first commit

vllm_br/v1/sample/ops/logprobs.py

@@ -0,0 +1,40 @@
+################################################################################
+# Copyright(c)2020-2025 Shanghai Biren Technology 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.
+#
+################################################################################
+"""Some utilities for logprobs, including logits."""
+
+import torch
+from fastcore.basics import patch_to
+
+from vllm.v1.sample.ops import logprobs
+
+
+@patch_to(logprobs)
+def batched_count_greater_than(x: torch.Tensor,
+                               values: torch.Tensor) -> torch.Tensor:
+    """
+    Counts elements in each row of x that are greater than the corresponding
+    value in values.  Use torch.compile to generate an optimized kernel for
+    this function. otherwise, it will create additional copies of the input
+    tensors and cause memory issues.
+
+    Args:
+        x (torch.Tensor): A 2D tensor of shape (batch_size, n_elements).
+        values (torch.Tensor): A 2D tensor of shape (batch_size, 1).
+
+    Returns:
+        torch.Tensor: A 1D tensor of shape (batch_size,) with the counts.
+    """
+    return (x >= values).sum(-1)