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[Zero-Dim] Support output 0D for argmin/argmax/median/kthvalue/mode/equal_all/allclose, test=allcase #51889

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merged 3 commits into from
Mar 21, 2023
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[Zero-Dim] Support output 0D for argmin/argmax/median/kthvalue/mode/equal_all/allclose, test=allcase #51889

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09fc20a
[Zero-Dim] Support output 0D for argmin/argmax/median/kthvalue/mode/e…
zhwesky2010 Mar 14, 2023
aba92d3
Merge branch 'develop' into output_0d1
zhwesky2010 Mar 20, 2023
6aa01c4
fix CI
zhwesky2010 Mar 20, 2023
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16 changes: 2 additions & 14 deletions paddle/phi/infermeta/binary.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -85,14 +85,7 @@ void AllValueCompareInferMeta(const MetaTensor& x,
MetaTensor* out,
MetaConfig config) {
detail::BinarySameInputDimsCheck(x, y, config);

auto x_dims = x.dims();
auto y_dims = y.dims();
if (x_dims.size() == 0 && y_dims.size() == 0) {
out->set_dims(phi::make_ddim({}));
} else {
out->set_dims(phi::make_ddim({1}));
}
out->set_dims(phi::make_ddim({}));
out->set_dtype(DataType::BOOL);
}

Expand Down Expand Up @@ -403,12 +396,7 @@ void CompareAllInferMeta(const MetaTensor& x,
errors::InvalidArgument(
"The size of dim_y should not be greater than dim_x's."));
out->share_lod(x);
if (!x.dims().size() || !y.dims().size()) {
out->set_dims(make_ddim({}));
} else {
out->set_dims(make_ddim({1}));
}
out->set_dtype(DataType::BOOL);
out->set_dims(make_ddim({}));
}

void ComplexInferMeta(const MetaTensor& x,
Expand Down
42 changes: 27 additions & 15 deletions paddle/phi/infermeta/unary.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -148,7 +148,11 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
if (!config.is_runtime && axis.FromTensor()) {
std::vector<int64_t> vec;
if (flatten) {
vec = {1};
if (keepdims) {
vec = std::vector<int64_t>(x.dims().size(), -1);
} else {
vec = {};
}
} else {
if (keepdims) {
vec = std::vector<int64_t>(x.dims().size(), -1);
Expand All @@ -169,7 +173,6 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
const auto& x_dims = x.dims();

auto x_rank = x.dims().size();
auto zero_dim_tensor = x_rank == 0;
if (x_rank > 0) {
PADDLE_ENFORCE_GE(int_axis,
-x_rank,
Expand Down Expand Up @@ -200,7 +203,7 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
if (config.is_runtime) {
if (dtype == phi::TransToProtoVarType(DataType::INT32)) {
int64_t all_element_num = 0;
if (flatten || zero_dim_tensor) {
if (flatten) {
all_element_num = phi::product(x_dims);
} else {
all_element_num = x_dims[int_axis];
Expand All @@ -218,11 +221,12 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
}

std::vector<int64_t> vec;

if (x_rank == 0) {
// vec is set to empty
} else if (flatten) {
vec.emplace_back(static_cast<int64_t>(1));
if (flatten) {
if (keepdims) {
vec = std::vector<int64_t>(x.dims().size(), 1);
} else {
vec = {};
}
} else {
for (int64_t i = 0; i < int_axis; i++) vec.emplace_back(x_dims[i]);
if (keepdims) {
Expand Down Expand Up @@ -1838,21 +1842,29 @@ void KthvalueInferMeta(const MetaTensor& x,
MetaConfig config) {
auto input_dims = x.dims();
const int& dim_size = input_dims.size();
PADDLE_ENFORCE_LE(axis,
dim_size,
phi::errors::InvalidArgument(
"the axis must be [-%d, %d), but received %d .",
dim_size,
dim_size,
axis));
if (dim_size > 0) {
PADDLE_ENFORCE_LT(axis,
dim_size,
phi::errors::InvalidArgument(
"the axis must be [-%d, %d), but received %d .",
dim_size,
dim_size,
axis));
PADDLE_ENFORCE_GE(axis,
-dim_size,
phi::errors::InvalidArgument(
"the axis must be [-%d, %d), but received %d .",
dim_size,
dim_size,
axis));
} else if (dim_size == 0) {
// 0-dim tensor
PADDLE_ENFORCE_EQ(axis == 0 || axis == -1,
true,
phi::errors::InvalidArgument(
"'axis'(%d) must be 0 or -1 if input tensor is "
"0-dim.",
axis));
}
if (axis < 0) axis += dim_size;
PADDLE_ENFORCE_GE(
Expand Down
74 changes: 38 additions & 36 deletions paddle/phi/kernels/cpu/arg_min_max_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -32,26 +32,34 @@ template <typename Context,
ArgMinMaxType argMinMaxValue>
struct ArgMinMaxFunctor {};

