[Excutor] Increase buffer size to prevent address corruption; add forward metadata debug tool (#3404)

* 修复buffer申请不够大，增加打印forwardmetadata的工具

* fix mistake

* Make CPU tensor in CPUPlace

* Add test about forward_meta_str and Add unitest_requirement

---------

Co-authored-by: RAM <gstian5555@outlook.com>

custom_ops/gpu_ops/append_attn/get_block_shape_and_split_kv_block.cu

@@ -289,7 +289,7 @@ std::vector<paddle::Tensor> GetBlockShapeAndSplitKVBlock(
     kv_tile_ids_per_batch =
         GetEmptyTensor({0}, paddle::DataType::INT32, seq_lens_encoder.place());
     kv_num_blocks_x_cpu =
-        GetEmptyTensor({0}, paddle::DataType::INT32, seq_lens_encoder.place());
+        GetEmptyTensor({0}, paddle::DataType::INT32, paddle::CPUPlace());
   }
 
   if (max_just_dec_len_this_time > 0) {

fastdeploy/model_executor/forward_meta.py

@@ -114,6 +114,39 @@ class ForwardMeta:
         if self.caches:
             del self.caches
 
+    def __str__(self) -> str:
+        """
+        Returns a concise string representation of the ForwardMeta object in a compact format.
+        """
+
+        def format_str(obj):
+            """
+            A helper function to recursively get a concise string representation of objects.
+            """
+            if obj is None:
+                return "None"
+            elif isinstance(obj, paddle.Tensor):
+                tensor_info = {
+                    "data_ptr": obj.data_ptr(),
+                    "shape": obj.shape,
+                    "dtype": str(obj.dtype),
+                    "place": str(obj.place),
+                }
+                return tensor_info
+            elif isinstance(obj, (list, tuple)):
+                return [format_str(item) for item in obj]
+            elif isinstance(obj, dict):
+                return {key: format_str(value) for key, value in obj.items()}
+            elif not isinstance(obj, (int, float, str, bool)) and hasattr(obj, "__dict__"):
+                info = {key: format_str(value) for key, value in obj.__dict__.items() if not key.startswith("_")}
+                return f"<{obj.__class__.__name__} object info: {info}>"
+            else:
+                return str(obj)
+
+        simplified_info = format_str(self.__dict__)
+        lines = [f"  {key}: {value}" for key, value in simplified_info.items()]
+        return "{\n" + ",\n".join(lines) + "\n}"
+
 
 @dataclass
 class XPUForwardMeta(ForwardMeta):

fastdeploy/worker/gpu_model_runner.py

@@ -681,9 +681,11 @@ class GPUModelRunner(ModelRunnerBase):
             dtype="int64",
         )
         self.share_inputs["cum_offsets"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
-        self.share_inputs["batch_id_per_token"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
-        self.share_inputs["cu_seqlens_q"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
-        self.share_inputs["cu_seqlens_k"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
+        self.share_inputs["batch_id_per_token"] = paddle.full(
+            [max_num_seqs * self.parallel_config.max_model_len, 1], 0, dtype="int32"
+        )
+        self.share_inputs["cu_seqlens_q"] = paddle.full([max_num_seqs + 1, 1], 0, dtype="int32")
+        self.share_inputs["cu_seqlens_k"] = paddle.full([max_num_seqs + 1, 1], 0, dtype="int32")
 
