray_module():
     """List and add all the narray functions to current module."""
diff --git a/python/mxnet/symbol.py b/python/mxnet/symbol.py
index 899f78ec22b8..c35f84fda25d 100644
--- a/python/mxnet/symbol.py
+++ b/python/mxnet/symbol.py
@@ -1,12 +1,12 @@
 # coding: utf-8
-# pylint: disable=invalid-name, protected-access, too-many-locals, fixme
+# pylint: disable=invalid-name, protected-access, fixme
 """Symbol support of mxnet"""
 from __future__ import absolute_import
 
 import ctypes
 import sys
 from .base import _LIB
-from .base import c_array, c_str, mx_uint, string_types
+from .base import c_array, c_str, mx_uint, py_str, string_types
 from .base import NArrayHandle, ExecutorHandle, SymbolHandle
 from .base import check_call
 from .context import Context
@@ -92,8 +92,8 @@ def _compose(self, *args, **kwargs):
         else:
             keys = None
             args = c_array(SymbolHandle, [s.handle for s in args])
-        check_call(_LIB.MXSymbolCompose( \
-                self.handle, name, num_args, keys, args))
+        check_call(_LIB.MXSymbolCompose(
+            self.handle, name, num_args, keys, args))
 
     def list_arguments(self):
         """List all the arguments in the symbol.
@@ -105,9 +105,9 @@ def list_arguments(self):
         """
         size = ctypes.c_uint()
         sarr = ctypes.POINTER(ctypes.c_char_p)()
-        check_call(_LIB.MXSymbolListArguments( \
-                self.handle, ctypes.byref(size), ctypes.byref(sarr)))
-        return [sarr[i] for i in range(size.value)]
+        check_call(_LIB.MXSymbolListArguments(
+            self.handle, ctypes.byref(size), ctypes.byref(sarr)))
+        return [py_str(sarr[i]) for i in range(size.value)]
 
     def list_returns(self):
         """List all returns in the symbol.
@@ -119,9 +119,9 @@ def list_returns(self):
         """
         size = ctypes.c_uint()
         sarr = ctypes.POINTER(ctypes.c_char_p)()
-        check_call(_LIB.MXSymbolListReturns( \
-                self.handle, ctypes.byref(size), ctypes.byref(sarr)))
-        return [sarr[i] for i in range(size.value)]
+        check_call(_LIB.MXSymbolListReturns(
+            self.handle, ctypes.byref(size), ctypes.byref(sarr)))
+        return [py_str(sarr[i]) for i in range(size.value)]
 
     def infer_shape(self, *args, **kwargs):
         """Infer the shape of outputs and arguments of given known shapes of arguments.
@@ -148,6 +148,7 @@ def infer_shape(self, *args, **kwargs):
             List of shapes of outputs.
             The order is in the same order as list_returns()
         """
+        # pylint: disable=too-many-locals
         if len(args) != 0 and len(kwargs) != 0:
             raise ValueError('Can only specify known argument \
                     shapes either by positional or kwargs way.')
@@ -176,26 +177,27 @@ def infer_shape(self, *args, **kwargs):
         out_shape_ndim = ctypes.POINTER(mx_uint)()
         out_shape_data = ctypes.POINTER(ctypes.POINTER(mx_uint))()
         complete = ctypes.c_int()
-        check_call(_LIB.MXSymbolInferShape( \
-                self.handle, len(indptr) - 1, \
-                c_array(ctypes.c_char_p, keys), \
-                c_array(mx_uint, indptr), \
-                c_array(mx_uint, sdata), \
-                ctypes.byref(arg_shape_size), \
-                ctypes.byref(arg_shape_ndim), \
-                ctypes.byref(arg_shape_data), \
-                ctypes.byref(out_shape_size), \
-                ctypes.byref(out_shape_ndim), \
-                ctypes.byref(out_shape_data), \
-                ctypes.byref(complete)))
+        check_call(_LIB.MXSymbolInferShape(
+            self.handle, len(indptr) - 1,
+            c_array(ctypes.c_char_p, keys),
+            c_array(mx_uint, indptr),
+            c_array(mx_uint, sdata),
+            ctypes.byref(arg_shape_size),
+            ctypes.byref(arg_shape_ndim),
+            ctypes.byref(arg_shape_data),
+            ctypes.byref(out_shape_size),
+            ctypes.byref(out_shape_ndim),
+            ctypes.byref(out_shape_data),
+            ctypes.byref(complete)))
         if complete.value != 0:
-            arg_shapes = [tuple(arg_shape_data[i][:arg_shape_ndim[i]]) \
-                    for i in range(arg_shape_size.value)]
-            out_shapes = [tuple(out_shape_data[i][:out_shape_ndim[i]]) \
-                    for i in range(out_shape_size.value)]
+            arg_shapes = [
+                tuple(arg_shape_data[i][:arg_shape_ndim[i]]) for i in range(arg_shape_size.value)]
+            out_shapes = [
+                tuple(out_shape_data[i][:out_shape_ndim[i]]) for i in range(out_shape_size.value)]
             return (arg_shapes, out_shapes)
         else:
             return (None, None)
+        # pylint: enable=too-many-locals
 
