def test_base_buffer_exception(self):
with self.assertRaises(ValueError):
# size <= 0
ub_data.BaseBuffer(0, 1)
with self.assertRaises(AssertionError):
# batch <= 0
ub_data.BaseBuffer(1, 0)
buf = ub_data.BaseBuffer(1, 1)
self.assertTrue(buf.isnull)
with self.assertRaises(AssertionError):
# AssertionError: Buffer space not created
buf[0]
# auto create space
buf._set_data(1, indices=0)
buf[0]
def test_base_buffer_relative_index(self):
capacity = 10
batch = 1
n_samples = 15 # test circular
buf = ub_data.BaseBuffer(capacity, batch=batch)
for i in range(n_samples):
buf.add({'a': ([i], [i + 1])})
head = n_samples % capacity
self.assertEqual(head, buf.head)
self.assertEqual(head, buf.tail)
# test int, slice key
data = buf.rel[1]
self.assertArrayEqual([head + 1], data['a'][0])
self.assertArrayEqual([head + 2], data['a'][1])
data = buf.rel[-1]
self.assertArrayEqual([n_samples - 1], data['a'][0])
self.assertArrayEqual([n_samples], data['a'][1])
data = buf.rel[1:3]
exp = np.arange(2).reshape(-1, 1)
self.assertArrayEqual(exp + head + 1, data['a'][0])
self.assertArrayEqual(exp + head + 2, data['a'][1])
data = buf.rel[-3:-1]
exp = np.arange(2, 0, -1).reshape(-1, 1)
self.assertArrayEqual(n_samples - 1 - exp, data['a'][0])
self.assertArrayEqual(n_samples - exp, data['a'][1])
data = buf.rel[-1:1]
self.assertEqual((0, 1), data['a'][0].shape)
self.assertEqual((0, 1), data['a'][1].shape)
# test tuple key
data = buf.rel[1, 0]
self.assertArrayEqual(head + 1, data['a'][0])
self.assertArrayEqual(head + 2, data['a'][1])
data = buf.rel[-1, 0]
self.assertArrayEqual(n_samples - 1, data['a'][0])
self.assertArrayEqual(n_samples, data['a'][1])
data = buf.rel[1:3, 0]
exp = np.arange(2)
self.assertArrayEqual(exp + head + 1, data['a'][0])
self.assertArrayEqual(exp + head + 2, data['a'][1])
data = buf.rel[-3:-1, 0]
exp = np.arange(2, 0, -1)
self.assertArrayEqual(n_samples - 1 - exp, data['a'][0])
self.assertArrayEqual(n_samples - exp, data['a'][1])
data = buf.rel[-1:1, 0]
self.assertEqual((0, ), data['a'][0].shape)
self.assertEqual((0, ), data['a'][1].shape)
# test list key
data = buf.rel[[1, 3]]
self.assertArrayEqual([[head + 1], [head + 3]], data['a'][0])
self.assertArrayEqual([[head + 2], [head + 4]], data['a'][1])
# test np key
data = buf.rel[np.asarray([1, 3])]
self.assertArrayEqual([[head + 1], [head + 3]], data['a'][0])
self.assertArrayEqual([[head + 2], [head + 4]], data['a'][1])
# test index out of range
with self.assertRaises(IndexError):
buf.rel[capacity + 1]
def test_sampler_exception(self):
with self.assertRaises(ValueError):
# `buffer` must be an instance of BaseBuffer
ub_data.UniformSampler(None)
with self.assertRaises(ValueError):
# `buffer` must be an instance of BaseBuffer
ub_data.PermuteSampler(None)
with self.assertRaises(ValueError):
# `buffer` must be ReplayBuffer
ub_data.PrioritizedSampler(ub_data.BaseBuffer(10), 1.0)
with self.assertRaises(ValueError):
