def test_minibatch_index_generator():
n_samples = 48
n_epochs = 1.5
minibatch_size = 5
data = np.arange(n_samples)
expected_total_samples = int(len(data)*n_epochs)
for slice_when_possible in (True, False):
i = 0
for ix in minibatch_index_generator(n_samples = n_samples, n_epochs=n_epochs, final_treatment='truncate',
slice_when_possible = slice_when_possible, minibatch_size=minibatch_size):
assert np.array_equal(data[ix], np.arange(i, min(expected_total_samples, i+minibatch_size)) % n_samples)
i += len(data[ix])
assert i == expected_total_samples == 72
i = 0
for ix in minibatch_index_generator(n_samples = n_samples, n_epochs=n_epochs, final_treatment='stop',
slice_when_possible = slice_when_possible, minibatch_size=minibatch_size):
assert np.array_equal(data[ix], np.arange(i, min(expected_total_samples, i+minibatch_size)) % n_samples)
i += len(data[ix])
assert i == int(expected_total_samples/minibatch_size) * minibatch_size == 70
def test_minibatch_index_generator():
n_samples = 48
n_epochs = 1.5
minibatch_size = 5
data = np.arange(n_samples)
expected_total_samples = int(len(data)*n_epochs)
for slice_when_possible in (True, False):
i = 0
for ix in minibatch_index_generator(n_samples = n_samples, n_epochs=n_epochs, final_treatment='truncate',
slice_when_possible = slice_when_possible, minibatch_size=minibatch_size):
assert np.array_equal(data[ix], np.arange(i, min(expected_total_samples, i+minibatch_size)) % n_samples)
i += len(data[ix])
assert i == expected_total_samples == 72
i = 0
for ix in minibatch_index_generator(n_samples = n_samples, n_epochs=n_epochs, final_treatment='stop',
slice_when_possible = slice_when_possible, minibatch_size=minibatch_size):
assert np.array_equal(data[ix], np.arange(i, min(expected_total_samples, i+minibatch_size)) % n_samples)
i += len(data[ix])
assert i == int(expected_total_samples/minibatch_size) * minibatch_size == 70
def test_minibatch_index_even():
n_samples = 5
n_epochs=2
ixs = list(minibatch_index_generator(n_samples=n_samples, n_epochs=n_epochs, minibatch_size=1, slice_when_possible=False, final_treatment='truncate'))
assert ixs==[[i%n_samples] for i in range(n_samples*n_epochs)]
def test_minibatch_index_even():
n_samples = 5
n_epochs=2
ixs = list(minibatch_index_generator(n_samples=n_samples, n_epochs=n_epochs, minibatch_size=1, slice_when_possible=False, final_treatment='truncate'))
assert ixs==[[i%n_samples] for i in range(n_samples*n_epochs)]