def test_concat():
element_type = Type.f32
A = Parameter(element_type, Shape([1, 2]))
B = Parameter(element_type, Shape([1, 2]))
C = Parameter(element_type, Shape([1, 2]))
parameter_list = [A, B, C]
axis = 0
function = Function(NodeVector([Concat(NodeVector([A, B, C]), axis)]),
parameter_list, 'test')
backend, cf = make_backend_call_frame(function)
a = backend.make_primary_tensor_view(element_type, Shape([1, 2]))
b = backend.make_primary_tensor_view(element_type, Shape([1, 2]))
c = backend.make_primary_tensor_view(element_type, Shape([1, 2]))
result = backend.make_primary_tensor_view(element_type, Shape([3, 2]))
a.write(util.numpy_to_c(np.array([1, 2], dtype=np.float32)), 0, 8)
b.write(util.numpy_to_c(np.array([5, 6], dtype=np.float32)), 0, 8)
c.write(util.numpy_to_c(np.array([7, 8], dtype=np.float32)), 0, 8)
result_arr = np.zeros(6, dtype=np.float32).reshape(3, 2)
result.write(util.numpy_to_c(result_arr), 0, 24)
cf.call([result], [a, b, c])
result.read(util.numpy_to_c(result_arr), 0, 24)
a_arr = np.array([[1, 2]], dtype=np.float32)
b_arr = np.array([[5, 6]], dtype=np.float32)
c_arr = np.array([[7, 8]], dtype=np.float32)
result_arr_ref = np.concatenate((a_arr, b_arr, c_arr), axis)
assert np.allclose(result_arr, result_arr_ref)
def test_concat():
element_type = Type.f32
A = Parameter(element_type, Shape([1, 2]))
B = Parameter(element_type, Shape([1, 2]))
C = Parameter(element_type, Shape([1, 2]))
parameter_list = [A, B, C]
axis = 0
function = Function(NodeVector([Concat(NodeVector([A, B, C]), axis)]),
parameter_list, 'test')
backend = Backend.create(pytest.config.getoption('backend'))
a = backend.create_tensor(element_type, Shape([1, 2]))
b = backend.create_tensor(element_type, Shape([1, 2]))
c = backend.create_tensor(element_type, Shape([1, 2]))
result = backend.create_tensor(element_type, Shape([3, 2]))
a.write(util.numpy_to_c(np.array([1, 2], dtype=np.float32)), 0, 8)
b.write(util.numpy_to_c(np.array([5, 6], dtype=np.float32)), 0, 8)
c.write(util.numpy_to_c(np.array([7, 8], dtype=np.float32)), 0, 8)
result_arr = np.zeros(6, dtype=np.float32).reshape(3, 2)
result.write(util.numpy_to_c(result_arr), 0, 24)
backend.call(backend.compile(function), [result], [a, b, c])
result.read(util.numpy_to_c(result_arr), 0, 24)
a_arr = np.array([[1, 2]], dtype=np.float32)
b_arr = np.array([[5, 6]], dtype=np.float32)
c_arr = np.array([[7, 8]], dtype=np.float32)
result_arr_ref = np.concatenate((a_arr, b_arr, c_arr), axis)
assert np.allclose(result_arr, result_arr_ref)
def concat(nodes, axis): # type: (List[Node], int) -> Node
"""Concatenate input nodes into single new node along specified axis.
:param nodes: The nodes we want concatenate into single new node.
:param axis: The axis along which we want to concatenate input nodes.
:return: Return new node that is a concatenation of input nodes.
"""
return Concat(NodeVector(nodes), axis)
def concat(nodes, axis, name=None): # type: (List[Node], int, str) -> Node
"""Concatenate input nodes into single new node along specified axis.
:param nodes: The nodes we want concatenate into single new node.
:param axis: The axis along which we want to concatenate input nodes.
:param name: The optional new name for output node.
:return: Return new node that is a concatenation of input nodes.
"""
return Concat(nodes, axis)