     def debug_str(self):
         """Get a debug string.
@@ -206,9 +208,9 @@ def debug_str(self):
             Debug string of the symbol.
         """
         debug_str = ctypes.c_char_p()
-        check_call(_LIB.MXSymbolPrint( \
-                self.handle, ctypes.byref(debug_str)))
-        return debug_str.value
+        check_call(_LIB.MXSymbolPrint(
+            self.handle, ctypes.byref(debug_str)))
+        return py_str(debug_str.value)
 
     def bind(self, ctx, args, args_grad, reqs):
         """bind current symbol to get an executor.
@@ -275,7 +277,7 @@ def Variable(name):
     if not isinstance(name, string_types):
         raise TypeError('Expect a string for variable `name`')
     handle = SymbolHandle()
-    check_call(_LIB.MXSymbolCreateVariable(name, ctypes.byref(handle)))
+    check_call(_LIB.MXSymbolCreateVariable(c_str(name), ctypes.byref(handle)))
     return Symbol(handle)
 
 
@@ -312,18 +314,18 @@ def _make_atomic_symbol_function(handle):
     arg_types = ctypes.POINTER(ctypes.c_char_p)()
     arg_descs = ctypes.POINTER(ctypes.c_char_p)()
 
-    check_call(_LIB.MXSymbolGetAtomicSymbolInfo( \
-            handle, ctypes.byref(name), ctypes.byref(desc), \
-            ctypes.byref(num_args), \
-            ctypes.byref(arg_names), \
-            ctypes.byref(arg_types), \
-            ctypes.byref(arg_descs)))
-    func_name = name.value
+    check_call(_LIB.MXSymbolGetAtomicSymbolInfo(
+        handle, ctypes.byref(name), ctypes.byref(desc),
+        ctypes.byref(num_args),
+        ctypes.byref(arg_names),
+        ctypes.byref(arg_types),
+        ctypes.byref(arg_descs)))
+    func_name = py_str(name.value)
     param_str = []
     for i in range(num_args.value):
-        ret = '%s : %s' % (arg_names[i], arg_types[i])
+        ret = '%s : %s' % (py_str(arg_names[i]), py_str(arg_types[i]))
         if len(arg_descs[i]) != 0:
-            ret += '\n    ' + arg_descs[i]
+            ret += '\n    ' + py_str(arg_descs[i])
         param_str.append(ret)
 
     doc_str = ('%s\n\n' +
@@ -336,7 +338,7 @@ def _make_atomic_symbol_function(handle):
                '-------\n' +
                'symbol: Symbol\n'+
                '    The result symbol.')
-    doc_str = doc_str % (desc.value, '\n'.join(param_str))
+    doc_str = doc_str % (py_str(desc.value), '\n'.join(param_str))
 
