def testMockExecuteSize(self):
import mars.tensor as mt
from mars.core.graph import DAG
from mars.tensor.fetch import TensorFetch
from mars.tensor.arithmetic import TensorTreeAdd
graph_add = DAG()
input_chunks = []
for _ in range(2):
fetch_op = TensorFetch(dtype=np.dtype('int64'))
inp_chunk = fetch_op.new_chunk(None, shape=(100, 100)).data
input_chunks.append(inp_chunk)
add_op = TensorTreeAdd(args=input_chunks, dtype=np.dtype('int64'))
add_chunk = add_op.new_chunk(input_chunks,
shape=(100, 100),
dtype=np.dtype('int64')).data
graph_add.add_node(add_chunk)
for inp_chunk in input_chunks:
graph_add.add_node(inp_chunk)
graph_add.add_edge(inp_chunk, add_chunk)
executor = Executor()
res = executor.execute_graph(graph_add, [add_chunk.key],
compose=False,
mock=True)[0]
self.assertEqual(res, (80000, 80000))
self.assertEqual(executor.mock_max_memory, 80000)
for _ in range(3):
new_add_op = TensorTreeAdd(args=[add_chunk],
dtype=np.dtype('int64'))
new_add_chunk = new_add_op.new_chunk([add_chunk],
shape=(100, 100),
dtype=np.dtype('int64')).data
graph_add.add_node(new_add_chunk)
graph_add.add_edge(add_chunk, new_add_chunk)
add_chunk = new_add_chunk
executor = Executor()
res = executor.execute_graph(graph_add, [add_chunk.key],
compose=False,
mock=True)[0]
self.assertEqual(res, (80000, 80000))
self.assertEqual(executor.mock_max_memory, 160000)
a = mt.random.rand(10, 10, chunk_size=10)
b = a[:, mt.newaxis, :] - a
r = mt.triu(mt.sqrt(b**2).sum(axis=2))
executor = Executor()
res = executor.execute_tensor(r, concat=False, mock=True)
# larger than maximal memory size in calc procedure
self.assertGreaterEqual(res[0][0], 800)
self.assertGreaterEqual(executor.mock_max_memory, 8000)
def testMockExecuteSize(self):
a = mt.random.rand(10, 10, chunk_size=10)
b = a[:, mt.newaxis, :] - a
r = mt.triu(mt.sqrt(b**2).sum(axis=2))
executor = Executor()
res = executor.execute_tensor(r, concat=False, mock=True)
# larger than maximal memory size in calc procedure
self.assertGreaterEqual(res[0][0], 800)
self.assertGreaterEqual(res[0][1], 8000)
def test_triu_tril():
a_data = np.arange(12).reshape(4, 3)
a = tensor(a_data, chunk_size=2)
t = triu(a)
assert t.op.gpu is False
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTriu)
assert isinstance(t.chunks[1].op, TensorTriu)
assert isinstance(t.chunks[2].op, TensorZeros)
assert isinstance(t.chunks[3].op, TensorTriu)
t = triu(a, k=1)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTriu)
assert isinstance(t.chunks[1].op, TensorTriu)
assert isinstance(t.chunks[2].op, TensorZeros)
assert isinstance(t.chunks[3].op, TensorZeros)
t = triu(a, k=2)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorZeros)
assert isinstance(t.chunks[1].op, TensorTriu)
assert isinstance(t.chunks[2].op, TensorZeros)
assert isinstance(t.chunks[3].op, TensorZeros)
t = triu(a, k=-1)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTriu)
assert isinstance(t.chunks[1].op, TensorTriu)
assert isinstance(t.chunks[2].op, TensorTriu)
assert isinstance(t.chunks[3].op, TensorTriu)
t = tril(a)
assert t.op.gpu is False
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTril)
assert isinstance(t.chunks[1].op, TensorZeros)
assert isinstance(t.chunks[2].op, TensorTril)
assert isinstance(t.chunks[3].op, TensorTril)
t = tril(a, k=1)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTril)
assert isinstance(t.chunks[1].op, TensorTril)
assert isinstance(t.chunks[2].op, TensorTril)
assert isinstance(t.chunks[3].op, TensorTril)
t = tril(a, k=-1)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorTril)
assert isinstance(t.chunks[1].op, TensorZeros)
assert isinstance(t.chunks[2].op, TensorTril)
assert isinstance(t.chunks[3].op, TensorTril)
t = tril(a, k=-2)
t = tile(t)
assert len(t.chunks) == 4
assert isinstance(t.chunks[0].op, TensorZeros)
assert isinstance(t.chunks[1].op, TensorZeros)
assert isinstance(t.chunks[2].op, TensorTril)
assert isinstance(t.chunks[3].op, TensorZeros)
def testTriuTril(self):
a_data = np.arange(12).reshape(4, 3)
a = tensor(a_data, chunk_size=2)
t = triu(a)
self.assertFalse(t.op.gpu)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTriu)
self.assertIsInstance(t.chunks[1].op, TensorTriu)
self.assertIsInstance(t.chunks[2].op, TensorZeros)
self.assertIsInstance(t.chunks[3].op, TensorTriu)
t = triu(a, k=1)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTriu)
self.assertIsInstance(t.chunks[1].op, TensorTriu)
self.assertIsInstance(t.chunks[2].op, TensorZeros)
self.assertIsInstance(t.chunks[3].op, TensorZeros)
t = triu(a, k=2)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorZeros)
