def test_add_with_mul():
element_type = Type.f32
shape = Shape([2, 2])
A = Parameter(element_type, shape)
B = Parameter(element_type, shape)
C = Parameter(element_type, shape)
parameter_list = [A, B, C]
function = Function(NodeVector([Multiply(Add(A, B), C)]), parameter_list,
'test')
backend, cf = make_backend_call_frame(function)
a = backend.make_primary_tensor_view(element_type, shape)
b = backend.make_primary_tensor_view(element_type, shape)
c = backend.make_primary_tensor_view(element_type, shape)
result = backend.make_primary_tensor_view(element_type, shape)
a.write(util.numpy_to_c(np.array([1, 2, 3, 4], dtype=np.float32)), 0, 16)
b.write(util.numpy_to_c(np.array([5, 6, 7, 8], dtype=np.float32)), 0, 16)
c.write(util.numpy_to_c(np.array([9, 10, 11, 12], dtype=np.float32)), 0,
16)
result_arr = np.array([0, 0, 0, 0], dtype=np.float32)
result.write(util.numpy_to_c(result_arr), 0, 16)
cf.call([result], [a, b, c])
result.read(util.numpy_to_c(result_arr), 0, 16)
a_arr = np.array([1, 2, 3, 4], dtype=np.float32)
b_arr = np.array([5, 6, 7, 8], dtype=np.float32)
c_arr = np.array([9, 10, 11, 12], dtype=np.float32)
result_arr_ref = (a_arr + b_arr) * c_arr
assert np.allclose(result_arr, result_arr_ref)
def test_add_with_mul():
element_type = Type.f32
shape = Shape([2, 2])
A = Parameter(element_type, shape)
B = Parameter(element_type, shape)
C = Parameter(element_type, shape)
parameter_list = [A, B, C]
function = Function([Multiply(Add(A, B), C)], parameter_list, 'test')
backend = Backend.create(test.BACKEND_NAME)
a = backend.create_tensor(element_type, shape)
b = backend.create_tensor(element_type, shape)
c = backend.create_tensor(element_type, shape)
result = backend.create_tensor(element_type, shape)
a.write(util.numpy_to_c(np.array([1, 2, 3, 4], dtype=np.float32)), 16)
b.write(util.numpy_to_c(np.array([5, 6, 7, 8], dtype=np.float32)), 16)
c.write(util.numpy_to_c(np.array([9, 10, 11, 12], dtype=np.float32)), 16)
result_arr = np.array([0, 0, 0, 0], dtype=np.float32)
result.write(util.numpy_to_c(result_arr), 16)
handle = backend.compile(function)
handle.call([result], [a, b, c])
result.read(util.numpy_to_c(result_arr), 16)
a_arr = np.array([1, 2, 3, 4], dtype=np.float32)
b_arr = np.array([5, 6, 7, 8], dtype=np.float32)
c_arr = np.array([9, 10, 11, 12], dtype=np.float32)
result_arr_ref = (a_arr + b_arr) * c_arr
assert np.allclose(result_arr, result_arr_ref)
def binary_op(op_str, a, b):
if op_str == '+':
return a + b
elif op_str == 'Add':
return Add(a, b)
elif op_str == '-':
return a - b
elif op_str == 'Sub':
return Subtract(a, b)
elif op_str == '*':
return a * b
elif op_str == 'Mul':
return Multiply(a, b)
elif op_str == '/':
return a / b
elif op_str == 'Div':
return Divide(a, b)
elif op_str == 'Dot':
return Dot(a, b)
elif op_str == 'Equal':
return Equal(a, b)
elif op_str == 'Greater':
return Greater(a, b)
elif op_str == 'GreaterEq':
return GreaterEq(a, b)
elif op_str == 'Less':
return Less(a, b)
elif op_str == 'LessEq':
return LessEq(a, b)
elif op_str == 'Maximum':
return Maximum(a, b)
elif op_str == 'Minimum':
return Minimum(a, b)
elif op_str == 'NotEqual':
return NotEqual(a, b)
elif op_str == 'Power':
return Power(a, b)
def multiply(left_node,
right_node,
name=None): # type: (NodeInput, NodeInput, str) -> Node
"""Return node which applies f(x) = A*B to the input nodes elementwise."""
return Multiply(left_node, right_node)