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kernels-bot commited on 18 days ago

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.gitattributes +2 -0
build/torch210-metal-aarch64-darwin/{_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so → _mlx_quantization_metal_kernels_metal_86f75d9.abi3.so} +2 -2
build/torch210-metal-aarch64-darwin/_ops.py +3 -3
build/torch210-metal-aarch64-darwin/metadata.json +8 -2
build/torch210-metal-aarch64-darwin/mlx_quantization_metal_kernels/__init__.py +2 -2
build/{torch28-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/__init__.py +0 -0
build/{torch28-metal-aarch64-darwin/_mlx_quantization_metal_kernels_33fa8c7.abi3.so → torch211-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_86f75d9.abi3.so} +2 -2
build/{torch29-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/_ops.py +3 -3
build/torch211-metal-aarch64-darwin/metadata.json +10 -0
build/{torch28-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/mlx_quantization_metal_kernels/__init__.py +2 -2
build/torch28-metal-aarch64-darwin/_ops.py +0 -9
build/torch28-metal-aarch64-darwin/metadata.json +0 -3
build/torch29-metal-aarch64-darwin/__init__.py +0 -162
build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so +0 -3
build/torch29-metal-aarch64-darwin/metadata.json +0 -4
build/torch29-metal-aarch64-darwin/mlx_quantization_metal_kernels/__init__.py +0 -26

.gitattributes CHANGED Viewed

@@ -38,3 +38,5 @@ build/torch28-metal-aarch64-darwin/_mlx_quantization_metal_kernels_33fa8c7.abi3.
 build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_33fa8c7.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch210-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so filter=lfs diff=lfs merge=lfs -text

 build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_33fa8c7.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch210-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_86f75d9.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch211-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_86f75d9.abi3.so filter=lfs diff=lfs merge=lfs -text

build/torch210-metal-aarch64-darwin/{_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so → _mlx_quantization_metal_kernels_metal_86f75d9.abi3.so} RENAMED Viewed

@@ -1,3 +1,3 @@
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-oid sha256:4f3cd1fc44fc6b52d4ec5bc275cd8ebbc17bc247256ff0063cf0dc70a7f0e57b
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+oid sha256:cf762ec1255ee6555cb163b30c6bfa6abef2425c04982f908aba65899b4d2f5f
+size 40010744

build/torch210-metal-aarch64-darwin/_ops.py CHANGED Viewed

@@ -1,9 +1,9 @@
 import torch
-from . import _mlx_quantization_metal_kernels_metal_0aaded7
-ops = torch.ops._mlx_quantization_metal_kernels_metal_0aaded7
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_mlx_quantization_metal_kernels_metal_0aaded7::{op_name}"

 import torch
+from . import _mlx_quantization_metal_kernels_metal_86f75d9
+ops = torch.ops._mlx_quantization_metal_kernels_metal_86f75d9
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
+    return f"_mlx_quantization_metal_kernels_metal_86f75d9::{op_name}"

build/torch210-metal-aarch64-darwin/metadata.json CHANGED Viewed

@@ -1,4 +1,10 @@
 {
   "license": "MIT",
-  "python-depends": []
-}

 {
+  "name": "mlx-quantization-metal-kernels",
+  "id": "_mlx_quantization_metal_kernels_metal_86f75d9",
+  "version": 1,
   "license": "MIT",
+  "python-depends": [],
+  "backend": {
+    "type": "metal"
+  }
+}

build/torch210-metal-aarch64-darwin/mlx_quantization_metal_kernels/__init__.py CHANGED Viewed

@@ -1,10 +1,10 @@
 import ctypes
 import sys
-import importlib
 from pathlib import Path
 from types import ModuleType
 def _import_from_path(file_path: Path) -> ModuleType:
     # We cannot use the module name as-is, after adding it to `sys.modules`,
     # it would also be used for other imports. So, we make a module name that

 import ctypes
+import importlib.util
 import sys
 from pathlib import Path
 from types import ModuleType
 def _import_from_path(file_path: Path) -> ModuleType:
     # We cannot use the module name as-is, after adding it to `sys.modules`,
     # it would also be used for other imports. So, we make a module name that

build/{torch28-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/__init__.py RENAMED Viewed

