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Add unit test #91

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Jun 14, 2017
Merged

Add unit test #91

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95bf6d6
add unittest
jiajiechen Jun 13, 2017
f08b8ce
minor fix
jiajiechen Jun 13, 2017
722bc62
remove commented lines
jiajiechen Jun 13, 2017
cddc13d
change test func name
jiajiechen Jun 13, 2017
5023e1b
add test rsp
jiajiechen Jun 14, 2017
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24 changes: 0 additions & 24 deletions python/mxnet/sparse_ndarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,45 +84,21 @@ class SparseNDArray(NDArray):
fixed-size items, stored in sparse format. See CSRNDArray and RowSparseNDArray
for more details.
"""
def __add__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __iadd__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __radd__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __isub__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __rsub__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __imul__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __rmul__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __rdiv__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __idiv__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __rtruediv__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __itruediv__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __pow__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __rpow__(self, other):
raise Exception('Not implemented for SparseND yet!')

def __setitem__(self, key, value):
"""x.__setitem__(i, y) <=> x[i]=y

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189 changes: 112 additions & 77 deletions tests/python/unittest/test_sparse_ndarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -165,81 +165,81 @@ def check_sparse_nd_csr_slice(shape):


def test_sparse_nd_equal():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x == y
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 == x
assert (z.asnumpy() == np.ones(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x == y
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 == x
assert (z.asnumpy() == np.ones(shape)).all()


def test_sparse_nd_not_equal():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x != y
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 != x
assert (z.asnumpy() == np.zeros(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x != y
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 != x
assert (z.asnumpy() == np.zeros(shape)).all()


def test_sparse_nd_greater():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x > y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y > 0
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 > y
assert (z.asnumpy() == np.zeros(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x > y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y > 0
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 > y
assert (z.asnumpy() == np.zeros(shape)).all()


def test_sparse_nd_greater_equal():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x >= y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y >= 0
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 >= y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y >= 1
assert (z.asnumpy() == np.ones(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = x >= y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y >= 0
assert (z.asnumpy() == np.ones(shape)).all()
z = 0 >= y
assert (z.asnumpy() == np.zeros(shape)).all()
z = y >= 1
assert (z.asnumpy() == np.ones(shape)).all()


def test_sparse_nd_lesser():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = y < x
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 < y
assert (z.asnumpy() == np.ones(shape)).all()
z = y < 0
assert (z.asnumpy() == np.zeros(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = y < x
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 < y
assert (z.asnumpy() == np.ones(shape)).all()
z = y < 0
assert (z.asnumpy() == np.zeros(shape)).all()


def test_sparse_nd_lesser_equal():
stype = 'csr'
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = y <= x
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 <= y
assert (z.asnumpy() == np.ones(shape)).all()
z = y <= 0
assert (z.asnumpy() == np.zeros(shape)).all()
z = 1 <= y
assert (z.asnumpy() == np.ones(shape)).all()
for stype in ['row_sparse', 'csr']:
shape = rand_shape_2d()
x = mx.sparse_nd.zeros(stype, shape)
y = sparse_nd_ones(shape, stype)
z = y <= x
assert (z.asnumpy() == np.zeros(shape)).all()
z = 0 <= y
assert (z.asnumpy() == np.ones(shape)).all()
z = y <= 0
assert (z.asnumpy() == np.zeros(shape)).all()
z = 1 <= y
assert (z.asnumpy() == np.ones(shape)).all()


def test_sparse_nd_binary():
Expand All @@ -257,35 +257,70 @@ def check_binary(fn):
lshape[ndim-i-1] = 1
elif sep < 0.66:
rshape[bdim-i-1] = 1
lhs = np.random.normal(0, 1, size=lshape)
rhs = np.random.normal(0, 1, size=rshape)
lhs_nd = mx.nd.array(lhs).to_csr()
rhs_nd = mx.nd.array(rhs).to_csr()
assert_allclose(fn(lhs, rhs),
fn(lhs_nd, rhs_nd).asnumpy(),
rtol=1e-4, atol=1e-4)

#check_binary(lambda x, y: x + y)
lhs = np.random.uniform(0, 1, size=lshape)
rhs = np.random.uniform(0, 1, size=rshape)
lhs_nd_csr = mx.nd.array(lhs).to_csr()
rhs_nd_csr = mx.nd.array(rhs).to_csr()
lhs_nd_rsp = mx.nd.array(lhs).to_rsp()
rhs_nd_rsp = mx.nd.array(rhs).to_rsp()
for lhs_nd, rhs_nd in [(lhs_nd_csr, rhs_nd_csr), (lhs_nd_rsp, rhs_nd_rsp)]:
assert_allclose(fn(lhs, rhs),
fn(lhs_nd, rhs_nd).asnumpy(),
rtol=1e-4, atol=1e-4)

check_binary(lambda x, y: x + y)
check_binary(lambda x, y: x - y)
check_binary(lambda x, y: x * y)
check_binary(lambda x, y: x / y)
check_binary(lambda x, y: x ** y)
check_binary(lambda x, y: x > y)
check_binary(lambda x, y: x < y)
check_binary(lambda x, y: x >= y)
check_binary(lambda x, y: x <= y)
check_binary(lambda x, y: x == y)


def test_sparse_nd_binary_rop():
N = 100
def check(fn):
for _ in range(N):
ndim = 2
shape = np.random.randint(1, 6, size=(ndim,))
npy_nd = np.random.normal(0, 1, size=shape)
csr_nd = mx.nd.array(npy_nd).to_csr()
rsp_nd = mx.nd.array(npy_nd).to_rsp()
for sparse_nd in [csr_nd, rsp_nd]:
assert_allclose(
fn(npy_nd),
fn(sparse_nd).asnumpy(),
rtol=1e-4,
atol=1e-4
)
check(lambda x: 1 + x)
check(lambda x: 1 - x)
check(lambda x: 1 * x)
check(lambda x: 1 / x)
check(lambda x: 2 ** x)
check(lambda x: 1 > x)
check(lambda x: 0.5 > x)
check(lambda x: 0.5 < x)
check(lambda x: 0.5 >= x)
check(lambda x: 0.5 <= x)
check(lambda x: 0.5 == x)


def test_sparse_nd_negate():
npy = np.random.uniform(-10, 10, rand_shape_2d())
arr = mx.nd.array(npy).to_csr()
assert_almost_equal(npy, arr.asnumpy())
assert_almost_equal(-npy, (-arr).asnumpy())

# a final check to make sure the negation (-) is not implemented
# as inplace operation, so the contents of arr does not change after
# we compute (-arr)
assert_almost_equal(npy, arr.asnumpy())
arr_csr = mx.nd.array(npy).to_csr()
arr_rsp = mx.nd.array(npy).to_rsp()
for arr in [arr_csr, arr_rsp]:
assert_almost_equal(npy, arr.asnumpy())
assert_almost_equal(-npy, (-arr).asnumpy())

# a final check to make sure the negation (-) is not implemented
# as inplace operation, so the contents of arr does not change after
# we compute (-arr)
assert_almost_equal(npy, arr.asnumpy())


def test_sparse_nd_output_fallback():
Expand Down