# `buffer` must be ReplayBuffer
ub_data.PrioritizedSampler(ub_data.DynamicBuffer(), 1.0)
def test_base_buffer_auto_calc_space(self):
capacity = 10
batch = 1
buf = ub_data.BaseBuffer(capacity, batch=batch)
self.assertEqual(0, len(buf))
self.assertEqual(0, buf.len_slots())
self.assertEqual(capacity, buf.capacity)
self.assertEqual(capacity, buf.slots)
self.assertEqual(batch, buf.batch)
self.assertEqual(0, buf.head)
self.assertEqual(0, buf.tail)
self.assertTrue(buf.isnull)
self.assertFalse(buf.isfull)
self.assertTrue(buf.ready_for_sample)
capacity = 10
n_samples = 15 # test circular
buf = ub_data.BaseBuffer(capacity, batch=None)
self.assertEqual(0, len(buf))
self.assertEqual(0, buf.len_slots())
self.assertEqual(None, buf.capacity)
self.assertEqual(None, buf.slots)
self.assertEqual(None, buf.batch)
self.assertEqual(0, buf.head)
self.assertEqual(0, buf.tail)
self.assertTrue(buf.isnull)
self.assertFalse(buf.isfull)
self.assertTrue(buf.ready_for_sample)
buf.add({'a': [0, 1]})
self.assertEqual(2, len(buf))
self.assertEqual(1, buf.len_slots())
self.assertEqual(capacity, buf.capacity)
self.assertEqual(math.ceil(capacity / 2), buf.slots)
self.assertEqual(2, buf.batch)
self.assertEqual(0, buf.head)
self.assertEqual(1, buf.tail)
self.assertFalse(buf.isnull)
self.assertFalse(buf.isfull)
self.assertTrue(buf.ready_for_sample)
def test_base_buffer_shape(self):
capacity = 10
batch = 3
n_samples = 15
buf = ub_data.BaseBuffer(capacity, batch=batch)
for i in range(n_samples):
buf.add({'a': np.arange(batch)})
self.assertArrayEqual((3, ), buf[1]['a'].shape)
self.assertArrayEqual((2, 3), buf[1:3]['a'].shape)
self.assertArrayEqual((2, ), buf[1:3, 0]['a'].shape)
self.assertArrayEqual((2, 2), buf[1:3, :2]['a'].shape)
self.assertArrayEqual((3, ), buf.rel[1]['a'].shape)
self.assertArrayEqual((2, 3), buf.rel[1:3]['a'].shape)
self.assertArrayEqual((2, ), buf.rel[1:3, 0]['a'].shape)
self.assertArrayEqual((2, 2), buf.rel[1:3, :2]['a'].shape)
def test_uniform_sampler_with_base_buffer(self):
capacity = 10
batch = 1
n_samples = 15
buf = ub_data.BaseBuffer(capacity, batch=batch)
samp = ub_data.UniformSampler(buf)
for i in range(n_samples):
buf.add({'a': ([i], [i + 1])})
if i < capacity - 1:
self.assertFalse(buf.isfull)
self.assertEqual(i + 1, len(buf))
else:
self.assertTrue(buf.isfull)
self.assertEqual(capacity, len(buf))
exp = np.arange(n_samples - capacity, n_samples)
exp_a0 = np.roll(exp, n_samples % capacity)
exp_a1 = exp_a0 + 1
exp_a0 = np.expand_dims(exp_a0, axis=-1)
exp_a1 = np.expand_dims(exp_a1, axis=-1)
self.assertArrayEqual(buf.data['a'][0], exp_a0)
self.assertArrayEqual(buf.data['a'][1], exp_a1)
# test sample (batch=None)
batch = samp()
self.assertArrayEqual((capacity, ), batch['a'][0].shape)
self.assertArrayEqual((capacity, ), batch['a'][1].shape)
self.assertArrayEqual(batch['a'][0], buf[samp.indices]['a'][0])
self.assertArrayEqual(batch['a'][1], buf[samp.indices]['a'][1])
# test sample (batch=3)
batch_size = 3