File without changes

build/{torch28-metal-aarch64-darwin/_mlx_quantization_metal_kernels_33fa8c7.abi3.so → torch211-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_86f75d9.abi3.so} RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 40042432

 version https://git-lfs.github.com/spec/v1
+oid sha256:c0bab012de037b761f8ecac05f87c017c1aa32bf7a09187164c4193e77237222
+size 40010744

build/{torch29-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/_ops.py RENAMED Viewed

@@ -1,9 +1,9 @@
 import torch
-from . import _mlx_quantization_metal_kernels_metal_0aaded7
-ops = torch.ops._mlx_quantization_metal_kernels_metal_0aaded7
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_mlx_quantization_metal_kernels_metal_0aaded7::{op_name}"

 import torch
+from . import _mlx_quantization_metal_kernels_metal_86f75d9
+ops = torch.ops._mlx_quantization_metal_kernels_metal_86f75d9
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
+    return f"_mlx_quantization_metal_kernels_metal_86f75d9::{op_name}"

build/torch211-metal-aarch64-darwin/metadata.json ADDED Viewed

	@@ -0,0 +1,10 @@

+{
+  "name": "mlx-quantization-metal-kernels",
+  "id": "_mlx_quantization_metal_kernels_metal_86f75d9",
+  "version": 1,
+  "license": "MIT",
+  "python-depends": [],
+  "backend": {
+    "type": "metal"
+  }
+}

build/{torch28-metal-aarch64-darwin → torch211-metal-aarch64-darwin}/mlx_quantization_metal_kernels/__init__.py RENAMED Viewed

@@ -1,10 +1,10 @@
 import ctypes
 import sys
-import importlib
 from pathlib import Path
 from types import ModuleType
 def _import_from_path(file_path: Path) -> ModuleType:
     # We cannot use the module name as-is, after adding it to `sys.modules`,
     # it would also be used for other imports. So, we make a module name that

 import ctypes
+import importlib.util
 import sys
 from pathlib import Path
 from types import ModuleType
 def _import_from_path(file_path: Path) -> ModuleType:
     # We cannot use the module name as-is, after adding it to `sys.modules`,
     # it would also be used for other imports. So, we make a module name that

build/torch28-metal-aarch64-darwin/_ops.py DELETED Viewed

@@ -1,9 +0,0 @@
-import torch
-from . import _mlx_quantization_metal_kernels_33fa8c7
-ops = torch.ops._mlx_quantization_metal_kernels_33fa8c7
-def add_op_namespace_prefix(op_name: str):
-    """
-    Prefix op by namespace.
-    """
-    return f"_mlx_quantization_metal_kernels_33fa8c7::{op_name}"

