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)
