def test_seq_batchmatmul6():
""" No sequence axis, left operand is matrix, right operand is tensor """
dynamic_batch = 2
matmul_batch = 3
batch_shape = (dynamic_batch, matmul_batch)
inner_dim = 2
left_operand_shape = (5, inner_dim)
right_operand_shape = (inner_dim, 6, 3)
final_shape = (5, 6, 3)
n = np.random.random(batch_shape + left_operand_shape).astype(np.float32)
m = np.random.random(batch_shape + right_operand_shape).astype(np.float32)
a = C.input_variable((matmul_batch,) + left_operand_shape)
b = C.input_variable((matmul_batch,) + right_operand_shape)
c = batchmatmul(a, b, output_rank=2)
assert c.shape == (matmul_batch, ) + final_shape
desired_packed = n @ m.reshape(batch_shape + (inner_dim, -1))
desired = desired_packed.reshape(batch_shape + final_shape)
result = c.eval({a: n, b: m})
result = np.array(result)
np.testing.assert_almost_equal(result, desired, decimal=7)
def test_seq_batchmatmul7():
"""
sequence axis present with samples of uneven sequence length
left operand is matrix, right operand is matrix
"""
# uneven sequence length between batches
n = [np.random.random((4, 3, 5, 2)).astype(np.float32),
np.random.random((2, 3, 5, 2)).astype(np.float32),
np.random.random((7, 3, 5, 2)).astype(np.float32)]
m = [np.random.random((4, 3, 2, 7)).astype(np.float32),
np.random.random((2, 3, 2, 7)).astype(np.float32),
np.random.random((7, 3, 2, 7)).astype(np.float32)]
a = C.sequence.input_variable((3, 5, 2))
b = C.sequence.input_variable((3, 2, 7))
c = batchmatmul(a, b)
assert c.shape == (3, 5, 7)
desired_packed = [nn @ mm for nn, mm in zip(n, m)]
desired_results = desired_packed
results = c.eval({a: n, b: m})
assert len(results) == len(desired_results)
for result, desired in zip(results, desired_results):
np.testing.assert_almost_equal(result, desired, decimal=7)
def test_seq_batchmatmul3():
""" sequence axis present, left operand is matrix and right operand is tensor """
dynamic_batch = 2
seq_len = 4
matmul_batch = 3
batch_shape = (dynamic_batch, seq_len, matmul_batch)
left_operand_shape = (5, 2)
right_operand_shape = (2, 6, 3)
final_shape = (5, 6, 3)
n = np.random.random(batch_shape + left_operand_shape).astype(np.float32)
m = np.random.random(batch_shape + right_operand_shape).astype(np.float32)
a = C.sequence.input_variable((matmul_batch, ) + left_operand_shape)
b = C.sequence.input_variable((matmul_batch, ) + right_operand_shape)
c = batchmatmul(a, b, output_rank=2)
assert c.shape == (matmul_batch, ) + final_shape
desired_packed = n @ m.reshape(batch_shape + (2, -1))
desired = desired_packed.reshape(batch_shape + final_shape)
result = c.eval({a: n, b: m})
result = np.array(result)
np.testing.assert_almost_equal(result, desired, decimal=7)
