def testRandom(self):
arr = rand(2, 3)
self.assertIsNotNone(arr.dtype)
arr = beta(1, 2, chunk_size=2).tiles()
self.assertEqual(arr.shape, ())
self.assertEqual(calc_shape(arr), arr.shape)
self.assertEqual(len(arr.chunks), 1)
self.assertEqual(arr.chunks[0].shape, ())
self.assertEqual(calc_shape(arr.chunks[0]), arr.chunks[0].shape)
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
arr = beta([1, 2], [3, 4], chunk_size=2).tiles()
self.assertEqual(arr.shape, (2, ))
self.assertEqual(calc_shape(arr), arr.shape)
self.assertEqual(len(arr.chunks), 1)
self.assertEqual(arr.chunks[0].shape, (2, ))
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
self.assertEqual(calc_shape(arr.chunks[0]), arr.chunks[0].shape)
arr = beta([[2, 3]],
from_ndarray([[4, 6], [5, 2]], chunk_size=2),
chunk_size=1,
size=(3, 2, 2)).tiles()
self.assertEqual(arr.shape, (3, 2, 2))
self.assertEqual(calc_shape(arr), arr.shape)
self.assertEqual(len(arr.chunks), 12)
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
self.assertEqual(calc_shape(arr.chunks[0]), arr.chunks[0].shape)
def testRandomSerialize(self):
arr = RandomState(0).beta([[2, 3]],
from_ndarray([[4, 6], [5, 2]], chunk_size=2),
chunk_size=1,
size=(3, 2, 2)).tiles()
chunk = arr.chunks[0]
self.assertEqual(chunk.op.dtype, np.dtype('f8'))
serials = self._pb_serial(chunk)
chunk2 = self._pb_deserial(serials)[chunk.data]
self.assertEqual(chunk.index, chunk2.index)
state, state2 = chunk.op.state, chunk2.op.state
self.assertTrue(np.array_equal(state.keys, state2.keys))
def testBetaExecute(self):
arr = tensor.random.beta(1, 2, chunk_size=2).tiles()
arr.chunks[0].op._state = State(np.random.RandomState(0))
self.assertEqual(
self.executor.execute_tensor(arr)[0],
np.random.RandomState(0).beta(1, 2))
arr = tensor.random.beta([1, 2], [3, 4], chunk_size=2).tiles()
arr.chunks[0].op._state = State(np.random.RandomState(0))
self.assertTrue(
np.array_equal(
self.executor.execute_tensor(arr)[0],
np.random.RandomState(0).beta([1, 2], [3, 4])))
arr = tensor.random.beta([[2, 3]],
from_ndarray([[4, 6], [5, 2]], chunk_size=2),
chunk_size=1,
size=(3, 2, 2)).tiles()
for c in arr.chunks:
c.op._state = State(np.random.RandomState(0))
res = self.executor.execute_tensor(arr, concat=True)[0]
self.assertEqual(res[0, 0, 0], np.random.RandomState(0).beta(2, 4))
self.assertEqual(res[0, 0, 1], np.random.RandomState(0).beta(3, 6))
self.assertEqual(res[0, 1, 0], np.random.RandomState(0).beta(2, 5))
self.assertEqual(res[0, 1, 1], np.random.RandomState(0).beta(3, 2))
arr = tensor.random.RandomState(0).beta([[3, 4]], [[1], [2]],
chunk_size=1)
tensor.random.seed(0)
arr2 = tensor.random.beta([[3, 4]], [[1], [2]], chunk_size=1)
self.assertTrue(
np.array_equal(
self.executor.execute_tensor(arr, concat=True)[0],
self.executor.execute_tensor(arr2, concat=True)[0]))
