Sync from v0.13

vllm/v1/sample/ops/logprobs.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Some utilities for logprobs, including logits."""
+
+import torch
+
+from vllm.platforms import current_platform
+
+
+@torch.compile(dynamic=True, backend=current_platform.simple_compile_backend)
+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)