#define DECLARE_ARG_MIN_MAX_FUNCTOR(eigen_op_type, enum_argminmax_value) \
template <typename Context, typename T, typename Tout, int64_t Rank> \
struct ArgMinMaxFunctor<Context, T, Tout, Rank, enum_argminmax_value> { \
void operator()(const Context& dev_ctx, \
const DenseTensor& in, \
DenseTensor* out, \
phi::DDim x_dims, \
int64_t axis, \
bool keepdims) { \
auto in_eigen = EigenTensor<T, Rank>::From(in, x_dims); \
if (keepdims) { \
auto out_eigen = EigenTensor<Tout, Rank>::From(*out); \
out_eigen.device(*(dev_ctx.eigen_device())) = \
in_eigen.eigen_op_type(axis).template cast<Tout>(); \
} else { \
auto out_eigen = EigenTensor<Tout, Rank - 1>::From(*out); \
out_eigen.device(*(dev_ctx.eigen_device())) = \
in_eigen.eigen_op_type(axis).template cast<Tout>(); \
} \
} \
#define DECLARE_ARG_MIN_MAX_FUNCTOR(eigen_op_type, enum_argminmax_value) \
template <typename Context, typename T, typename Tout, int64_t Rank> \
struct ArgMinMaxFunctor<Context, T, Tout, Rank, enum_argminmax_value> { \
void operator()(const Context& dev_ctx, \
const DenseTensor& in, \
DenseTensor* out, \
phi::DDim x_dims, \
phi::DDim out_dims, \
int64_t axis, \
bool keepdims, \
bool flatten) { \
auto in_eigen = EigenTensor<T, Rank>::From(in, x_dims); \
if (flatten) { \
auto out_eigen = EigenTensor<Tout, 0>::From(*out, out_dims); \
out_eigen.device(*(dev_ctx.eigen_device())) = \
in_eigen.eigen_op_type(axis).template cast<Tout>(); \
} else { \
if (keepdims) { \
auto out_eigen = EigenTensor<Tout, Rank>::From(*out, out_dims); \
out_eigen.device(*(dev_ctx.eigen_device())) = \
in_eigen.eigen_op_type(axis).template cast<Tout>(); \
} else { \
auto out_eigen = EigenTensor<Tout, Rank - 1>::From(*out, out_dims); \
out_eigen.device(*(dev_ctx.eigen_device())) = \
in_eigen.eigen_op_type(axis).template cast<Tout>(); \
} \
} \
} \
}

DECLARE_ARG_MIN_MAX_FUNCTOR(argmin, ArgMinMaxType::kArgMin);
Expand Down Expand Up @@ -81,32 +89,30 @@ struct VisitDataArgMinMaxFunctor {
template <typename Tout>
void apply() const {
dev_ctx.template Alloc<Tout>(out);
bool new_keepdims = keepdims;
if (flatten) new_keepdims = true;

// if flatten, will construct the new dims for the cacluate
phi::DDim x_dims;
phi::DDim out_dims;
int new_axis = axis;
if (flatten) {
// always reduce 1D -> 0D
x_dims = phi::make_ddim({x.numel()});
// if flatten, the axis just as 0
out_dims = phi::make_ddim({});
new_axis = 0;
} else {
x_dims = x.dims();
out_dims = out->dims();
if (axis < 0) new_axis = axis + x_dims.size();
}

// For 0D Tensor
if (x.dims().size() == 0) {
phi::funcs::set_constant(dev_ctx, out, 0);
return;
}

