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  1. build/torch211-cxx11-cu126-aarch64-linux/_ops.py +3 -3
  2. build/torch211-cxx11-cu126-aarch64-linux/{_paged_attention_cuda_2567cd6.abi3.so → _paged_attention_cuda_2e4b976.abi3.so} +2 -2
  3. build/torch211-cxx11-cu126-aarch64-linux/metadata.json +3 -3
  4. build/torch211-cxx11-cu126-aarch64-linux/metadata.json.sigstore +1 -1
  5. build/torch211-cxx11-cu128-aarch64-linux/_ops.py +3 -3
  6. build/torch211-cxx11-cu128-aarch64-linux/{_paged_attention_cuda_2567cd6.abi3.so → _paged_attention_cuda_2e4b976.abi3.so} +2 -2
  7. build/torch211-cxx11-cu128-aarch64-linux/metadata.json +3 -3
  8. build/torch211-cxx11-cu128-aarch64-linux/metadata.json.sigstore +1 -1
  9. build/torch211-cxx11-cu130-aarch64-linux/_ops.py +3 -3
  10. build/{torch212-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2567cd6.abi3.so → torch211-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so} +2 -2
  11. build/torch211-cxx11-cu130-aarch64-linux/metadata.json +5 -4
  12. build/torch211-cxx11-cu130-aarch64-linux/metadata.json.sigstore +1 -1
  13. build/torch212-cxx11-cu126-aarch64-linux/_ops.py +3 -3
  14. build/torch212-cxx11-cu126-aarch64-linux/{_paged_attention_cuda_2567cd6.abi3.so → _paged_attention_cuda_2e4b976.abi3.so} +2 -2
  15. build/torch212-cxx11-cu126-aarch64-linux/metadata.json +3 -3
  16. build/torch212-cxx11-cu126-aarch64-linux/metadata.json.sigstore +1 -1
  17. build/torch212-cxx11-cu130-aarch64-linux/_ops.py +3 -3
  18. build/{torch212-cxx11-cu132-aarch64-linux/_paged_attention_cuda_2567cd6.abi3.so → torch212-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so} +2 -2
  19. build/torch212-cxx11-cu130-aarch64-linux/metadata.json +5 -4
  20. build/torch212-cxx11-cu130-aarch64-linux/metadata.json.sigstore +1 -1
  21. build/torch212-cxx11-cu132-aarch64-linux/_ops.py +3 -3
  22. build/{torch211-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2567cd6.abi3.so → torch212-cxx11-cu132-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so} +2 -2
  23. build/torch212-cxx11-cu132-aarch64-linux/metadata.json +5 -4
  24. build/torch212-cxx11-cu132-aarch64-linux/metadata.json.sigstore +1 -1
  25. build/torch213-cxx11-cu126-aarch64-linux/__init__.py +21 -0
  26. build/torch213-cxx11-cu126-aarch64-linux/_custom_ops.py +173 -0
  27. build/torch213-cxx11-cu126-aarch64-linux/_ops.py +9 -0
  28. build/torch213-cxx11-cu126-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so +3 -0
  29. build/torch213-cxx11-cu126-aarch64-linux/metadata.json +31 -0
  30. build/torch213-cxx11-cu126-aarch64-linux/metadata.json.sigstore +1 -0
  31. build/torch213-cxx11-cu126-aarch64-linux/paged_attention/__init__.py +26 -0
  32. build/torch213-cxx11-cu126-aarch64-linux/platforms.py +92 -0
  33. build/torch213-cxx11-cu130-aarch64-linux/__init__.py +21 -0
  34. build/torch213-cxx11-cu130-aarch64-linux/_custom_ops.py +173 -0
  35. build/torch213-cxx11-cu130-aarch64-linux/_ops.py +9 -0
  36. build/torch213-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so +3 -0
  37. build/torch213-cxx11-cu130-aarch64-linux/metadata.json +33 -0
  38. build/torch213-cxx11-cu130-aarch64-linux/metadata.json.sigstore +1 -0
  39. build/torch213-cxx11-cu130-aarch64-linux/paged_attention/__init__.py +26 -0
  40. build/torch213-cxx11-cu130-aarch64-linux/platforms.py +92 -0
  41. build/torch213-cxx11-cu132-aarch64-linux/__init__.py +21 -0
  42. build/torch213-cxx11-cu132-aarch64-linux/_custom_ops.py +173 -0
  43. build/torch213-cxx11-cu132-aarch64-linux/_ops.py +9 -0
  44. build/torch213-cxx11-cu132-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so +3 -0
  45. build/torch213-cxx11-cu132-aarch64-linux/metadata.json +33 -0
  46. build/torch213-cxx11-cu132-aarch64-linux/metadata.json.sigstore +1 -0
  47. build/torch213-cxx11-cu132-aarch64-linux/paged_attention/__init__.py +26 -0
  48. build/torch213-cxx11-cu132-aarch64-linux/platforms.py +92 -0
build/torch211-cxx11-cu126-aarch64-linux/_ops.py CHANGED
@@ -1,9 +1,9 @@
1
  import torch
2
- from . import _paged_attention_cuda_2567cd6
3
- ops = torch.ops._paged_attention_cuda_2567cd6
4
 
5
  def add_op_namespace_prefix(op_name: str):
6
  """
7
  Prefix op by namespace.
8
  """
9
- return f"_paged_attention_cuda_2567cd6::{op_name}"
 
1
  import torch
2
+ from . import _paged_attention_cuda_2e4b976
3
+ ops = torch.ops._paged_attention_cuda_2e4b976
4
 
