def test_prelu_nhwc():
x = sym.Variable("x")
a = sym.Variable("a")
y = sym.prelu(data=x, alpha=a, axis=3)
def forward(x, a):
return (x < 0) * (x * a.reshape(1, 1, 3)) + (x >= 0) * x
shape = {'x': (1, 32, 32, 3), 'a': (3, )}
check_function(y, forward, shape=shape)
def test_prelu_nhwc():
x = sym.Variable("x")
a = sym.Variable("a")
y = sym.prelu(data=x, alpha=a, axis=3)
def forward(x, a):
return (x < 0) * (x * a.reshape(1, 1, 3)) + (x>=0) * x
shape = {'x': (1, 32, 32, 3), 'a': (3,)}
check_function(y, forward, shape=shape)
def test_prelu_nchw():
x = sym.Variable("x")
a = sym.Variable("a")
y = sym.prelu(data=x, alpha=a)
def forward(x, a):
return (x < 0) * (x * a.reshape(3, 1, 1)) + (x >= 0) * x
dtype = "float32"
dshape_x = (1, 3, 32, 32)
dshape_w = (3, )
inputs = [('x', dshape_x, x), ('a', dshape_w, a)]
helper(y, inputs, dtype, forward)
def check(in_shape, axis, out_shape):
x = sym.Variable("x", shape=in_shape)
w = sym.Variable("w")
y = sym.prelu(x, w, axis=axis, name="y")
sdict = infer_shape(y)
assert(tuple(sdict["y"][0]) == tuple(out_shape))
def check(in_shape, axis, out_shape):
x = sym.Variable("x", shape=in_shape)
w = sym.Variable("w")
y = sym.prelu(x, w, axis=axis, name="y")
sdict = infer_shape(y)
assert(tuple(sdict["y"][0]) == tuple(out_shape))
def test_prelu():
x = sym.Variable("x")
w = sym.Variable("w")
y = sym.prelu(x, w)
assert(y.list_input_names()[0] == 'x')
assert(y.list_input_names()[1] == 'w')