build/torch28-metal-aarch64-darwin/metadata.json DELETED Viewed

@@ -1,3 +0,0 @@
-{
-  "python-depends": []
-}

build/torch29-metal-aarch64-darwin/__init__.py DELETED Viewed

@@ -1,162 +0,0 @@
-from typing import Optional
-import torch
-from ._ops import ops
-# =============================================================================
-# FP-quantized (MXFP4) operations
-# =============================================================================
-def mxfp4_qmm_n(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    output_features: int,
-) -> torch.Tensor:
-    """Matrix-matrix multiply with MXFP4 quantized non-transposed weight.
-    Computes y = x @ dequantize(w, scales).
-    x: [..., M, K], w: [K_packed, N_packed] (uint32), y: [..., M, output_features]
-    """
-    return ops.mxfp4_qmm_n(x, w, scales, output_features)
-def mxfp4_qmv(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    output_features: int,
-) -> torch.Tensor:
-    """Matrix-vector multiply with MXFP4 quantized weight.
-    Computes y = dequantize(w, scales) @ x.
-    x: [..., K], w: [N, K_packed] (uint32), y: [..., output_features]
-    """
-    return ops.mxfp4_qmv(x, w, scales, output_features)
-# =============================================================================
-# Affine quantized operations (scales + biases)
-# =============================================================================
-def affine_qmv(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    output_features: int,
-    group_size: int = 128,
-    bits: int = 4,
-) -> torch.Tensor:
-    """Matrix-vector multiply with affine quantized weight.
-    x: [..., K], w: [N, K_packed], y: [..., output_features]
-    """
-    return ops.affine_qmv(x, w, scales, biases, group_size, bits, output_features)
-def affine_qmm_t(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    group_size: int = 128,
-    bits: int = 4,
-) -> torch.Tensor:
-    """Matrix-matrix multiply with affine quantized transposed weight.
-    Computes y = x @ dequantize(w, scales, biases).T
-    x: [..., M, K], w: [N, K_packed], y: [..., M, N]
-    N is inferred from w.size(0).
-    """
-    return ops.affine_qmm_t(x, w, scales, biases, group_size, bits)
-def affine_qmm_n(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    output_features: int,
-    group_size: int = 128,
-    bits: int = 4,
-) -> torch.Tensor:
-    """Matrix-matrix multiply with affine quantized non-transposed weight.
-    Computes y = x @ dequantize(w, scales, biases)
-    x: [..., M, K], w: [K_packed, N_packed], y: [..., M, output_features]
-    """
-    return ops.affine_qmm_n(x, w, scales, biases, group_size, bits, output_features)
-# =============================================================================
-# Affine quantized NAX operations (MetalPerformancePrimitives accelerated)
-# =============================================================================
-def affine_qmm_t_nax(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    group_size: int = 128,
-    bits: int = 4,
-) -> torch.Tensor:
-    """NAX-accelerated matrix-matrix multiply with transposed quantized weight.
-    x: [..., M, K], w: [N, K_packed], y: [..., M, N]
-    """
-    return ops.affine_qmm_t_nax(x, w, scales, biases, group_size, bits)
-def affine_qmm_n_nax(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    output_features: int,
-    group_size: int = 128,
-    bits: int = 4,
-) -> torch.Tensor:
-    """NAX-accelerated matrix-matrix multiply with non-transposed quantized weight.
-    x: [..., M, K], w: [K_packed, N_packed], y: [..., M, output_features]
-    """
-    return ops.affine_qmm_n_nax(x, w, scales, biases, group_size, bits, output_features)
-def affine_gather_qmm_rhs_nax(
-    x: torch.Tensor,
-    w: torch.Tensor,
-    scales: torch.Tensor,
-    biases: torch.Tensor,
-    indices: torch.Tensor,
-    output_features: int,
-    group_size: int = 128,
-    bits: int = 4,
-    transpose: bool = True,
-) -> torch.Tensor:
-    """NAX-accelerated gather + matrix-matrix multiply.
-    Gathers weight rows using indices, then computes matmul.
-    x: [M, K], w: [num_experts, ...], indices: [M], y: [M, output_features]
-    """
-    return ops.affine_gather_qmm_rhs_nax(
-        x, w, scales, biases, indices, group_size, bits, output_features, transpose
-    )
-__all__ = [
-    "mxfp4_qmm_n",
-    "mxfp4_qmv",
-    "affine_qmv",
-    "affine_qmm_t",
-    "affine_qmm_n",
-    "affine_qmm_t_nax",
-    "affine_qmm_n_nax",
-    "affine_gather_qmm_rhs_nax",
-]

build/torch29-metal-aarch64-darwin/_mlx_quantization_metal_kernels_metal_0aaded7.abi3.so DELETED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:df7ad3fa1ac77f9dc330bd7411b0168552dcaa25a5c6e91b61ed0b37c90b2a9f
-size 40042616

build/torch29-metal-aarch64-darwin/metadata.json DELETED Viewed

@@ -1,4 +0,0 @@
-{
-  "license": "MIT",
-  "python-depends": []
-}

build/torch29-metal-aarch64-darwin/mlx_quantization_metal_kernels/__init__.py DELETED Viewed

@@ -1,26 +0,0 @@
-import ctypes
-import sys
-import importlib
-from pathlib import Path
-from types import ModuleType
-def _import_from_path(file_path: Path) -> ModuleType:
-    # We cannot use the module name as-is, after adding it to `sys.modules`,
-    # it would also be used for other imports. So, we make a module name that
-    # depends on the path for it to be unique using the hex-encoded hash of
-    # the path.
-    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
-    module_name = path_hash
-    spec = importlib.util.spec_from_file_location(module_name, file_path)
-    if spec is None:
-        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
-    module = importlib.util.module_from_spec(spec)
-    if module is None:
-        raise ImportError(f"Cannot load module {module_name} from spec")
-    sys.modules[module_name] = module
-    spec.loader.exec_module(module)  # type: ignore
-    return module
-globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))