5
  def add_op_namespace_prefix(op_name: str):
6
  """
7
  Prefix op by namespace.
8
  """
9
+ return f"_paged_attention_cuda_2e4b976::{op_name}"
build/torch211-cxx11-cu126-aarch64-linux/{_paged_attention_cuda_2567cd6.abi3.so → _paged_attention_cuda_2e4b976.abi3.so} RENAMED
@@ -1,3 +1,3 @@
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build/torch211-cxx11-cu126-aarch64-linux/metadata.json CHANGED
@@ -1,6 +1,6 @@
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  {
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  "name": "paged-attention",
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- "id": "_paged_attention_cuda_2567cd6",
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  "version": 1,
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  "license": "Apache-2.0",
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  "python-depends": [],
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- "_ops.py": "ST57L+IjX2AEwynOMEGFD3qRftGXGPHPmZrfIlvz6fo=",
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- "_paged_attention_cuda_2567cd6.abi3.so": "Ftd/gUMwzlZQIYbrQr46whsehi8lS6V/Tu4hLIXBeIY=",
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  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
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  }
 
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  {
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  "name": "paged-attention",
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+ "id": "_paged_attention_cuda_2e4b976",
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  "version": 1,
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  "license": "Apache-2.0",
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  "python-depends": [],
 
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  "files": {
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  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
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+ "_ops.py": "kDMCjGR2pbDnyHOIAK6WFgf5t3g+TwrXHuSAsZBE7v4=",
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+ "_paged_attention_cuda_2e4b976.abi3.so": "hpx/z2c3fSt8oxwdsPhXOKNh0AuFlrA4MWBC7nCewlo=",
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  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
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  """
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  Prefix op by namespace.
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  """
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- return f"_paged_attention_cuda_2567cd6::{op_name}"
 
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  import torch
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+ from . import _paged_attention_cuda_2e4b976
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+ ops = torch.ops._paged_attention_cuda_2e4b976
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  def add_op_namespace_prefix(op_name: str):
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  """
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  Prefix op by namespace.
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@@ -25,8 +25,8 @@
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  "files": {
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  "__init__.py": "oes6jQj02wGGtnJVomIE7ZJr2qnJmOm6CWurue5Vf6w=",
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  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
28
- "_ops.py": "ST57L+IjX2AEwynOMEGFD3qRftGXGPHPmZrfIlvz6fo=",
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- "_paged_attention_cuda_2567cd6.abi3.so": "YCd95OEiQk1uVDApnDdUO3X2KynJdxic9luUSe6xpwU=",
30
  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
31
  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
32
  }
 
1
  {
2
  "name": "paged-attention",
3
+ "id": "_paged_attention_cuda_2e4b976",
4
  "version": 1,
5
  "license": "Apache-2.0",
6
  "python-depends": [],
 
25
  "files": {
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  "__init__.py": "oes6jQj02wGGtnJVomIE7ZJr2qnJmOm6CWurue5Vf6w=",
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  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
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+ "_ops.py": "kDMCjGR2pbDnyHOIAK6WFgf5t3g+TwrXHuSAsZBE7v4=",
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+ "_paged_attention_cuda_2e4b976.abi3.so": "mfTW0CwO8aqOP5Ex1+G9IacQ5pVJ7D64UyMSKhQvWZc=",
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  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
31
  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
32
  }
build/torch211-cxx11-cu128-aarch64-linux/metadata.json.sigstore CHANGED
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  """
7
  Prefix op by namespace.
8
  """
9
- return f"_paged_attention_cuda_2567cd6::{op_name}"
 
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2
+ from . import _paged_attention_cuda_2e4b976
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+ ops = torch.ops._paged_attention_cuda_2e4b976
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5
  def add_op_namespace_prefix(op_name: str):
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  """
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  Prefix op by namespace.
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  "version": 1,
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  "license": "Apache-2.0",
6
  "python-depends": [],
@@ -22,8 +22,8 @@
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  "files": {
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  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
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- "_paged_attention_cuda_2567cd6.abi3.so": "SjEC1u/TFMRK/2PM/ywfOMxr/QxUww7m36nZjTsqbmc=",
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  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
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  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
29
  }
 
1
  {
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  "name": "paged-attention",
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+ "id": "_paged_attention_cuda_2e4b976",
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  "version": 1,
5
  "license": "Apache-2.0",
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  "python-depends": [],
 
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  "files": {
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  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
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build/torch212-cxx11-cu126-aarch64-linux/metadata.json.sigstore CHANGED
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build/torch212-cxx11-cu132-aarch64-linux/_ops.py CHANGED
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  import torch
2
- from . import _paged_attention_cuda_2567cd6
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- ops = torch.ops._paged_attention_cuda_2567cd6
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5
  def add_op_namespace_prefix(op_name: str):
6
  """
7
  Prefix op by namespace.
8
  """
9
- return f"_paged_attention_cuda_2567cd6::{op_name}"
 
1
  import torch
2
+ from . import _paged_attention_cuda_2e4b976
3
+ ops = torch.ops._paged_attention_cuda_2e4b976
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5
  def add_op_namespace_prefix(op_name: str):
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  """
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  Prefix op by namespace.
8
  """
9
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build/{torch211-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2567cd6.abi3.so → torch212-cxx11-cu132-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so} RENAMED
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build/torch212-cxx11-cu132-aarch64-linux/metadata.json CHANGED
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  "license": "Apache-2.0",
6
  "python-depends": [],
@@ -9,7 +9,8 @@
9
  "archs": [
10
  "10.0",
11
  "11.0",
12
- "12.0+PTX",
 
13
  "7.5",
14
  "8.0",
15
  "8.6",
@@ -23,8 +24,8 @@
23
  "files": {
24
  "__init__.py": "oes6jQj02wGGtnJVomIE7ZJr2qnJmOm6CWurue5Vf6w=",
25
  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
26
- "_ops.py": "ST57L+IjX2AEwynOMEGFD3qRftGXGPHPmZrfIlvz6fo=",
27
- "_paged_attention_cuda_2567cd6.abi3.so": "/8b0H/ac9iIvrF4YO2C9H8NxrdvFcPeV2vM3HVdxAoI=",
28
  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
29
  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
30
  }
 
1
  {
2
  "name": "paged-attention",
3
+ "id": "_paged_attention_cuda_2e4b976",
4
  "version": 1,
5
  "license": "Apache-2.0",
6
  "python-depends": [],
 