     def creator(*args, **kwargs):
         """Activation Operator of Neural Net.
@@ -373,8 +375,9 @@ def creator(*args, **kwargs):
             ctypes.byref(sym_handle)))
 
         if len(args) != 0 and len(symbol_kwargs) != 0:
-            raise TypeError('%s can only accept input \
-                Symbols either as positional or keyword arguments, not both' % func_name)
+            raise TypeError(
+                '%s can only accept input'
+                'Symbols either as positional or keyword arguments, not both' % func_name)
 
         s = Symbol(sym_handle)
         s._compose(*args, name=name, **symbol_kwargs)
@@ -394,7 +397,7 @@ def _init_symbol_module():
                                                      ctypes.byref(plist)))
     module_obj = sys.modules[__name__]
     for i in range(size.value):
-        hdl = ctypes.c_void_p(plist[i])
+        hdl = SymbolHandle(plist[i])
         function = _make_atomic_symbol_function(hdl)
         setattr(module_obj, function.__name__, function)
 
diff --git a/python/test_infer_shape.py b/python/test_infer_shape.py
deleted file mode 100644
index 236ad1e7ae71..000000000000
--- a/python/test_infer_shape.py
+++ /dev/null
@@ -1,19 +0,0 @@
-# pylint: skip-file
-import mxnet as mx
-
-data = mx.symbol.Variable('data')
-
-fc1 = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=1000)
-fc2 = mx.symbol.FullyConnected(data=fc1, name='fc2', num_hidden=10)
-fc3 = mx.symbol.FullyConnected( name='fc2', num_hidden=10)
-
-print fc2.list_arguments()
-
-data_shape = (100, 100)
-arg_shapes, out_shapes = fc2.infer_shape(data=data_shape)
-print dict(zip(fc2.list_arguments(), arg_shapes))
-print dict(zip(fc2.list_returns(), out_shapes))
-
-weight_shape= (1, 100)
-data_shape = (100, 100)
-arg_shapes, out_shapes = fc2.infer_shape(data=data_shape, fc1_weight=weight_shape)
diff --git a/python/test_python.py b/python/test_python.py
deleted file mode 100644
index 905d16c283f8..000000000000
--- a/python/test_python.py
+++ /dev/null
@@ -1,30 +0,0 @@
-# pylint: skip-file
-import mxnet as mx
-
-a = mx.narray.create((3000, 4000))
-b = mx.narray.create((3000, 4000))
-a.numpy[:] = 10
-b.numpy[:] = 11
-print(a.numpy)
-
-c = b * a
-
-cc = mx.narray.NArray._mul(b, a)
-
-print(c.context)
-print(cc.numpy)
-d = c.copyto(mx.Context('cpu', 0))
-
-print(d.numpy)
-
-with mx.Context('gpu', 0) as ctx:
-    # gpu operations
-    print mx.current_context()
-    print ctx
-    a_gpu = a.copyto(ctx)
-    b_gpu = b.copyto(ctx)
-    c_gpu = b * a
-
-d_cpu = c_gpu.copyto(mx.current_context())
-print d_cpu.numpy
-
diff --git a/python/test_symbol.py b/python/test_symbol.py
deleted file mode 100644
index 451ee39775c9..000000000000
--- a/python/test_symbol.py
+++ /dev/null
@@ -1,27 +0,0 @@
-# pylint: skip-file
-import mxnet as mx
-
-data = mx.symbol.Variable('data')
-print data.debug_str()
-
-fc1 = mx.symbol.FullyConnected(data=data, name='fc1', no_bias=0)
-fc2 = mx.symbol.FullyConnected(data=fc1, name='fc2', no_bias=0)
-
-print fc2.debug_str()
-
-print fc2.list_arguments()
-
-fc3 = mx.symbol.FullyConnected(name='fc3')
-fc4 = mx.symbol.FullyConnected(data=fc3, name='fc4')
-
-print fc4.debug_str()
-
-print "-" * 10
-composed_fc4 = fc4(fc3_data=fc2, name='composed')
-print composed_fc4.debug_str()
-
-multi_out = mx.symbol.Group([composed_fc4, fc2])
-
-print multi_out.debug_str()
-print multi_out.list_arguments()
-print multi_out.list_returns()
diff --git a/scripts/travis_script.sh b/scripts/travis_script.sh
index ce9a22110fa2..1046051464be 100755
--- a/scripts/travis_script.sh
+++ b/scripts/travis_script.sh
@@ -3,26 +3,40 @@
 # main script of travis
 if [ ${TASK} == "lint" ]; then
     make lint || exit -1
+    exit 0
 fi
 