         # Declare AttentionBackend buffers
         self.share_inputs["decoder_batch_ids"] = None

scripts/unittest_requirement.txt

@@ -7,3 +7,4 @@ pytest-twisted
 anyio
 coverage
 diff-cover
+partial_json_parser

test/model_executor/test_forward_meta_str.py

@@ -0,0 +1,106 @@
+"""
+# Copyright (c) 2025 PaddlePaddle Authors. 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.
+"""
+
+import unittest
+
+import paddle
+
+from fastdeploy.model_executor.forward_meta import ForwardMeta
+
+
+class TOYGPUModelRunner:
+    def __init__(self):
+        self.forward_meta: ForwardMeta = None
+
+        self.max_num_seqs = 64
+        self.max_model_len = 1024
+        self.pre_max_block_num = 16
+        # Not the tensor in real sense, just for make ForwardMeta
+        self.share_inputs = {}
+        self.share_inputs["input_ids"] = paddle.full(
+            [self.max_num_seqs, self.max_model_len],
+            0,
+            dtype="int64",
+        )
+        self.share_inputs["ids_remove_padding"] = paddle.full(
+            [self.max_num_seqs * self.max_model_len],
+            0,
+            dtype="int64",
+        )
+        self.share_inputs["decoder_batch_ids"] = None
+        self.share_inputs["decoder_tile_ids_per_batch"] = None
+        self.share_inputs["decoder_num_blocks_cpu"] = None
+        self.share_inputs["max_len_tensor_cpu"] = None
+        self.share_inputs["seq_lens_encoder"] = paddle.full([self.max_num_seqs, 1], 0, dtype="int32")
+        self.share_inputs["seq_lens_decoder"] = paddle.full([self.max_num_seqs, 1], 0, dtype="int32")
+        self.share_inputs["seq_lens_this_time"] = paddle.full([self.max_num_seqs, 1], 0, dtype="int32")
+        self.share_inputs["batch_id_per_token"] = paddle.full(
+            [self.max_num_seqs * self.max_model_len, 1], 0, dtype="int32"
+        )
+        self.share_inputs["cu_seqlens_q"] = paddle.full([self.max_num_seqs + 1, 1], 0, dtype="int32")
+        self.share_inputs["cu_seqlens_k"] = paddle.full([self.max_num_seqs + 1, 1], 0, dtype="int32")
+        self.share_inputs["block_tables"] = paddle.full([self.max_num_seqs, self.pre_max_block_num], -1, dtype="int32")
+        self.share_inputs["caches"] = [
+            paddle.full([self.max_num_seqs, 4, self.max_model_len, self.pre_max_block_num], 0, dtype="int32")
+        ] * 16
+
+    def initialize_forward_meta(self):
+        """
+        Initialize forward meta
+        """
+        # Ignore the attentionbackbend for simplify
+        self.forward_meta = ForwardMeta(
+            input_ids=self.share_inputs["input_ids"],
+            ids_remove_padding=self.share_inputs["ids_remove_padding"],
+            # rotary_embs=self.share_inputs["rope_emb"],# Ignore the rope_emb for simplify
+            # attn_backend=self.attn_backends[0],# Ignore the attn_backbend for simplify
+            decoder_batch_ids=self.share_inputs["decoder_batch_ids"],
+            decoder_tile_ids_per_batch=self.share_inputs["decoder_tile_ids_per_batch"],
+            decoder_num_blocks_cpu=self.share_inputs["decoder_num_blocks_cpu"],
+            max_len_tensor_cpu=self.share_inputs["max_len_tensor_cpu"],
+            seq_lens_encoder=self.share_inputs["seq_lens_encoder"],
+            seq_lens_decoder=self.share_inputs["seq_lens_decoder"],
+            seq_lens_this_time=self.share_inputs["seq_lens_this_time"],
+            batch_id_per_token=self.share_inputs["batch_id_per_token"],
+            cu_seqlens_q=self.share_inputs["cu_seqlens_q"],
+            cu_seqlens_k=self.share_inputs["cu_seqlens_k"],
+            block_tables=self.share_inputs["block_tables"],
+            caches=self.share_inputs["caches"],
+        )
+
+
+class Test(unittest.TestCase):
+    def setUp(self):
+        """
+        Initialize the test environment
+        """
+        self.runner = TOYGPUModelRunner()
+
+    def test_case(self):
+        """
+        Check if the CustomAllreduce function works properly.
+        """
+        print(
+            "in test/model_executor/test_forward_meta_str.py, forward_meta :", self.runner.forward_meta
+        )  # Get None, Not Error
+        self.runner.initialize_forward_meta()
+        print(
+            "in test/model_executor/test_forward_meta_str.py, forward_meta :", self.runner.forward_meta
+        )  # Get information
+
+
+if __name__ == "__main__":
+    unittest.main()