9
  "archs": [
10
  "10.0",
11
  "11.0",
12
+ "12.0",
13
+ "12.1+PTX",
14
  "7.5",
15
  "8.0",
16
  "8.6",
 
24
  "files": {
25
  "__init__.py": "oes6jQj02wGGtnJVomIE7ZJr2qnJmOm6CWurue5Vf6w=",
26
  "_custom_ops.py": "tnC6OR7TPhMV+tt8MyUyIH2gDIdxBzHT+1z1NUhA9EE=",
27
+ "_ops.py": "kDMCjGR2pbDnyHOIAK6WFgf5t3g+TwrXHuSAsZBE7v4=",
28
+ "_paged_attention_cuda_2e4b976.abi3.so": "Ku9Hklzf8WOhLa2PFbOlhpqeJRcWKdYMdpgWhkkXISM=",
29
  "paged_attention/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
30
  "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
31
  }
build/torch212-cxx11-cu132-aarch64-linux/metadata.json.sigstore CHANGED
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1
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build/torch213-cxx11-cu126-aarch64-linux/__init__.py ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from ._custom_ops import (
2
+ convert_fp8,
3
+ copy_blocks,
4
+ paged_attention_v1,
5
+ paged_attention_v2,
6
+ reshape_and_cache,
7
+ reshape_and_cache_flash,
8
+ swap_blocks,
9
+ )
10
+ from ._ops import ops
11
+
12
+ __all__ = [
13
+ "convert_fp8",
14
+ "copy_blocks",
15
+ "ops",
16
+ "paged_attention_v1",
17
+ "paged_attention_v2",
18
+ "reshape_and_cache",
19
+ "reshape_and_cache_flash",
20
+ "swap_blocks",
21
+ ]
build/torch213-cxx11-cu126-aarch64-linux/_custom_ops.py ADDED
@@ -0,0 +1,173 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from typing import List, Optional
2
+
3
+ import torch
4
+
5
+ from ._ops import ops
6
+
7
+
8
+ # page attention ops
9
+ def paged_attention_v1(
10
+ out: torch.Tensor,
11
+ query: torch.Tensor,
12
+ key_cache: torch.Tensor,
13
+ value_cache: torch.Tensor,
14
+ num_kv_heads: int,
15
+ scale: float,
16
+ block_tables: torch.Tensor,
17
+ seq_lens: torch.Tensor,
18
+ block_size: int,
19
+ max_seq_len: int,
20
+ alibi_slopes: Optional[torch.Tensor],
21
+ kv_cache_dtype: str,
22
+ k_scale: float,
23
+ v_scale: float,
24
+ tp_rank: int = 0,
25
+ blocksparse_local_blocks: int = 0,
26
+ blocksparse_vert_stride: int = 0,
27
+ blocksparse_block_size: int = 64,
28
+ blocksparse_head_sliding_step: int = 0,
29
+ ) -> None:
30
+ ops.paged_attention_v1(
31
+ out,
32
+ query,
33
+ key_cache,
34
+ value_cache,
35
+ num_kv_heads,
36
+ scale,
37
+ block_tables,
38
+ seq_lens,
39
+ block_size,
40
+ max_seq_len,
41
+ alibi_slopes,
42
+ kv_cache_dtype,
43
+ k_scale,
44
+ v_scale,
45
+ tp_rank,
46
+ blocksparse_local_blocks,
47
+ blocksparse_vert_stride,
48
+ blocksparse_block_size,
49
+ blocksparse_head_sliding_step,
50
+ )
51
+
52
+
53
+ def paged_attention_v2(
54
+ out: torch.Tensor,
55
+ exp_sum: torch.Tensor,
56
+ max_logits: torch.Tensor,
57
+ tmp_out: torch.Tensor,
58
+ query: torch.Tensor,
59
+ key_cache: torch.Tensor,
60
+ value_cache: torch.Tensor,
61
+ num_kv_heads: int,
62
+ scale: float,
63
+ block_tables: torch.Tensor,
64
+ seq_lens: torch.Tensor,
65
+ block_size: int,
66
+ max_seq_len: int,
67
+ alibi_slopes: Optional[torch.Tensor],
68
+ kv_cache_dtype: str,
69
+ k_scale: float,
70
+ v_scale: float,
71
+ tp_rank: int = 0,
72
+ blocksparse_local_blocks: int = 0,
73
+ blocksparse_vert_stride: int = 0,
74
+ blocksparse_block_size: int = 64,
75
+ blocksparse_head_sliding_step: int = 0,
76
+ ) -> None:
77
+ ops.paged_attention_v2(
78
+ out,
79
+ exp_sum,
80
+ max_logits,
81
+ tmp_out,
82
+ query,
83
+ key_cache,
84
+ value_cache,
85
+ num_kv_heads,
86
+ scale,
87
+ block_tables,
88
+ seq_lens,
89
+ block_size,
90
+ max_seq_len,
91
+ alibi_slopes,
92
+ kv_cache_dtype,
93
+ k_scale,
94
+ v_scale,
95
+ tp_rank,
96
+ blocksparse_local_blocks,
97
+ blocksparse_vert_stride,
98
+ blocksparse_block_size,
99
+ blocksparse_head_sliding_step,
100
+ )
101
+
102
+
103
+ def reshape_and_cache(
104
+ key: torch.Tensor,
105
+ value: torch.Tensor,
106
+ key_cache: torch.Tensor,
107
+ value_cache: torch.Tensor,
108
+ slot_mapping: torch.Tensor,
109
+ kv_cache_dtype: str,
110
+ k_scale: float,
111
+ v_scale: float,
112
+ ) -> None:
113
+ ops.reshape_and_cache(
114
+ key,
115
+ value,
116
+ key_cache,
117
+ value_cache,
118
+ slot_mapping,
119
+ kv_cache_dtype,
120
+ k_scale,
121
+ v_scale,
122
+ )
123
+
124
+
125
+ def reshape_and_cache_flash(
126
+ key: torch.Tensor,
127
+ value: torch.Tensor,
128
+ key_cache: torch.Tensor,
129
+ value_cache: torch.Tensor,
130
+ slot_mapping: torch.Tensor,
131
+ kv_cache_dtype: str,
132
+ k_scale: torch.Tensor,
133
+ v_scale: torch.Tensor,
134
+ ) -> None:
135
+ ops.reshape_and_cache_flash(
136
+ key,
137
+ value,
138
+ key_cache,
139
+ value_cache,
140
+ slot_mapping,
141
+ kv_cache_dtype,
142
+ k_scale,
143
+ v_scale,
144
+ )
145
+
146
+
147
+ def copy_blocks(
148
+ key_caches: List[torch.Tensor],
149
+ value_caches: List[torch.Tensor],
150
+ block_mapping: torch.Tensor,
151
+ ) -> None:
152
+ ops.copy_blocks(key_caches, value_caches, block_mapping)
153
+
154
+
155
+ def swap_blocks(
156
+ src: torch.Tensor, dst: torch.Tensor, block_mapping: torch.Tensor
157
+ ) -> None:
158
+ ops.swap_blocks(src, dst, block_mapping)
159
+
160
+
161
+ def convert_fp8(
162
+ output: torch.Tensor, input: torch.Tensor, scale: float = 1.0, kv_dtype: str = "fp8"
163
+ ) -> None:
164
+ ops.convert_fp8(output, input, scale, kv_dtype)
165
+
166
+
167
+ __all__ = [
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+ "convert_fp8",
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+ "paged_attention_v1",
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+ "paged_attention_v2",
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+ "reshape_and_cache",
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+ "copy_blocks",
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+ ]
build/torch213-cxx11-cu126-aarch64-linux/_ops.py ADDED
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+ import torch
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+ from . import _paged_attention_cuda_2e4b976
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+ ops = torch.ops._paged_attention_cuda_2e4b976
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+
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+ def add_op_namespace_prefix(op_name: str):
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+ """
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+ Prefix op by namespace.
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+ """
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+ return f"_paged_attention_cuda_2e4b976::{op_name}"
build/torch213-cxx11-cu126-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so ADDED
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build/torch213-cxx11-cu126-aarch64-linux/paged_attention/__init__.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import ctypes
2
+ import importlib.util
3
+ import sys
4
+ from pathlib import Path
5
+ from types import ModuleType
6
+
7
+
8
+ def _import_from_path(file_path: Path) -> ModuleType:
9
+ # We cannot use the module name as-is, after adding it to `sys.modules`,
10
+ # it would also be used for other imports. So, we make a module name that
11
+ # depends on the path for it to be unique using the hex-encoded hash of
12
+ # the path.
13
+ path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
14
+ module_name = path_hash
15
+ spec = importlib.util.spec_from_file_location(module_name, file_path)
16
+ if spec is None:
17
+ raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
18
+ module = importlib.util.module_from_spec(spec)
19
+ if module is None:
20
+ raise ImportError(f"Cannot load module {module_name} from spec")
21
+ sys.modules[module_name] = module
22
+ spec.loader.exec_module(module) # type: ignore
23
+ return module
24
+
25
+
26
+ globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))
build/torch213-cxx11-cu126-aarch64-linux/platforms.py ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import random
3
+ from abc import ABC, abstractmethod
4
+ from functools import lru_cache, wraps
5
+ from typing import Callable, ParamSpec, TypeVar
6
+
7
+ import numpy as np
8
+ import torch
9
+
10
+ IS_ROCM = torch.version.hip is not None
11
+ IS_MPS = torch.backends.mps.is_available()
12
+
13
+
14
+ class Platform(ABC):
15
+ @classmethod
16
+ def seed_everything(cls, seed: int) -> None:
17
+ """
18
+ Set the seed of each random module.
19
+ `torch.manual_seed` will set seed on all devices.
20
+
21
+ Loosely based on: https://github.com/Lightning-AI/pytorch-lightning/blob/2.4.0/src/lightning/fabric/utilities/seed.py#L20
22
+ """
23
+ random.seed(seed)
24
+ np.random.seed(seed)
25
+ torch.manual_seed(seed)
26
+
27
+ @abstractmethod
28
+ def get_device_name(self, device_id: int = 0) -> str: ...
29
+
30
+ @abstractmethod
31
+ def is_cuda(self) -> bool: ...
32
+
33
+ @abstractmethod
34
+ def is_rocm(self) -> bool: ...
35
+
36
+ @abstractmethod
37
+ def is_mps(self) -> bool: ...
38
+
39
+
40
+ class CudaPlatform(Platform):
41
+ @classmethod
42
+ @lru_cache(maxsize=8)
43
+ def get_device_name(cls, device_id: int = 0) -> str:
44
+ return torch.cuda.get_device_name(0)
45
+
46
+ def is_cuda(self) -> bool:
47
+ return True
48
+
49
+ def is_rocm(self) -> bool:
50
+ return False
51
+
52
+ def is_mps(self) -> bool:
53
+ return False
54
+
55
+
56
+ class RocmPlatform(Platform):
57
+ @classmethod
58
+ @lru_cache(maxsize=8)
59
+ def get_device_name(cls, device_id: int = 0) -> str:
60
+ return torch.cuda.get_device_name(device_id)
61
+
62
+ def is_cuda(self) -> bool:
63
+ return False
64
+
65
+ def is_rocm(self) -> bool:
66
+ return True
67
+
68
+ def is_mps(self) -> bool:
69
+ return False
70
+
71
+
72
+ class MpsPlatform(Platform):
73
+ @classmethod
74
+ @lru_cache(maxsize=8)
75
+ def get_device_name(cls, device_id: int = 0) -> str:
76
+ return torch.cuda.get_device_name(device_id)
77
+
78
+ def is_cuda(self) -> bool:
79
+ return False
80
+
81
+ def is_rocm(self) -> bool:
82
+ return False
83
+
84
+ def is_mps(self) -> bool:
85
+ return True
86
+
87
+ current_platform = (