 if [ ${TASK} == "doc" ]; then
     make doc 2>log.txt
     (cat log.txt|grep warning) && exit -1
+    exit 0
 fi
 
+# prereqs for things that need make
+cp make/config.mk config.mk
+echo "USE_BLAS=blas" >> config.mk
+echo "USE_CUDNN=0" >> config.mk
+echo "CXX=g++-4.8" >> config.mk
+export CXX="g++-4.8"
+
+
 if [ ${TASK} == "build" ]; then
-    echo "USE_BLAS=blas" >> config.mk
     echo "USE_CUDA=1" >> config.mk
-    echo "USE_CUDNN=0" >> config.mk
-    echo "CXX=g++-4.8" >> config.mk
-    export CXX="g++-4.8"
     ./dmlc-core/scripts/setup_nvcc.sh $NVCC_PREFIX
     make all || exit -1
 fi
 
-if [ ${TASK} == "test" ]; then
-    cd test
+if [ ${TASK} == "python" ]; then
+    echo "USE_CUDA=0" >> config.mk
+    make all || exit -1
+    nosetests tests/python || exit -1
+fi
+
+if [ ${TASK} == "python3" ]; then
+    echo "USE_CUDA=0" >> config.mk
     make all || exit -1
-    ../scripts/travis_runtest.sh || exit -1
+    nosetests3 tests/python || exit -1
 fi
 