#define CALL_ARG_MINMAX_FUNCTOR(rank) \
ArgMinMaxFunctor<Context, T, Tout, rank, EnumArgMinMaxValue> functor##rank; \
functor##rank(dev_ctx, x, out, x_dims, new_axis, new_keepdims)
functor##rank(dev_ctx, x, out, x_dims, out_dims, new_axis, keepdims, flatten)

switch (x_dims.size()) {
case 0:
phi::funcs::set_constant(dev_ctx, out, 0);
return;
case 1:
CALL_ARG_MINMAX_FUNCTOR(1);
break;
Expand Down Expand Up @@ -195,9 +201,7 @@ PD_REGISTER_KERNEL(argmin,
int32_t,
int64_t,
int16_t,
uint8_t) {
kernel->OutputAt(0).SetDataType(phi::DataType::UNDEFINED);
}
uint8_t) {}

PD_REGISTER_KERNEL(argmax,
CPU,
Expand All @@ -208,6 +212,4 @@ PD_REGISTER_KERNEL(argmax,
int32_t,
int64_t,
int16_t,
uint8_t) {
kernel->OutputAt(0).SetDataType(phi::DataType::UNDEFINED);
}
uint8_t) {}
6 changes: 4 additions & 2 deletions python/paddle/fluid/dygraph/learning_rate_scheduler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,8 +95,10 @@ def state_dict(self):
if isinstance(value, Variable):
assert (
value.size == 1
), "size of Variable in state_dict must be 1"
value = float(value)
), "the size of Variable in state_dict must be 1, but its size is {} with shape {}".format(
value.size, value.shape
)
value = value.item()
state_dict[key] = value

return state_dict
Expand Down
2 changes: 1 addition & 1 deletion .../paddle/fluid/tests/unittests/collective/fleet/parallel_dygraph_no_sync_gradient_check.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@ def __init__(self, train_id):

def forward(self, x):
is_use = (
paddle.equal_all(x, paddle.ones(shape=(batch, in_dim))).numpy()[0]
paddle.equal_all(x, paddle.ones(shape=(batch, in_dim))).item()
and self.trainer_id == 1
)

Expand Down
2 changes: 1 addition & 1 deletion python/paddle/fluid/tests/unittests/parallel_dygraph_gradient_check_in_eager_mode.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@ def __init__(self, train_id):

def forward(self, x):
is_use = (
paddle.equal_all(x, paddle.ones(shape=(batch, in_dim))).numpy()[0]
paddle.equal_all(x, paddle.ones(shape=(batch, in_dim))).item()
and self.trainer_id == 1
)

Expand Down
32 changes: 17 additions & 15 deletions python/paddle/fluid/tests/unittests/test_allclose_layer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@
import paddle
import paddle.fluid as fluid

paddle.enable_static()


class TestAllcloseLayer(unittest.TestCase):
def allclose_check(self, use_cuda, dtype='float32'):
Expand All @@ -44,31 +46,31 @@ def allclose_check(self, use_cuda, dtype='float32'):
result_v, result_nan_v = exe.run(
feed={'a': x, 'b': y}, fetch_list=[result, result_nan]
)
self.assertEqual(result_v[0], False)
self.assertEqual(result_nan_v[0], False)
self.assertEqual(result_v, False)
self.assertEqual(result_nan_v, False)

x = np.array([10000.0, 1e-08]).astype(dtype)
y = np.array([10000.1, 1e-09]).astype(dtype)
result_v, result_nan_v = exe.run(
feed={'a': x, 'b': y}, fetch_list=[result, result_nan]
)
self.assertEqual(result_v[0], True)
self.assertEqual(result_nan_v[0], True)
self.assertEqual(result_v, True)
self.assertEqual(result_nan_v, True)

x = np.array([1.0, float('nan')]).astype(dtype)
y = np.array([1.0, float('nan')]).astype(dtype)
result_v, result_nan_v = exe.run(
feed={'a': x, 'b': y}, fetch_list=[result, result_nan]
)
self.assertEqual(result_v[0], False)
self.assertEqual(result_nan_v[0], True)
self.assertEqual(result_v, False)
self.assertEqual(result_nan_v, True)