self.assertIsInstance(t.chunks[1].op, TensorTriu)
self.assertIsInstance(t.chunks[2].op, TensorZeros)
self.assertIsInstance(t.chunks[3].op, TensorZeros)
t = triu(a, k=-1)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTriu)
self.assertIsInstance(t.chunks[1].op, TensorTriu)
self.assertIsInstance(t.chunks[2].op, TensorTriu)
self.assertIsInstance(t.chunks[3].op, TensorTriu)
t = tril(a)
self.assertFalse(t.op.gpu)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTril)
self.assertIsInstance(t.chunks[1].op, TensorZeros)
self.assertIsInstance(t.chunks[2].op, TensorTril)
self.assertIsInstance(t.chunks[3].op, TensorTril)
t = tril(a, k=1)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTril)
self.assertIsInstance(t.chunks[1].op, TensorTril)
self.assertIsInstance(t.chunks[2].op, TensorTril)
self.assertIsInstance(t.chunks[3].op, TensorTril)
t = tril(a, k=-1)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorTril)
self.assertIsInstance(t.chunks[1].op, TensorZeros)
self.assertIsInstance(t.chunks[2].op, TensorTril)
self.assertIsInstance(t.chunks[3].op, TensorTril)
t = tril(a, k=-2)
t = t.tiles()
self.assertEqual(len(t.chunks), 4)
self.assertIsInstance(t.chunks[0].op, TensorZeros)
self.assertIsInstance(t.chunks[1].op, TensorZeros)
self.assertIsInstance(t.chunks[2].op, TensorTril)
self.assertIsInstance(t.chunks[3].op, TensorZeros)
def testSolveTriangular(self):
from mars.tensor import tril, triu
np.random.seed(1)
data1 = np.random.randint(1, 10, (20, 20))
data2 = np.random.randint(1, 10, (20, ))
A = tensor(data1, chunk_size=20)
b = tensor(data2, chunk_size=20)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
data1 = np.random.randint(1, 10, (10, 10))
data2 = np.random.randint(1, 10, (10, 5))
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
A = tensor(data1, chunk_size=3)
b = tensor(data2, chunk_size=3)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
# test sparse
data1 = sps.csr_matrix(np.triu(np.random.randint(1, 10, (10, 10))))
data2 = np.random.random((10, ))
A = tensor(data1, chunk_size=5)
b = tensor(data2, chunk_size=5)
x = solve_triangular(A, b)
result_x = self.executor.execute_tensor(x, concat=True)[0]
result_b = data1.dot(result_x)
self.assertIsInstance(result_x, SparseNDArray)
np.testing.assert_allclose(result_b, data2)
data1 = sps.csr_matrix(np.triu(np.random.randint(1, 10, (10, 10))))
data2 = np.random.random((10, 2))
A = tensor(data1, chunk_size=5)
b = tensor(data2, chunk_size=5)
x = solve_triangular(A, b)
result_x = self.executor.execute_tensor(x, concat=True)[0]
result_b = data1.dot(result_x)
self.assertIsInstance(result_x, SparseNDArray)
np.testing.assert_allclose(result_b, data2)
def test_solve_triangular(setup):
from mars.tensor import tril, triu
rs = np.random.RandomState(0)
data1 = rs.randint(1, 10, (20, 20))
data2 = rs.randint(1, 10, (20, ))
A = tensor(data1, chunk_size=20)
b = tensor(data2, chunk_size=20)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
data1 = rs.randint(1, 10, (10, 10))
data2 = rs.randint(1, 10, (10, 5))
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = t.execute().fetch()
np.testing.assert_allclose(res, data2)
# test sparse
data1 = sps.csr_matrix(np.triu(rs.randint(1, 10, (10, 10))))
data2 = rs.random((10, ))
A = tensor(data1, chunk_size=5)
b = tensor(data2, chunk_size=5)
x = solve_triangular(A, b)
result_x = x.execute().fetch()
result_b = data1.dot(result_x)
assert isinstance(result_x, SparseNDArray)
np.testing.assert_allclose(result_b, data2)
data1 = sps.csr_matrix(np.triu(rs.randint(1, 10, (10, 10))))
data2 = rs.random((10, 2))
A = tensor(data1, chunk_size=5)
b = tensor(data2, chunk_size=5)
x = solve_triangular(A, b)
result_x = x.execute().fetch()
result_b = data1.dot(result_x)
assert isinstance(result_x, SparseNDArray)
np.testing.assert_allclose(result_b, data2)
def testSolveTriangular(self):
from mars.tensor import tril, triu
np.random.seed(1)
data1 = np.random.randint(1, 10, (20, 20))
data2 = np.random.randint(1, 10, (20, ))
A = tensor(data1, chunk_size=20)
b = tensor(data2, chunk_size=20)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
data1 = np.random.randint(1, 10, (10, 10))
data2 = np.random.randint(1, 10, (10, 5))
A = tensor(data1, chunk_size=10)
b = tensor(data2, chunk_size=10)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
A = tensor(data1, chunk_size=3)
b = tensor(data2, chunk_size=3)
x = solve_triangular(A, b)
t = triu(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
x = solve_triangular(A, b, lower=True)
t = tril(A).dot(x)
res = self.executor.execute_tensor(t, concat=True)[0]
np.testing.assert_allclose(res, data2)