88
+ RocmPlatform() if IS_ROCM else
89
+ MpsPlatform() if IS_MPS else
90
+ CudaPlatform() if torch.cuda.is_available() else
91
+ None
92
+ )
build/torch213-cxx11-cu130-aarch64-linux/__init__.py ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from ._custom_ops import (
2
+ convert_fp8,
3
+ copy_blocks,
4
+ paged_attention_v1,
5
+ paged_attention_v2,
6
+ reshape_and_cache,
7
+ reshape_and_cache_flash,
8
+ swap_blocks,
9
+ )
10
+ from ._ops import ops
11
+
12
+ __all__ = [
13
+ "convert_fp8",
14
+ "copy_blocks",
15
+ "ops",
16
+ "paged_attention_v1",
17
+ "paged_attention_v2",
18
+ "reshape_and_cache",
19
+ "reshape_and_cache_flash",
20
+ "swap_blocks",
21
+ ]
build/torch213-cxx11-cu130-aarch64-linux/_custom_ops.py ADDED
@@ -0,0 +1,173 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from typing import List, Optional
2
+
3
+ import torch
4
+
5
+ from ._ops import ops
6
+
7
+
8
+ # page attention ops
9
+ def paged_attention_v1(
10
+ out: torch.Tensor,
11
+ query: torch.Tensor,
12
+ key_cache: torch.Tensor,
13
+ value_cache: torch.Tensor,
14
+ num_kv_heads: int,
15
+ scale: float,
16
+ block_tables: torch.Tensor,
17
+ seq_lens: torch.Tensor,
18
+ block_size: int,
19
+ max_seq_len: int,
20
+ alibi_slopes: Optional[torch.Tensor],
21
+ kv_cache_dtype: str,
22
+ k_scale: float,
23
+ v_scale: float,
24
+ tp_rank: int = 0,
25
+ blocksparse_local_blocks: int = 0,
26
+ blocksparse_vert_stride: int = 0,
27
+ blocksparse_block_size: int = 64,
28
+ blocksparse_head_sliding_step: int = 0,
29
+ ) -> None:
30
+ ops.paged_attention_v1(
31
+ out,
32
+ query,
33
+ key_cache,
34
+ value_cache,
35
+ num_kv_heads,
36
+ scale,
37
+ block_tables,
38
+ seq_lens,
39
+ block_size,
40
+ max_seq_len,
41
+ alibi_slopes,
42
+ kv_cache_dtype,
43
+ k_scale,
44
+ v_scale,
45
+ tp_rank,
46
+ blocksparse_local_blocks,
47
+ blocksparse_vert_stride,
48
+ blocksparse_block_size,
49
+ blocksparse_head_sliding_step,
50
+ )
51
+
52
+
53
+ def paged_attention_v2(
54
+ out: torch.Tensor,
55
+ exp_sum: torch.Tensor,
56
+ max_logits: torch.Tensor,
57
+ tmp_out: torch.Tensor,
58
+ query: torch.Tensor,
59
+ key_cache: torch.Tensor,
60
+ value_cache: torch.Tensor,
61
+ num_kv_heads: int,
62
+ scale: float,
63
+ block_tables: torch.Tensor,
64
+ seq_lens: torch.Tensor,
65
+ block_size: int,
66
+ max_seq_len: int,
67
+ alibi_slopes: Optional[torch.Tensor],
68
+ kv_cache_dtype: str,
69
+ k_scale: float,
70
+ v_scale: float,
71
+ tp_rank: int = 0,
72
+ blocksparse_local_blocks: int = 0,
73
+ blocksparse_vert_stride: int = 0,
74
+ blocksparse_block_size: int = 64,
75
+ blocksparse_head_sliding_step: int = 0,
76
+ ) -> None:
77
+ ops.paged_attention_v2(
78
+ out,
79
+ exp_sum,
80
+ max_logits,
81
+ tmp_out,
82
+ query,
83
+ key_cache,
84
+ value_cache,
85
+ num_kv_heads,
86
+ scale,
87
+ block_tables,
88
+ seq_lens,
89
+ block_size,
90
+ max_seq_len,
91
+ alibi_slopes,
92
+ kv_cache_dtype,
93
+ k_scale,
94
+ v_scale,
95
+ tp_rank,
96
+ blocksparse_local_blocks,
97
+ blocksparse_vert_stride,
98
+ blocksparse_block_size,
99
+ blocksparse_head_sliding_step,
100
+ )
101
+
102
+
103
+ def reshape_and_cache(
104
+ key: torch.Tensor,
105
+ value: torch.Tensor,
106
+ key_cache: torch.Tensor,
107
+ value_cache: torch.Tensor,
108
+ slot_mapping: torch.Tensor,
109
+ kv_cache_dtype: str,
110
+ k_scale: float,
111
+ v_scale: float,
112
+ ) -> None:
113
+ ops.reshape_and_cache(
114
+ key,
115
+ value,
116
+ key_cache,
117
+ value_cache,
118
+ slot_mapping,
119
+ kv_cache_dtype,
120
+ k_scale,
121
+ v_scale,
122
+ )
123
+
124
+
125
+ def reshape_and_cache_flash(
126
+ key: torch.Tensor,
127
+ value: torch.Tensor,
128
+ key_cache: torch.Tensor,
129
+ value_cache: torch.Tensor,
130
+ slot_mapping: torch.Tensor,
131
+ kv_cache_dtype: str,
132
+ k_scale: torch.Tensor,
133
+ v_scale: torch.Tensor,
134
+ ) -> None:
135
+ ops.reshape_and_cache_flash(
136
+ key,
137
+ value,
138
+ key_cache,
139
+ value_cache,
140
+ slot_mapping,
141
+ kv_cache_dtype,
142
+ k_scale,
143
+ v_scale,
144
+ )
145
+
146
+
147
+ def copy_blocks(
148
+ key_caches: List[torch.Tensor],
149
+ value_caches: List[torch.Tensor],
150
+ block_mapping: torch.Tensor,
151
+ ) -> None:
152
+ ops.copy_blocks(key_caches, value_caches, block_mapping)
153
+
154
+
155
+ def swap_blocks(
156
+ src: torch.Tensor, dst: torch.Tensor, block_mapping: torch.Tensor
157
+ ) -> None:
158
+ ops.swap_blocks(src, dst, block_mapping)
159
+
160
+
161
+ def convert_fp8(
162
+ output: torch.Tensor, input: torch.Tensor, scale: float = 1.0, kv_dtype: str = "fp8"
163
+ ) -> None:
164
+ ops.convert_fp8(output, input, scale, kv_dtype)
165
+
166
+
167
+ __all__ = [
168
+ "convert_fp8",
169
+ "paged_attention_v1",
170
+ "paged_attention_v2",
171
+ "reshape_and_cache",
172
+ "copy_blocks",
173
+ ]
build/torch213-cxx11-cu130-aarch64-linux/_ops.py ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ from . import _paged_attention_cuda_2e4b976
3
+ ops = torch.ops._paged_attention_cuda_2e4b976