batch = samp(batch_size=batch_size)
self.assertArrayEqual((batch_size, ), batch['a'][0].shape)
self.assertArrayEqual((batch_size, ), batch['a'][1].shape)
self.assertArrayEqual(batch['a'][0], buf[samp.indices]['a'][0])
self.assertArrayEqual(batch['a'][1], buf[samp.indices]['a'][1])
# test sample (batch=3, seq=2)
batch_size = 3
seq_len = 2
batch = samp(batch_size=batch_size, seq_len=seq_len)
self.assertArrayEqual((batch_size, seq_len), batch['a'][0].shape)
self.assertArrayEqual((batch_size, seq_len), batch['a'][1].shape)
self.assertArrayEqual(batch['a'][0], buf[samp.indices]['a'][0])
self.assertArrayEqual(batch['a'][1], buf[samp.indices]['a'][1])
# test update
batch['a'] = (np.zeros_like(batch['a'][0]),
np.zeros_like(batch['a'][1]))
samp.update(batch)
self.assertArrayEqual(buf[samp.indices]['a'][0], batch['a'][0])
self.assertArrayEqual(buf[samp.indices]['a'][1], batch['a'][1])
def test_uniform_sampler_with_base_buffer_rel(self):
capacity = 10
batch = 1
n_samples = 15
buf = ub_data.BaseBuffer(capacity, batch=batch)
samp = ub_data.UniformSampler(buf)
for i in range(n_samples):
buf.add({'a': ([i], [i + 1])})
# test relative indexing
inds1 = np.arange(3)
inds2 = np.zeros(3, dtype=np.int64)
samp._cached_inds = (inds1, inds2)
self.assertArrayEqual(buf[samp.indices]['a'][0], samp.rel[0]['a'][0])
self.assertArrayEqual(buf[samp.indices]['a'][1], samp.rel[0]['a'][1])
self.assertArrayEqual(buf[(inds1 - 3, inds2)]['a'][0],
samp.rel[-3]['a'][0])
self.assertArrayEqual(buf[(inds1 - 3, inds2)]['a'][1],
samp.rel[-3]['a'][1])
self.assertArrayEqual(buf[(inds1 + 3, inds2)]['a'][0],
samp.rel[3]['a'][0])
self.assertArrayEqual(buf[(inds1 + 3, inds2)]['a'][1],
samp.rel[3]['a'][1])
add = np.array([[1, 2]], dtype=np.int64).T
self.assertArrayEqual(buf[(inds1 + add, inds2)]['a'][0],
samp.rel[1:3]['a'][0])
self.assertArrayEqual(buf[(inds1 + add, inds2)]['a'][1],
samp.rel[1:3]['a'][1])
add = np.array([[-3, -2]], dtype=np.int64).T
self.assertArrayEqual(buf[(inds1 + add, inds2)]['a'][0],
samp.rel[-3:-1]['a'][0])
self.assertArrayEqual(buf[(inds1 + add, inds2)]['a'][1],
samp.rel[-3:-1]['a'][1])
# test shape
self.assertArrayEqual((0, 3), samp.rel[-1:1]['a'][0].shape)
# test setitem
add = np.array([[1, 2]], dtype=np.int64).T
batch = samp.rel[1:3]
batch['a'] = (np.zeros_like(batch['a'][0]),
np.zeros_like(batch['a'][1]))
samp.rel[1:3] = batch
self.assertTrue(np.all(samp.rel[1:3]['a'][0] == 0))
self.assertTrue(np.all(samp.rel[1:3]['a'][1] == 0))
def test_base_buffer_multidim(self):
capacity = 20
batch = 2
dim = 2
n_samples = 15 # test circular
buf = ub_data.BaseBuffer(capacity, batch=batch)
data = np.arange(n_samples * batch * dim).reshape(
(n_samples, batch, dim))
for i in range(n_samples):
buf.add({'a': data[i]})
if (i + 1) * batch < capacity:
self.assertFalse(buf.isfull)
self.assertEqual((i + 1) * batch, len(buf))
self.assertEqual(i + 1, buf.len_slots())
self.assertEqual(0, buf.head)