+
+# TODO(yutian): add unittest back
diff --git a/test/.gitignore b/tests/.gitignore
similarity index 100%
rename from test/.gitignore
rename to tests/.gitignore
diff --git a/tests/python/models.py b/tests/python/models.py
new file mode 100644
index 000000000000..d7fb74e4fd1e
--- /dev/null
+++ b/tests/python/models.py
@@ -0,0 +1,10 @@
+"""This file defines various models used in the test"""
+import mxnet as mx
+
+def mlp2():
+    data = mx.symbol.Variable('data')
+    out = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=1000)
+    out = mx.symbol.Activation(data=out, act_type='relu')
+    out = mx.symbol.FullyConnected(data=out, name='fc2', num_hidden=10)
+    return out
+
diff --git a/tests/python/test_inter_shape.py b/tests/python/test_inter_shape.py
new file mode 100644
index 000000000000..fa18ff175fbf
--- /dev/null
+++ b/tests/python/test_inter_shape.py
@@ -0,0 +1,30 @@
+# pylint: skip-file
+import mxnet as mx
+import models
+from nose.tools import *
+
+def test_mlp2_infer_shape():
+    # Build MLP
+    out = models.mlp2()
+    # infer shape
+    data_shape = (100, 100)
+    arg_shapes, out_shapes = out.infer_shape(data=data_shape)
+    arg_shape_dict = dict(zip(out.list_arguments(), arg_shapes))
+
+    assert len(out_shapes) == 1
+    assert out_shapes[0] == (100, 10)
+    true_shapes = {'fc2_bias': (10,),
+                   'fc2_weight' : (10, 1000),
+                   'fc1_bias' : (1000,),
+                   'fc1_weight' : (1000,100) }
+    for k, v in true_shapes.items():
+        assert arg_shape_dict[k] == v
+
+@raises(mx.MXNetError)
+def test_mlp2_infer_error():
+    # Test shape inconsistent case
+    out = models.mlp2()
+    weight_shape= (1, 100)
+    data_shape = (100, 100)
+    arg_shapes, out_shapes = out.infer_shape(data=data_shape, fc1_weight=weight_shape)
+
diff --git a/tests/python/test_narray.py b/tests/python/test_narray.py
new file mode 100644
index 000000000000..986176de81fe
--- /dev/null
+++ b/tests/python/test_narray.py
@@ -0,0 +1,46 @@
+import mxnet as mx
+import numpy as np
+
+def reldiff(a, b):
+    diff = np.sum(np.abs(a - b))
+    norm = np.sum(np.abs(a))
+    reldiff = diff  / norm
+    return reldiff
+
+def check_with_uniform(uf, arg_shapes, dim=None):
+    """check function consistency with uniform random numbers"""
+    if isinstance(arg_shapes, int):
+        assert dim
+        shape = tuple(np.random.randint(1, int(1000**(1.0/dim)), size=dim))
+        arg_shapes = [shape] * arg_shapes
+    narray_arg = []
+    numpy_arg = []
+    for s in arg_shapes:
+        narr = mx.narray.create(s)
+        npy = np.random.uniform(-10, 10, s)
+        narr.numpy[:] = npy
+        narray_arg.append(narr)
+        numpy_arg.append(npy)
+    out1 = uf(*narray_arg)
+    out2 = uf(*numpy_arg)
+    assert out1.shape == out2.shape
+    assert reldiff(out1.numpy, out2) < 1e-6
+
+
+def test_narray_elementwise():
+    np.random.seed(0)
+    nrepeat = 10
+    maxdim = 4
+    for repeat in range(nrepeat):
+        for dim in range(1, maxdim):
+            check_with_uniform(lambda x, y: x + y, 2, dim)
+            check_with_uniform(lambda x, y: x - y, 2, dim)
+            check_with_uniform(lambda x, y: x * y, 2, dim)
+            # check_with_uniform(lambda x, y: x / y, 2, dim)
+
+
+def test_narray_copy():
+    c = mx.narray.create((10,10))
+    c.numpy[:] = np.random.uniform(-10, 10, c.shape)
+    d = c.copyto(mx.Context('cpu', 0))
+    assert np.sum(np.abs(c.numpy != d.numpy)) == 0.0
diff --git a/tests/python/test_symbol.py b/tests/python/test_symbol.py
new file mode 100644
index 000000000000..b08f6a310570
--- /dev/null
+++ b/tests/python/test_symbol.py
@@ -0,0 +1,28 @@
+import mxnet as mx
+import models
+
+def test_symbol_basic():
+    mlist = []
+    mlist.append(models.mlp2())
+    for m in mlist:
+        m.list_arguments()
+        m.list_returns()
+
+
+def test_compose():
+    data = mx.symbol.Variable('data')
+    net1 = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=10)
+    net1 = mx.symbol.FullyConnected(data=net1, name='fc2', num_hidden=100)
+    net1.list_arguments() == ['data',
+                              'fc1_weight', 'fc1_bias',
+                              'fc2_weight', 'fc2_bias']
+
+    net2 = mx.symbol.FullyConnected(name='fc3', num_hidden=10)
+    net2 = mx.symbol.Activation(data=net2)
+    net2 = mx.symbol.FullyConnected(data=net2, name='fc4', num_hidden=20)
+    print(net2.debug_str())
+
+    composed = net2(fc3_data=net1, name='composed')
+    print(composed.debug_str())
+    multi_out = mx.symbol.Group([composed, net1])
+    assert len(multi_out.list_returns()) == 2
diff --git a/test/test_storage.cc b/tests/test_storage.cc
similarity index 100%
rename from test/test_storage.cc
rename to tests/test_storage.cc
diff --git a/test/test_threaded_engine.cc b/tests/test_threaded_engine.cc
similarity index 100%
rename from test/test_threaded_engine.cc
rename to tests/test_threaded_engine.cc