4
+
5
+ def add_op_namespace_prefix(op_name: str):
6
+ """
7
+ Prefix op by namespace.
8
+ """
9
+ return f"_paged_attention_cuda_2e4b976::{op_name}"
build/torch213-cxx11-cu130-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so ADDED
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+ size 90545864
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+ "id": "_paged_attention_cuda_2e4b976",
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+ "version": 1,
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+ "python-depends": [],
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+ "backend": {
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+ "type": "cuda",
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+ "archs": [
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+ "11.0",
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+ "files": {
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build/torch213-cxx11-cu130-aarch64-linux/metadata.json.sigstore ADDED
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build/torch213-cxx11-cu130-aarch64-linux/paged_attention/__init__.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import ctypes
2
+ import importlib.util
3
+ import sys
4
+ from pathlib import Path
5
+ from types import ModuleType
6
+
7
+
8
+ def _import_from_path(file_path: Path) -> ModuleType:
9
+ # We cannot use the module name as-is, after adding it to `sys.modules`,
10
+ # it would also be used for other imports. So, we make a module name that
11
+ # depends on the path for it to be unique using the hex-encoded hash of
12
+ # the path.
13
+ path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
14
+ module_name = path_hash
15
+ spec = importlib.util.spec_from_file_location(module_name, file_path)
16
+ if spec is None:
17
+ raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
18
+ module = importlib.util.module_from_spec(spec)
19
+ if module is None:
20
+ raise ImportError(f"Cannot load module {module_name} from spec")
21
+ sys.modules[module_name] = module
22
+ spec.loader.exec_module(module) # type: ignore
23
+ return module
24
+
25
+
26
+ globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))
build/torch213-cxx11-cu130-aarch64-linux/platforms.py ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import random
3
+ from abc import ABC, abstractmethod
4
+ from functools import lru_cache, wraps
5
+ from typing import Callable, ParamSpec, TypeVar
6
+
7
+ import numpy as np
8
+ import torch
9
+
10
+ IS_ROCM = torch.version.hip is not None
11
+ IS_MPS = torch.backends.mps.is_available()
12
+
13
+
14
+ class Platform(ABC):
15
+ @classmethod
16
+ def seed_everything(cls, seed: int) -> None:
17
+ """
18
+ Set the seed of each random module.
19
+ `torch.manual_seed` will set seed on all devices.
20
+
21
+ Loosely based on: https://github.com/Lightning-AI/pytorch-lightning/blob/2.4.0/src/lightning/fabric/utilities/seed.py#L20
22
+ """
23
+ random.seed(seed)
24
+ np.random.seed(seed)
25
+ torch.manual_seed(seed)
26
+
27
+ @abstractmethod
28
+ def get_device_name(self, device_id: int = 0) -> str: ...
29
+
30
+ @abstractmethod
31
+ def is_cuda(self) -> bool: ...
32
+
33
+ @abstractmethod
34
+ def is_rocm(self) -> bool: ...
35
+
36
+ @abstractmethod
37
+ def is_mps(self) -> bool: ...
38
+
39
+
40
+ class CudaPlatform(Platform):
41
+ @classmethod
42
+ @lru_cache(maxsize=8)
43
+ def get_device_name(cls, device_id: int = 0) -> str:
44
+ return torch.cuda.get_device_name(0)
45
+
46
+ def is_cuda(self) -> bool:
47
+ return True
48
+
49
+ def is_rocm(self) -> bool:
50
+ return False
51
+
52
+ def is_mps(self) -> bool:
53
+ return False
54
+
55
+
56
+ class RocmPlatform(Platform):
57
+ @classmethod
58
+ @lru_cache(maxsize=8)
59
+ def get_device_name(cls, device_id: int = 0) -> str:
60
+ return torch.cuda.get_device_name(device_id)
61
+
62
+ def is_cuda(self) -> bool:
63
+ return False
64
+
65
+ def is_rocm(self) -> bool:
66
+ return True
67
+
68
+ def is_mps(self) -> bool:
69
+ return False
70
+
71
+
72
+ class MpsPlatform(Platform):
73
+ @classmethod
74
+ @lru_cache(maxsize=8)
75
+ def get_device_name(cls, device_id: int = 0) -> str:
76
+ return torch.cuda.get_device_name(device_id)
77
+
78
+ def is_cuda(self) -> bool:
79
+ return False
80
+
81
+ def is_rocm(self) -> bool:
82
+ return False
83
+
84
+ def is_mps(self) -> bool:
85
+ return True
86
+
87
+ current_platform = (
88
+ RocmPlatform() if IS_ROCM else
89
+ MpsPlatform() if IS_MPS else
90
+ CudaPlatform() if torch.cuda.is_available() else
91
+ None
92
+ )
build/torch213-cxx11-cu132-aarch64-linux/__init__.py ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from ._custom_ops import (
2
+ convert_fp8,
3
+ copy_blocks,
4
+ paged_attention_v1,
5
+ paged_attention_v2,
6
+ reshape_and_cache,
7
+ reshape_and_cache_flash,
8
+ swap_blocks,
9
+ )
10
+ from ._ops import ops
11
+
12
+ __all__ = [
13
+ "convert_fp8",
14
+ "copy_blocks",
15
+ "ops",
16