# for corner case
x = np.array([10.1, 10.1]).astype(dtype)
y = np.array([10, 10]).astype(dtype)
(result_c,) = exe.run(feed={'a': x, 'b': y}, fetch_list=[result_corner])
corner_res = dtype == 'float64'
self.assertEqual(result_c[0], corner_res)
self.assertEqual(result_c, corner_res)

def test_allclose_cpu_fp32(self):
main = fluid.Program()
Expand Down Expand Up @@ -123,7 +125,7 @@ def test_dygraph_mode(self):
equal_nan=False,
name='test_1',
)
self.assertEqual(ret_1.numpy()[0], False)
self.assertEqual(ret_1.numpy(), False)
ret_1 = paddle.allclose(
x_v_1,
y_v_1,
Expand All @@ -132,7 +134,7 @@ def test_dygraph_mode(self):
equal_nan=True,
name='test_2',
)
self.assertEqual(ret_1.numpy()[0], False)
self.assertEqual(ret_1.numpy(), False)
x_v_2 = paddle.to_tensor(x_2)
y_v_2 = paddle.to_tensor(y_2)
ret_2 = paddle.allclose(
Expand All @@ -143,7 +145,7 @@ def test_dygraph_mode(self):
equal_nan=False,
name='test_3',
)
self.assertEqual(ret_2.numpy()[0], True)
self.assertEqual(ret_2.numpy(), True)
ret_2 = paddle.allclose(
x_v_2,
y_v_2,
Expand All @@ -152,7 +154,7 @@ def test_dygraph_mode(self):
equal_nan=True,
name='test_4',
)
self.assertEqual(ret_2.numpy()[0], True)
self.assertEqual(ret_2.numpy(), True)
x_v_3 = paddle.to_tensor(x_3)
y_v_3 = paddle.to_tensor(y_3)
ret_3 = paddle.allclose(
Expand All @@ -163,7 +165,7 @@ def test_dygraph_mode(self):
equal_nan=False,
name='test_5',
)
self.assertEqual(ret_3.numpy()[0], False)
self.assertEqual(ret_3.numpy(), False)
ret_3 = paddle.allclose(
x_v_3,
y_v_3,
Expand All @@ -172,20 +174,20 @@ def test_dygraph_mode(self):
equal_nan=True,
name='test_6',
)
self.assertEqual(ret_3.numpy()[0], True)
self.assertEqual(ret_3.numpy(), True)
# for corner case
x_v_4 = paddle.to_tensor(x_4)
y_v_4 = paddle.to_tensor(y_4)
ret_4 = paddle.allclose(
x_v_4, y_v_4, rtol=0.01, atol=0.0, name='test_7'
)
self.assertEqual(ret_4.numpy()[0], False)
self.assertEqual(ret_4.numpy(), False)
x_v_5 = paddle.to_tensor(x_5)
y_v_5 = paddle.to_tensor(y_5)
ret_5 = paddle.allclose(
x_v_5, y_v_5, rtol=0.015, atol=0.0, name='test_8'
)
self.assertEqual(ret_5.numpy()[0], True)
self.assertEqual(ret_5.numpy(), True)


if __name__ == "__main__":
Expand Down
6 changes: 1 addition & 5 deletions python/paddle/fluid/tests/unittests/test_median.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,8 +32,6 @@ def static_single_test_median(self, lis_test):
paddle.enable_static()
x, axis, keepdims = lis_test
res_np = np.median(x, axis=axis, keepdims=keepdims)
if not isinstance(res_np, np.ndarray):
res_np = np.array([res_np])
main_program = Program()
startup_program = Program()
exe = paddle.static.Executor()
Expand All @@ -47,10 +45,8 @@ def static_single_test_median(self, lis_test):
def dygraph_single_test_median(self, lis_test):
x, axis, keepdims = lis_test
res_np = np.median(x, axis=axis, keepdims=keepdims)
if not isinstance(res_np, np.ndarray):
res_np = np.array([res_np])
res_pd = paddle.median(paddle.to_tensor(x), axis, keepdims)
self.check_numpy_res(res_pd.numpy(), res_np)
self.check_numpy_res(res_pd.numpy(False), res_np)

def test_median_static(self):
h = 3
Expand Down
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