else:
self.assertTrue(buf.isfull)
self.assertEqual(capacity, len(buf))
self.assertEqual(capacity // batch, buf.len_slots())
self.assertEqual((i + 1) % (capacity // batch), buf.tail)
exp = np.arange(n_samples * batch * dim - capacity * dim,
n_samples * batch * dim)
exp = exp.reshape(-1, 2, 2)
exp = np.roll(exp, n_samples % (capacity // batch), axis=0)
self.assertArrayEqual(exp, buf.data['a'])
# test ravel/unravel index
def test_ravel(indices):
self.assertArrayEqual(
np.ravel_multi_index(indices, (buf.slots, buf.batch)),
buf.ravel_index(indices))
test_ravel(([1, 2, 3], 0))
test_ravel(([[1], [2], [3]], [0, 1]))
def test_unravel(indices):
self.assertArrayEqual(
np.unravel_index(indices, (buf.slots, buf.batch)),
buf.unravel_index(indices))
test_unravel([4, 5, 6])
test_unravel(7)
def test_permute_sampler_with_base_buffer(self):
capacity = 10
batch = 1
n_samples = 15
buf = ub_data.BaseBuffer(capacity, batch=batch)
samp = ub_data.PermuteSampler(buf)
for i in range(n_samples):
buf.add({'a': ([i], [i + 1])})
# test sample (batch=None)
batch_size = len(buf)
batches = []
indices = []
for batch in samp():
self.assertArrayEqual((batch_size, ), batch['a'][0].shape)
self.assertArrayEqual((batch_size, ), batch['a'][1].shape)
self.assertArrayEqual(buf[samp.indices]['a'][0], batch['a'][0])
self.assertArrayEqual(buf[samp.indices]['a'][1], batch['a'][1])
batches.append(batch)
indices.append(
np.ravel_multi_index(samp.indices,
(buf.len_slots(), buf.batch)))
self.assertEqual(1, len(batches))
unique, counts = np.unique(indices, return_counts=True)
# check if contains all elements
self.assertTrue(len(buf), len(unique))
# check if all elements are sampled at least once
self.assertTrue(np.all(counts == 1))
# test sample (batch=3)
batch_size = 3
batches = []
indices = []
for batch in samp(batch_size=batch_size):
self.assertArrayEqual((batch_size, ), batch['a'][0].shape)
self.assertArrayEqual((batch_size, ), batch['a'][1].shape)
self.assertArrayEqual(buf[samp.indices]['a'][0], batch['a'][0])
self.assertArrayEqual(buf[samp.indices]['a'][1], batch['a'][1])
batches.append(batch)
indices.append(
np.ravel_multi_index(samp.indices,
(buf.len_slots(), buf.batch)))
self.assertEqual(4, len(batches)) # total samples == capacity
unique, counts = np.unique(indices, return_counts=True)
# check if contains all elements
self.assertTrue(len(buf), len(unique))
# check if all elements are sampled at least once but less than 2
self.assertTrue(np.all(counts >= 1))
self.assertTrue(np.all(counts <= 2))
# test sample (batch=3, seq_len=2)
batch_size = 3
seq_len = 2
batches = []
indices = []
for batch in samp(batch_size=batch_size, seq_len=seq_len):
self.assertArrayEqual((batch_size, seq_len), batch['a'][0].shape)
self.assertArrayEqual((batch_size, seq_len), batch['a'][1].shape)
self.assertArrayEqual(buf[samp.indices]['a'][0], batch['a'][0])
self.assertArrayEqual(buf[samp.indices]['a'][1], batch['a'][1])