+ "paged_attention_v1",
17
+ "paged_attention_v2",
18
+ "reshape_and_cache",
19
+ "reshape_and_cache_flash",
20
+ "swap_blocks",
21
+ ]
build/torch213-cxx11-cu132-aarch64-linux/_custom_ops.py ADDED
@@ -0,0 +1,173 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from typing import List, Optional
2
+
3
+ import torch
4
+
5
+ from ._ops import ops
6
+
7
+
8
+ # page attention ops
9
+ def paged_attention_v1(
10
+ out: torch.Tensor,
11
+ query: torch.Tensor,
12
+ key_cache: torch.Tensor,
13
+ value_cache: torch.Tensor,
14
+ num_kv_heads: int,
15
+ scale: float,
16
+ block_tables: torch.Tensor,
17
+ seq_lens: torch.Tensor,
18
+ block_size: int,
19
+ max_seq_len: int,
20
+ alibi_slopes: Optional[torch.Tensor],
21
+ kv_cache_dtype: str,
22
+ k_scale: float,
23
+ v_scale: float,
24
+ tp_rank: int = 0,
25
+ blocksparse_local_blocks: int = 0,
26
+ blocksparse_vert_stride: int = 0,
27
+ blocksparse_block_size: int = 64,
28
+ blocksparse_head_sliding_step: int = 0,
29
+ ) -> None:
30
+ ops.paged_attention_v1(
31
+ out,
32
+ query,
33
+ key_cache,
34
+ value_cache,
35
+ num_kv_heads,
36
+ scale,
37
+ block_tables,
38
+ seq_lens,
39
+ block_size,
40
+ max_seq_len,
41
+ alibi_slopes,
42
+ kv_cache_dtype,
43
+ k_scale,
44
+ v_scale,
45
+ tp_rank,
46
+ blocksparse_local_blocks,
47
+ blocksparse_vert_stride,
48
+ blocksparse_block_size,
49
+ blocksparse_head_sliding_step,
50
+ )
51
+
52
+
53
+ def paged_attention_v2(
54
+ out: torch.Tensor,
55
+ exp_sum: torch.Tensor,
56
+ max_logits: torch.Tensor,
57
+ tmp_out: torch.Tensor,
58
+ query: torch.Tensor,
59
+ key_cache: torch.Tensor,
60
+ value_cache: torch.Tensor,
61
+ num_kv_heads: int,
62
+ scale: float,
63
+ block_tables: torch.Tensor,
64
+ seq_lens: torch.Tensor,
65
+ block_size: int,
66
+ max_seq_len: int,
67
+ alibi_slopes: Optional[torch.Tensor],
68
+ kv_cache_dtype: str,
69
+ k_scale: float,
70
+ v_scale: float,
71
+ tp_rank: int = 0,
72
+ blocksparse_local_blocks: int = 0,
73
+ blocksparse_vert_stride: int = 0,
74
+ blocksparse_block_size: int = 64,
75
+ blocksparse_head_sliding_step: int = 0,
76
+ ) -> None:
77
+ ops.paged_attention_v2(
78
+ out,
79
+ exp_sum,
80
+ max_logits,
81
+ tmp_out,
82
+ query,
83
+ key_cache,
84
+ value_cache,
85
+ num_kv_heads,
86
+ scale,
87
+ block_tables,
88
+ seq_lens,
89
+ block_size,
90
+ max_seq_len,
91
+ alibi_slopes,
92
+ kv_cache_dtype,
93
+ k_scale,
94
+ v_scale,
95
+ tp_rank,
96
+ blocksparse_local_blocks,
97
+ blocksparse_vert_stride,
98
+ blocksparse_block_size,
99
+ blocksparse_head_sliding_step,
100
+ )
101
+
102
+
103
+ def reshape_and_cache(
104
+ key: torch.Tensor,
105
+ value: torch.Tensor,
106
+ key_cache: torch.Tensor,
107
+ value_cache: torch.Tensor,
108
+ slot_mapping: torch.Tensor,
109
+ kv_cache_dtype: str,
110
+ k_scale: float,
111
+ v_scale: float,
112
+ ) -> None:
113
+ ops.reshape_and_cache(
114
+ key,
115
+ value,
116
+ key_cache,
117
+ value_cache,
118
+ slot_mapping,
119
+ kv_cache_dtype,
120
+ k_scale,
121
+ v_scale,
122
+ )
123
+
124
+
125
+ def reshape_and_cache_flash(
126
+ key: torch.Tensor,
127
+ value: torch.Tensor,
128
+ key_cache: torch.Tensor,
129
+ value_cache: torch.Tensor,
130
+ slot_mapping: torch.Tensor,
131
+ kv_cache_dtype: str,
132
+ k_scale: torch.Tensor,
133
+ v_scale: torch.Tensor,
134
+ ) -> None:
135
+ ops.reshape_and_cache_flash(
136
+ key,
137
+ value,
138
+ key_cache,
139
+ value_cache,
140
+ slot_mapping,
141
+ kv_cache_dtype,
142
+ k_scale,
143
+ v_scale,
144
+ )
145
+
146
+
147
+ def copy_blocks(
148
+ key_caches: List[torch.Tensor],
149
+ value_caches: List[torch.Tensor],
150
+ block_mapping: torch.Tensor,
151
+ ) -> None:
152
+ ops.copy_blocks(key_caches, value_caches, block_mapping)
153
+
154
+
155
+ def swap_blocks(
156
+ src: torch.Tensor, dst: torch.Tensor, block_mapping: torch.Tensor
157
+ ) -> None:
158
+ ops.swap_blocks(src, dst, block_mapping)
159
+
160
+
161
+ def convert_fp8(
162
+ output: torch.Tensor, input: torch.Tensor, scale: float = 1.0, kv_dtype: str = "fp8"
163
+ ) -> None:
164
+ ops.convert_fp8(output, input, scale, kv_dtype)
165
+
166
+
167
+ __all__ = [
168
+ "convert_fp8",
169
+ "paged_attention_v1",
170
+ "paged_attention_v2",
171
+ "reshape_and_cache",
172
+ "copy_blocks",
173
+ ]
build/torch213-cxx11-cu132-aarch64-linux/_ops.py ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ from . import _paged_attention_cuda_2e4b976
3
+ ops = torch.ops._paged_attention_cuda_2e4b976
4
+
5
+ def add_op_namespace_prefix(op_name: str):
6
+ """
7
+ Prefix op by namespace.
8
+ """
9
+ return f"_paged_attention_cuda_2e4b976::{op_name}"
build/torch213-cxx11-cu132-aarch64-linux/_paged_attention_cuda_2e4b976.abi3.so ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ oid sha256:5a9eb91e8e325a216aaf2b5a56eda28922d440fa3e4b5eb3c882858e9d12963e
3
+ size 89434632
build/torch213-cxx11-cu132-aarch64-linux/metadata.json ADDED
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+ "id": "_paged_attention_cuda_2e4b976",
