init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

tests/ut/_310p/ops/test_gdn_310.py

@@ -0,0 +1,141 @@
+#
+# Copyright (c) 2026 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# 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.
+# This file is a part of the vllm-ascend project.
+#
+
+from types import SimpleNamespace
+
+import torch
+from vllm.v1.attention.backends.utils import NULL_BLOCK_ID
+
+from vllm_ascend._310p.ops.fla.gdn_310 import (
+    AscendGatedDeltaNetAttention310,
+    _mask_padded_recurrent_accepted_tokens,
+    _zero_padded_tokens,
+)
+from vllm_ascend._310p.ops.gdn_attn_builder_310 import (
+    AscendGDNAttentionBackend310,
+    AscendGDNAttentionMetadataBuilder310,
+)
+
+
+def test_ascend_gdn_attention_310_uses_310p_backend():
+    assert AscendGatedDeltaNetAttention310.get_attn_backend(object()) is AscendGDNAttentionBackend310
+    assert AscendGDNAttentionBackend310.get_builder_cls() is AscendGDNAttentionMetadataBuilder310
+
+
+def test_zero_padded_tokens_masks_only_padded_token_positions():
+    tensor = torch.arange(2 * 4 * 3, dtype=torch.float32).reshape(2, 4, 3)
+
+    masked = _zero_padded_tokens(tensor, torch.tensor(2), token_dim=1)
+
+    torch.testing.assert_close(masked[:, :2], tensor[:, :2])
+    assert torch.count_nonzero(masked[:, 2:]) == 0
+
+
+def test_mask_padded_recurrent_accepted_tokens_zeros_dummy_requests():
+    accepted_tokens = torch.tensor([2, 3, 4], dtype=torch.int64)
+    actual_seq_lengths = torch.tensor([4, 0, 1], dtype=torch.int32)
+
+    masked = _mask_padded_recurrent_accepted_tokens(
+        accepted_tokens,
+        actual_seq_lengths,
+    )
+
+    assert masked.dtype == torch.int32
+    assert masked.tolist() == [2, 0, 4]
+
+
+def test_builder310_pads_spec_decode_metadata_with_dummy_requests():
+    builder = object.__new__(AscendGDNAttentionMetadataBuilder310)
+    builder.spec_state_indices_tensor = torch.full((4, 2), -1, dtype=torch.int32)
+    builder.spec_sequence_masks = torch.empty(4, dtype=torch.bool)
+    builder.non_spec_token_indx = torch.empty(0, dtype=torch.int32)
+    builder.spec_token_indx = torch.empty(8, dtype=torch.int32)
+    builder.spec_query_start_loc = torch.empty(5, dtype=torch.int32)
+    builder.num_accepted_tokens = torch.empty(4, dtype=torch.int32)
+    builder.spec_actual_seq_lengths = torch.empty(5, dtype=torch.int32)
+    builder.use_full_cuda_graph = True
+    attn_metadata = SimpleNamespace(
+        num_prefills=0,
+        num_decodes=0,
+        num_spec_decodes=2,
+        spec_state_indices_tensor=torch.tensor(
+            [[3, 30], [4, 40]],
+            dtype=torch.int32,
+        ),
+        spec_sequence_masks=torch.tensor([True, True]),
+        spec_query_start_loc=torch.tensor([0, 4, 8], dtype=torch.int32),
+        num_accepted_tokens=torch.tensor([2, 3], dtype=torch.int32),
+        non_spec_token_indx=torch.empty(0, dtype=torch.int32),
+        spec_token_indx=torch.arange(8, dtype=torch.int32),
+    )
+
+    builder._pad_spec_decode_metadata(attn_metadata, graph_batch_size=4)
+
+    assert attn_metadata.spec_state_indices_tensor.tolist() == [
+        [3, 30],
+        [4, 40],
+        [NULL_BLOCK_ID, NULL_BLOCK_ID],
+        [NULL_BLOCK_ID, NULL_BLOCK_ID],
+    ]
+    assert attn_metadata.spec_sequence_masks.tolist() == [True, True, False, False]
+    assert attn_metadata.spec_query_start_loc.tolist() == [0, 4, 8, 8, 8]
+    assert attn_metadata.num_accepted_tokens.tolist() == [2, 3, 0, 0]
+    spec_meta = attn_metadata.spec_decode_metadata.spec_causal_conv1d
+    assert spec_meta.query_start_loc.data_ptr() == attn_metadata.spec_query_start_loc.data_ptr()
+    assert spec_meta.cache_indices.data_ptr() == attn_metadata.spec_state_indices_tensor.data_ptr()
+    assert spec_meta.num_accepted_tokens.data_ptr() == attn_metadata.num_accepted_tokens.data_ptr()
+    assert attn_metadata.spec_decode_metadata.actual_seq_lengths.tolist() == [0, 4, 4, 0, 0]
+
+
+def test_builder310_refreshes_non_spec_decode_graph_metadata():
+    builder = object.__new__(AscendGDNAttentionMetadataBuilder310)
+    builder.non_spec_state_indices_tensor = torch.full((4,), 77, dtype=torch.int32)
+    builder.non_spec_query_start_loc = torch.full((5,), 77, dtype=torch.int32)
+    builder.non_spec_actual_seq_lengths = torch.full((5,), 77, dtype=torch.int32)
+    builder.use_full_cuda_graph = True
+    attn_metadata = SimpleNamespace(
+        num_prefills=0,
+        num_decodes=4,
+        num_decode_tokens=2,
+        num_spec_decodes=0,
+        non_spec_state_indices_tensor=torch.tensor(
+            [10, 11, 98, 99],
+            dtype=torch.int32,
+        ),
+        non_spec_query_start_loc=torch.tensor(
+            [0, 1, 2, 2, 2],
+            dtype=torch.int32,
+        ),
+    )
+
+    builder._pad_decode_metadata(attn_metadata, graph_batch_size=4)
+
+    assert attn_metadata.non_spec_state_indices_tensor.tolist() == [
+        10,
+        11,
+        NULL_BLOCK_ID,
+        NULL_BLOCK_ID,
+    ]
+    assert attn_metadata.non_spec_query_start_loc.tolist() == [0, 1, 2, 2, 2]
+    assert attn_metadata.non_spec_state_indices_tensor.data_ptr() == builder.non_spec_state_indices_tensor.data_ptr()
+    assert attn_metadata.non_spec_query_start_loc.data_ptr() == builder.non_spec_query_start_loc.data_ptr()
+    decode_meta = attn_metadata.non_spec_decode_metadata
+    conv_meta = decode_meta.causal_conv1d
+    assert conv_meta.query_start_loc.data_ptr() == attn_metadata.non_spec_query_start_loc.data_ptr()
+    assert conv_meta.cache_indices.data_ptr() == attn_metadata.non_spec_state_indices_tensor.data_ptr()
+    assert decode_meta.actual_seq_lengths.data_ptr() == builder.non_spec_actual_seq_lengths.data_ptr()
+    assert decode_meta.actual_seq_lengths.tolist() == [0, 1, 1, 0, 0]