batches.append(batch)
indices.append(
np.ravel_multi_index(samp.indices,
(buf.len_slots(), buf.batch)))
self.assertEqual(3, len(batches)) # total samples == capacity
unique, counts = np.unique(indices, return_counts=True)
# check if contains all elements
self.assertTrue(len(buf), len(unique))
# check if all elements are sampled at least once but less than 3
self.assertTrue(np.all(counts >= 1))
self.assertTrue(np.all(counts <= 4))
def test_base_buffer(self):
capacity = 10
batch = 1
n_samples = 15 # test circular
buf = ub_data.BaseBuffer(capacity, batch=batch)
self.assertEqual(capacity, buf.capacity)
self.assertEqual(capacity, buf.slots)
self.assertEqual(batch, buf.batch)
self.assertEqual(0, buf.head)
self.assertEqual(0, buf.tail)
self.assertTrue(buf.isnull)
self.assertFalse(buf.isfull)
self.assertTrue(buf.ready_for_sample)
for i in range(n_samples):
buf.add({'a': ([i], [i + 1])})
if i < capacity - 1:
self.assertFalse(buf.isfull)
self.assertEqual(i + 1, len(buf))
self.assertEqual(i + 1, buf.len_slots())
self.assertEqual(0, buf.head)
else:
self.assertTrue(buf.isfull)
self.assertEqual(capacity, len(buf))
self.assertEqual(capacity, buf.len_slots())
self.assertEqual((i + 1) % capacity, buf.tail)
exp = np.arange(n_samples - capacity, n_samples)
exp_a0 = np.roll(exp, n_samples % capacity)
exp_a1 = exp_a0 + 1
exp_a0 = np.expand_dims(exp_a0, axis=-1)
exp_a1 = np.expand_dims(exp_a1, axis=-1)
self.assertArrayEqual(exp_a0, buf.data['a'][0])
self.assertArrayEqual(exp_a1, buf.data['a'][1])
# test getitem
data = buf[np.arange(n_samples % capacity)]
exp_a0 = np.arange(n_samples - n_samples % capacity, n_samples)
exp_a1 = exp_a0 + 1
exp_a0 = np.expand_dims(exp_a0, axis=-1)
exp_a1 = np.expand_dims(exp_a1, axis=-1)
self.assertArrayEqual(exp_a0, data['a'][0])
self.assertArrayEqual(exp_a1, data['a'][1])
# test setitem
n = n_samples - capacity
new_data = np.arange(n - n_samples % capacity, n)
new_data = np.expand_dims(new_data, axis=-1)
new_data = {'a': (new_data, new_data + 1)}
buf[np.arange(n_samples % capacity)] = new_data
n = n_samples - capacity - n_samples % capacity
exp_a0 = np.arange(n, n + capacity)
exp_a1 = exp_a0 + 1
exp_a0 = np.expand_dims(exp_a0, axis=-1)
exp_a1 = np.expand_dims(exp_a1, axis=-1)
self.assertArrayEqual(exp_a0, buf.data['a'][0])
self.assertArrayEqual(exp_a1, buf.data['a'][1])
# test update (should have the same results as setitem)
buf.update(new_data, indices=np.arange(n_samples % capacity))
self.assertArrayEqual(exp_a0, buf.data['a'][0])
self.assertArrayEqual(exp_a1, buf.data['a'][1])
# test ravel/unravel index
def test_ravel(indices):
self.assertArrayEqual(
np.ravel_multi_index(indices, (buf.slots, buf.batch)),
buf.ravel_index(indices))
test_ravel(([1, 2, 3], 0))
test_ravel(([1, 2, 3], [0]))
def test_unravel(indices):
self.assertArrayEqual(
np.unravel_index(indices, (buf.slots, buf.batch)),
buf.unravel_index(indices))
test_unravel([4, 5, 6])
test_unravel(7)
