def dynamic(self, value=1.0):
with fluid.dygraph.guard(self._place):
input = fluid.dygraph.to_variable(self.input)
tensor1 = fluid.dygraph.to_variable(self.tensor1)
tensor2 = fluid.dygraph.to_variable(self.tensor2)
out = paddle.addcmul(input, tensor1, tensor2, value)
return out.numpy()
def test_addcmul_with_broadcast0(self):
program = Program()
with program_guard(program):
input = fluid.data(name='in', shape=[3, 100], dtype='float32')
tensor1 = fluid.data(name='t1', shape=[3, 100], dtype='float32')
tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
out = paddle.addcmul(input, tensor1, tensor2)
self.assertEqual(out.shape, input.shape)
def test_addcmul(self):
program = Program()
with program_guard(program):
data_shape = [3, 64, 64]
input = fluid.data(name='in', shape=data_shape, dtype='float32')
tensor1 = fluid.data(name='t1', shape=data_shape, dtype='float32')
tensor2 = fluid.data(name='t2', shape=data_shape, dtype='float32')
out = paddle.addcmul(input, tensor1, tensor2)
self.assertEqual(out.shape, input.shape)
def test_addcmul_has_out(self):
program = Program()
with program_guard(program):
input = fluid.data(name='in', shape=[4, 100], dtype='float32')
tensor1 = fluid.data(name='t1', shape=[100], dtype='float32')
tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
out = fluid.data(name='out', shape=[4, 100], dtype='float32')
out = paddle.addcmul(input, tensor1, tensor2, out=out)
self.assertEqual(out.shape, input.shape)
def test_invalid_value_float():
program = Program()
with program_guard(program):
input = fluid.data(name='input', shape=[20, 20], dtype='int32')
tensor1 = fluid.data(name='tensor1',
shape=[20, 20],
dtype='int32')
tensor2 = fluid.data(name='tensor2',
shape=[20, 20],
dtype='int32')
out = paddle.addcmul(input, tensor1, tensor2, value=1.0)
def test_invalid_tensor2():
program = Program()
with program_guard(program):
input = fluid.data(name='input',
shape=[20, 20],
dtype='float32')
tensor1 = fluid.data(name='tensor1',
shape=[20, 20],
dtype='float32')
tensor2 = [20, 20]
out = paddle.addcmul(input, tensor1, tensor2)
def static(self, value=1.0):
prog = fluid.Program()
with fluid.program_guard(prog):
input = fluid.data(name="input", dtype=self._dtype, shape=[3, 100])
tensor1 = fluid.data(name="tensor1",
dtype=self._dtype,
shape=[100])
tensor2 = fluid.data(name="tensor2",
dtype=self._dtype,
shape=[3, 100])
out = paddle.addcmul(input, tensor1, tensor2, value)
exe = fluid.Executor(self._place)
return exe.run(feed={
"input": self.input,
"tensor1": self.tensor1,
"tensor2": self.tensor2
},
program=prog,
fetch_list=[out])[0]