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[CINN]fix one hot decomposite bug #68380

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[CINN]fix one hot decomposite bug #68380

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76 changes: 7 additions & 69 deletions paddle/fluid/primitive/composite/composite.h
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Original file line number Diff line number Diff line change
Expand Up @@ -209,75 +209,13 @@ std::tuple<Tensor, Tensor> huber_loss_decomp(const Tensor& input,

template <typename T>
Tensor one_hot_decomp(const Tensor& x, const Tensor& num_classes) {
auto num_classes_tensor =
backend::full_with_tensor<T>(num_classes, 0, x.dtype());
Tensor ans;
if (has_dynamic_shape(x.shape())) {
Tensor x_shape = shape<T>(x);
Tensor one_tensor = full<T>({1}, 1, x_shape.dtype());
Tensor zero_tensor = full<T>({1}, 0, x_shape.dtype());
Tensor x_dims = one_tensor;
for (size_t i = 0; i < x.shape().size(); i++) {
x_dims = x_dims * get_slice<T>(x_shape, i);
}
Tensor input_dim = concat<T>(
{x_dims, full<T>({1}, num_classes_tensor.shape()[0], x_shape.dtype())});
auto input_tensor = backend::full_with_tensor<T>(input_dim, 0, x.dtype());
auto output_dim = concat<T>(
{x_shape,
full<T>({1}, num_classes_tensor.shape()[0], x_shape.dtype())});
auto arange_tensor = backend::arange_with_tensor<T>(
zero_tensor, x_dims, one_tensor, x_shape.dtype());
Tensor reshape_dim = concat<T>({x_dims, one_tensor});
auto x_reshape = backend::reshape<T>(x, reshape_dim);
auto arange_tensor_reshape =
backend::reshape<T>(arange_tensor, reshape_dim);
auto index_tensor = concat<T>({arange_tensor_reshape, x_reshape}, 1);
auto update_tensor = backend::full_with_tensor<T>(x_dims, 1, x.dtype());
ans = backend::reshape<T>(
cast<T>(scatter_nd_add<T>(input_tensor, index_tensor, update_tensor),
DataType::FLOAT32),
output_dim);
} else {
std::vector<int64_t> input_dim;
int x_dims = 1;
for (size_t i = 0; i < x.shape().size(); i++) {
x_dims *= x.shape()[i];
}

input_dim.push_back(x_dims);
input_dim.push_back(num_classes_tensor.shape()[0]);
auto input_tensor = full<T>(input_dim, 0, x.dtype());

std::vector<int64_t> output_dim;
for (size_t i = 0; i < x.shape().size(); i++) {
output_dim.push_back(x.shape()[i]);
}
output_dim.push_back(num_classes_tensor.shape()[0]);

auto end = full<T>({1}, x_dims, x.dtype());
auto start = full<T>({1}, 0, x.dtype());
auto step = full<T>({1}, 1, x.dtype());
auto arange_tensor =
backend::arange_with_tensor<T>(start, end, step, x.dtype());

std::vector<int64_t> reshape_dim{x_dims, 1};
auto x_reshape = reshape<T>(x, reshape_dim);
auto arange_tensor_reshape = reshape<T>(arange_tensor, reshape_dim);

std::vector<Tensor> index_concat;
index_concat.push_back(arange_tensor_reshape);
index_concat.push_back(x_reshape);
auto index_tensor = concat<T>(index_concat, 1);

auto update_tensor = full<T>({x_dims}, 1, x.dtype());

ans = reshape<T>(
cast<T>(scatter_nd_add<T>(input_tensor, index_tensor, update_tensor),
DataType::FLOAT32),
output_dim);
}
return ans;
auto start = full<T>({1}, 0, x.dtype());
auto step = full<T>({1}, 1, x.dtype());
auto arange_class =
backend::arange_with_tensor<T>(start, num_classes, step, x.dtype());
auto reshape_x = backend::unsqueeze<T>(x, {-1});
auto equal_res = backend::equal<T>(reshape_x, arange_class);
return cast<T>(equal_res, phi::DataType::FLOAT32);
}

template <typename T>
Expand Down