AIT softmax fix

python/aitemplate/backend/cuda/softmax/softmax.cuh

@@ -240,10 +240,10 @@ __global__ void softmax_small_k(Arguments<T> args, size_t M) {
 
     PRAGMA_UNROLL
     for (size_t i = 0; i < m; i++) {
-      T max = std::numeric_limits<T>::lowest();
+      T max = input_tile[i * K];
       // find max
       PRAGMA_UNROLL
-      for (size_t j = 0; j < K; j++) {
+      for (size_t j = 1; j < K; j++) {
         max = fast_max(input_tile[i * K + j], max);
       }
       // get sum
@@ -287,10 +287,10 @@ __global__ void softmax_small_k(Arguments<T> args, size_t M) {
         input_tile[j] = input[i * K + j];
       }
 
-      T max = std::numeric_limits<T>::lowest();
+      T max = input_tile[0];
       // find max
       PRAGMA_UNROLL
-      for (size_t j = 0; j < K; j++) {
+      for (size_t j = 1; j < K; j++) {
         max = fast_max(input_tile[j], max);
       }
       // get sum
@@ -865,13 +865,14 @@ __global__ void softmax_general(const T* input, T* output, size_t outer_size) {
          inner_index < InnerSize;
          inner_index += blockDim.y * gridDim.y) {
       const uint32_t data_offset = outer_offset + inner_index;
-      T local_max = std::numeric_limits<T>::lowest();
+      T local_max = input[data_offset + threadIdx.x * dim_stride];
       // First we reduce locally on a per-thread basis. We reduce #InnerThreads
       // consecutive rows of the tensor at once, so we read the #input values in
       // contiguous chunks of size #InnerThreads. For small values of InnerSize,
       // we have InnerThreads == InnerSize, and so we will read in one big
       // contiguous range.
-      for (uint32_t d = threadIdx.x; d < DimSize; d += blockDim.x) {
+      for (uint32_t d = threadIdx.x + blockDim.x; d < DimSize;
+           d += blockDim.x) {
         const T value = input[data_offset + d * dim_stride];
         local_max = fast_max(local_max, value);
       }

tests/unittest/ops/test_softmax.py

@@ -130,6 +130,20 @@ def _test_softmax(
                         (6, 8, 3, 3),
                         2,
                     ),
+                    (
+                        "zero_batch_size",
+                        "float16",
+                        (0,),
+                        (3, 3),
+                        0,
+                    ),
+                    (
+                        "empty_tensor",
+                        "float16",
+                        (2,),
+                        (0, 3),
+                        1,
+                    ),
                 ],
                 TestEnv.CUDA_SM80: [
                     ("dim_1_bf16", "bfloat16", (1, 2), (6,), 1),