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support more dim for mul op npu (#34546)
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* support more dim for mul op npu

* update unit test according to reviewer's comment.
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@houj04
houj04 authored Aug 3, 2021
1 parent e7dcdb7 commit 2aedf16
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Showing 2 changed files with 124 additions and 5 deletions.
16 changes: 11 additions & 5 deletions paddle/fluid/operators/mul_op_npu.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -41,10 +41,13 @@ class MulNPUKernel : public framework::OpKernel<T> {
{{"transpose_x1", false}, {"transpose_x2", false}});

runner.Run(stream);
} else if (x->dims().size() == 3 && y->dims().size() == 2) {
} else if (x->dims().size() >= 3 && y->dims().size() == 2) {
// reshape
Tensor tmp_x(x->type());
int64_t sec_dim = x->dims()[1] * x->dims()[2];
int64_t sec_dim = x->dims()[1];
for (auto i = 2; i < x->dims().size(); i++) {
sec_dim *= x->dims()[i];
}
int64_t first_dim = x->dims()[0];
tmp_x.ShareDataWith(*x);
tmp_x.Resize(framework::make_ddim({first_dim, sec_dim}));
Expand All @@ -56,7 +59,7 @@ class MulNPUKernel : public framework::OpKernel<T> {
runner.Run(stream);
} else {
PADDLE_THROW(
platform::errors::InvalidArgument("npu error: not suppert dims"));
platform::errors::InvalidArgument("npu error: not support dims"));
}
// to do other
} else if (x->dims().size() == 3 && y->dims().size() == 2) {
Expand Down Expand Up @@ -135,7 +138,7 @@ class MulGradNPUKernel : public framework::OpKernel<T> {

runner_dy.Run(stream);
}
} else if (x->dims().size() == 3 && y->dims().size() == 2) {
} else if (x->dims().size() >= 3 && y->dims().size() == 2) {
// flatten => x.shape=[6, 4]
// matmul
if (dx) {
Expand All @@ -154,7 +157,10 @@ class MulGradNPUKernel : public framework::OpKernel<T> {
if (dy) {
// flatten
Tensor tmp_x(x->type());
int64_t sec_dim = x->dims()[1] * x->dims()[2];
int64_t sec_dim = x->dims()[1];
for (auto i = 2; i < x->dims().size(); i++) {
sec_dim *= x->dims()[i];
}
int64_t first_dim = x->dims()[0];
tmp_x.ShareDataWith(*x);
tmp_x.Resize(framework::make_ddim({first_dim, sec_dim}));
Expand Down
113 changes: 113 additions & 0 deletions python/paddle/fluid/tests/unittests/npu/test_mul_op_npu.py
100644 → 100755
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Original file line number Diff line number Diff line change
Expand Up @@ -170,6 +170,44 @@ def test_check_grad_ingore_y(self):
pass


class TestMul4(TestMul):
# case 4: (20, 2, 2, 3) * (12, 50) -> (20, 50), x_num_col_dims = 1
def config(self):
self.x_shape = (20, 2, 2, 3)
self.y_shape = (12, 50)

def setUp(self):
self.set_npu()
self.op_type = "mul"
self.place = paddle.NPUPlace(0)
self.init_dtype()
self.config()
np.random.seed(SEED)
self.inputs = {
'X': np.random.random(self.x_shape).astype(self.dtype),
'Y': np.random.random(self.y_shape).astype(self.dtype)
}
self.outputs = {
'Out': np.dot(self.inputs['X'].reshape(20, 12), self.inputs['Y'])
}


@skip_check_grad_ci(
reason="Don't support grad checking for NPU OP with FP16 data type.")
class TestMul4FP16(TestMul4):
def init_dtype(self):
self.dtype = np.float16

def test_check_grad_normal(self):
pass

def test_check_grad_ingore_x(self):
pass

def test_check_grad_ingore_y(self):
pass


class TestMulNet(unittest.TestCase):
def init_dtype(self):
self.dtype = np.float32
Expand Down Expand Up @@ -385,5 +423,80 @@ def test_npu(self):
self.assertTrue(np.allclose(npu_loss, cpu_loss))


class TestMulNet4_2(unittest.TestCase):
def init_dtype(self):
self.dtype = np.float32

def _test(self, run_npu=True):
main_prog = paddle.static.Program()
startup_prog = paddle.static.Program()
main_prog.random_seed = SEED
startup_prog.random_seed = SEED
np.random.seed(SEED)

a_np = np.random.random(size=(12, 5)).astype(self.dtype)
b_np = np.random.random(size=(12, 5)).astype(self.dtype)
c_np = np.random.random(size=(12, 5)).astype(self.dtype)
d_np = np.random.random(size=(12, 5)).astype(self.dtype)
label_np = np.random.randint(2, size=(2, 1)).astype('int64')

with paddle.static.program_guard(main_prog, startup_prog):
a = paddle.static.data(name="a", shape=[12, 5], dtype=self.dtype)
b = paddle.static.data(name="b", shape=[12, 5], dtype=self.dtype)
c = paddle.static.data(name="c", shape=[12, 5], dtype=self.dtype)
d = paddle.static.data(name="d", shape=[12, 5], dtype=self.dtype)
label = paddle.static.data(
name="label", shape=[2, 1], dtype='int64')

sum_1 = paddle.add(a, b) # [12, 5]
sum_2 = paddle.add(c, d) # [12, 5]
fc_1 = fluid.layers.fc(input=sum_1, size=2) # [12, 2]
fc_1_re_shape = paddle.reshape(fc_1, shape=[2, 3, 2, 2])
fc_2 = fluid.layers.fc(input=sum_2, size=2) # [12, 2]
result = paddle.fluid.layers.mul(fc_1_re_shape,
fc_2) # [2, 3, 2, 2] * [12, 2]

prediction = fluid.layers.fc(input=result, size=2, act='softmax')

cost = fluid.layers.cross_entropy(input=prediction, label=label)
loss = fluid.layers.reduce_mean(cost)
sgd = fluid.optimizer.SGD(learning_rate=0.01)
sgd.minimize(loss)

if run_npu:
place = paddle.NPUPlace(0)
else:
place = paddle.CPUPlace()
exe = paddle.static.Executor(place)
exe.run(startup_prog)

print("testMulNet4_2 tart run on {}".format(place))
for epoch in range(100):

pred_res, loss_res = exe.run(main_prog,
feed={
"a": a_np,
"b": b_np,
"c": c_np,
"d": d_np,
"label": label_np
},
fetch_list=[prediction, loss])
if epoch % 10 == 0:
print("Epoch {} | Prediction[0]: {}, Loss: {}".format(
epoch, pred_res[0], loss_res))

return pred_res, loss_res

def test_npu(self):
self.init_dtype()
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)

self.assertTrue(np.allclose(
npu_pred, cpu_pred, atol=1e-5)) # atol needed on cann 20.3
self.assertTrue(np.allclose(npu_loss, cpu_loss, atol=1e-5))


if __name__ == '__main__':
unittest.main()

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