提交 6e04e580 编写于 作者: W wanghaoshuang

Change input data type to int64_t in unitest and GPU kernel

上级 77cf21e5
......@@ -39,8 +39,8 @@ __global__ void FillFirstColumn(T* dist, const int M, const int N) {
}
template <typename T>
__global__ void Levenshtein(T* dist, const int* x1, const int* x2, const int M,
const int N, const int start) {
__global__ void Levenshtein(T* dist, const int64_t* x1, const int64_t* x2,
const int M, const int N, const int start) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
int offset = N;
int index = start + idx * offset;
......
......@@ -51,8 +51,8 @@ class TestEditDistanceOp(OpTest):
def setUp(self):
self.op_type = "edit_distance"
normalized = False
x1 = np.array([[0, 12, 3, 5, 8, 2]]).astype("int32")
x2 = np.array([[0, 12, 4, 7, 8]]).astype("int32")
x1 = np.array([[0, 12, 3, 5, 8, 2]]).astype("int64")
x2 = np.array([[0, 12, 4, 7, 8]]).astype("int64")
x1 = np.transpose(x1)
x2 = np.transpose(x2)
x1_lod = [0, 1, 5]
......@@ -79,8 +79,8 @@ class TestEditDistanceOpNormalized(OpTest):
def setUp(self):
self.op_type = "edit_distance"
normalized = True
x1 = np.array([[0, 10, 3, 6, 5, 8, 2]]).astype("int32")
x2 = np.array([[0, 10, 4, 6, 7, 8]]).astype("int32")
x1 = np.array([[0, 10, 3, 6, 5, 8, 2]]).astype("int64")
x2 = np.array([[0, 10, 4, 6, 7, 8]]).astype("int64")
x1 = np.transpose(x1)
x2 = np.transpose(x2)
x1_lod = [0, 1, 3, 6]
......
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