bugfix: fix decode kernels output for empty kv cache

include/flashinfer/attention/handler.cuh

@@ -238,7 +238,7 @@ cudaError_t PartitionPagedKVCacheComputeAuxiliaryInfo(
   for (uint32_t batch_idx = 0; batch_idx < old_batch_size; batch_idx++) {
     uint32_t num_chunks =
         ceil_div(old_indptr_h[batch_idx + 1] - old_indptr_h[batch_idx], max_num_pages_per_batch);
-    chunk_indptr_vec.push_back(chunk_indptr_vec.back() + num_chunks);
+    chunk_indptr_vec.push_back(chunk_indptr_vec.back() + std::max(num_chunks, 1U));
     if (num_chunks == 0) {
       new_page_indptr_vec.push_back(old_indptr_h[batch_idx]);
       new_last_page_len_vec.push_back(0);

python/tests/test_decode_prefill_lse.py

@@ -0,0 +1,79 @@
+"""
+Copyright (c) 2024 by FlashInfer team.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+import flashinfer
+import numpy as np
+import torch
+import pytest
+
+
+def test_mlc_failed_case():
+    kv_layout = "HND"
+    num_pages = 12
+    kv_indptr_1 = torch.tensor([0, 0, 9]).int().to(0)
+    kv_indices_1 = torch.tensor([3, 4, 5, 6, 7, 8, 9, 10, 11]).int().to(0)
+    kv_last_page_len_1 = torch.tensor([0, 1]).int().to(0)
+    num_qo_heads = 32
+    num_kv_heads = 32
+    page_size = 16
+    head_dim = 128
+    q = torch.randn(2, num_qo_heads, head_dim).to(0).half()
+    kv_data = torch.randn(12, 2, num_kv_heads, page_size, head_dim).to(0).half()
+
+    workspace_buffer = torch.empty(128 * 1024 * 1024, dtype=torch.int8).to(0)
+    wrapper = flashinfer.BatchDecodeWithPagedKVCacheWrapper(workspace_buffer, kv_layout)
+    wrapper.begin_forward(
+        kv_indptr_1,
+        kv_indices_1,
+        kv_last_page_len_1,
+        num_qo_heads,
+        num_kv_heads,
+        head_dim,
+        page_size,
+        pos_encoding_mode="NONE",
+        data_type=torch.float16,
+        q_data_type=torch.float16,
+    )
+    o_1, lse_1 = wrapper.forward_return_lse(q, kv_data)
+
+    wrapper_tensor_cores = flashinfer.BatchDecodeWithPagedKVCacheWrapper(
+        workspace_buffer, kv_layout, use_tensor_cores=True
+    )
+    wrapper_tensor_cores.begin_forward(
+        kv_indptr_1,
+        kv_indices_1,
+        kv_last_page_len_1,
+        num_qo_heads,
+        num_kv_heads,
+        head_dim,
+        page_size,
+        pos_encoding_mode="NONE",
+        data_type=torch.float16,
+        q_data_type=torch.float16,
+    )
+    o_1_tc, lse_1_tc = wrapper_tensor_cores.forward_return_lse(
+        q, kv_data
+    )
+
+    np.testing.assert_allclose(
+        lse_1.cpu().numpy(), lse_1_tc.cpu().numpy(), rtol=1e-3, atol=1e-3
+    )
+    np.testing.assert_allclose(
+        o_1.cpu().numpy(), o_1_tc.cpu().numpy(), rtol=1e-3, atol=1e-3
+    )
+
+if __name__ == "__main__":
+    test_mlc_failed_case()

python/tests/test_tensor_cores_decode.py

@@ -104,7 +104,7 @@ def test_batch_decode_tensor_cores(
         num_kv_heads,
         head_dim,
         page_size,
-        "NONE",
+        pos_encoding_mode=pos_encoding_mode,
         data_type=torch.float16,
         q_data_type=torch.float16,
     )
@@ -121,7 +121,7 @@ def test_batch_decode_tensor_cores(
         num_kv_heads,
         head_dim,
         page_size,
-        "NONE",
+        pos_encoding_mode=pos_encoding_mode,
         data_type=torch.float16,
         q_data_type=torch.float16,
     )
@@ -187,7 +187,7 @@ def test_batch_decode_tensor_cores_cuda_graph(
         num_kv_heads,
         head_dim,
         page_size,
-        "NONE",
+        pos_encoding_mode=pos_encoding_mode,
         data_type=torch.float16,
         q_data_type=torch.float16,
     )
@@ -226,7 +226,7 @@ def test_batch_decode_tensor_cores_cuda_graph(
         num_kv_heads,
         head_dim,
         page_size,
-        "NONE",
+        pos_encoding_mode=pos_encoding_mode,
         data_type=torch.float16,
         q_data_type=torch.float16,
     )