def test_reshape_like(): x = sym.Variable("x") y = sym.Variable("y") z = sym.reshape_like(x, y) def forward(x, y): return np.reshape(x, y.shape) def backward(head_grads, x, y): return [np.reshape(head_grads, x.shape), np.zeros_like(y)] shape = {'x': (3, 4, 5), 'y': (5, 4, 3)} check_function(z, forward, backward, shape=shape)
def test_reshape_like(): x = sym.Variable("x") y = sym.Variable("y") z = sym.reshape_like(x, y) def forward(x, y): return np.reshape(x, y.shape) def backward(head_grads, x, y): return [np.reshape(head_grads, x.shape), np.zeros_like(y)] dtype = "float32" inputs = [('x', (3, 4, 5), x), ('y', (5, 4, 3), y)] helper(z, inputs, dtype, forward, backward)
def test_reshape_like(): x = sym.Variable("x") y = sym.Variable("y") z = sym.reshape_like(x, y) def forward(x, y): return np.reshape(x, y.shape) def backward(head_grads, x, y): return [np.reshape(head_grads, x.shape), np.zeros_like(y)] shape = {'x': (3, 4, 5), 'y': (5, 4, 3)} check_function(z, forward, backward, shape=shape)