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+ "version": 1,
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+ "license": "Apache-2.0",
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+ "python-depends": [],
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+ "backend": {
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+ "type": "cuda",
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+ "archs": [
10
+ "10.0",
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+ "11.0",
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+ "12.0",
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+ "12.1+PTX",
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+ "7.5",
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+ "8.9",
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+ ]
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+ "digest": {
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+ "files": {
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+ "__init__.py": "oes6jQj02wGGtnJVomIE7ZJr2qnJmOm6CWurue5Vf6w=",
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+ "platforms.py": "NeAhENqA8yXHgy3EfkYP1Bkx1n6aStkExV9py7Jvdiw="
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+ }
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+ }
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+ }
build/torch213-cxx11-cu132-aarch64-linux/metadata.json.sigstore ADDED
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build/torch213-cxx11-cu132-aarch64-linux/paged_attention/__init__.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import ctypes
2
+ import importlib.util
3
+ import sys
4
+ from pathlib import Path
5
+ from types import ModuleType
6
+
7
+
8
+ def _import_from_path(file_path: Path) -> ModuleType:
9
+ # We cannot use the module name as-is, after adding it to `sys.modules`,
10
+ # it would also be used for other imports. So, we make a module name that
11
+ # depends on the path for it to be unique using the hex-encoded hash of
12
+ # the path.
13
+ path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
14
+ module_name = path_hash
15
+ spec = importlib.util.spec_from_file_location(module_name, file_path)
16
+ if spec is None:
17
+ raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
18
+ module = importlib.util.module_from_spec(spec)
19
+ if module is None:
20
+ raise ImportError(f"Cannot load module {module_name} from spec")
21
+ sys.modules[module_name] = module
22
+ spec.loader.exec_module(module) # type: ignore
23
+ return module
24
+
25
+
26
+ globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))
build/torch213-cxx11-cu132-aarch64-linux/platforms.py ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import random
3
+ from abc import ABC, abstractmethod
4
+ from functools import lru_cache, wraps
5
+ from typing import Callable, ParamSpec, TypeVar
6
+
7
+ import numpy as np
8
+ import torch
9
+
10
+ IS_ROCM = torch.version.hip is not None
11
+ IS_MPS = torch.backends.mps.is_available()
12
+
13
+
14
+ class Platform(ABC):
15
+ @classmethod
16
+ def seed_everything(cls, seed: int) -> None:
17
+ """
18
+ Set the seed of each random module.
19
+ `torch.manual_seed` will set seed on all devices.
20
+
21
+ Loosely based on: https://github.com/Lightning-AI/pytorch-lightning/blob/2.4.0/src/lightning/fabric/utilities/seed.py#L20
22
+ """
23
+ random.seed(seed)
24
+ np.random.seed(seed)
25
+ torch.manual_seed(seed)
26
+
27
+ @abstractmethod
28
+ def get_device_name(self, device_id: int = 0) -> str: ...
29
+
30
+ @abstractmethod
31
+ def is_cuda(self) -> bool: ...
32
+
33
+ @abstractmethod
34
+ def is_rocm(self) -> bool: ...
35
+
36
+ @abstractmethod
37
+ def is_mps(self) -> bool: ...
38
+
39
+
40
+ class CudaPlatform(Platform):
41
+ @classmethod
42
+ @lru_cache(maxsize=8)
43
+ def get_device_name(cls, device_id: int = 0) -> str:
44
+ return torch.cuda.get_device_name(0)
45
+
46
+ def is_cuda(self) -> bool:
47
+ return True
48
+
49
+ def is_rocm(self) -> bool:
50
+ return False
51
+
52
+ def is_mps(self) -> bool:
53
+ return False
54
+
55
+
56
+ class RocmPlatform(Platform):
57
+ @classmethod
58
+ @lru_cache(maxsize=8)
59
+ def get_device_name(cls, device_id: int = 0) -> str:
60
+ return torch.cuda.get_device_name(device_id)
61
+
62
+ def is_cuda(self) -> bool:
63
+ return False
64
+
65
+ def is_rocm(self) -> bool:
66
+ return True
67
+
68
+ def is_mps(self) -> bool:
69
+ return False
70
+
71
+
72
+ class MpsPlatform(Platform):
73
+ @classmethod
74
+ @lru_cache(maxsize=8)
75
+ def get_device_name(cls, device_id: int = 0) -> str:
76
+ return torch.cuda.get_device_name(device_id)
77
+
78
+ def is_cuda(self) -> bool:
79
+ return False
80
+
81
+ def is_rocm(self) -> bool:
82
+ return False
83
+
84
+ def is_mps(self) -> bool:
85
+ return True
86
+
87
+ current_platform = (
88
+ RocmPlatform() if IS_ROCM else
89
+ MpsPlatform() if IS_MPS else
90
+ CudaPlatform() if torch.cuda.is_available() else
91
+ None
92
+ )