Update pytorch-metadata.json

lutzroeder · lutzroeder · commit eedae23ed304 · 2025-04-13T02:27:02.000-07:00
diff --git a/source/pytorch-metadata.json b/source/pytorch-metadata.json
@@ -435,6 +435,9 @@
   {
     "name": "_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"
   },
+  {
+    "name": "aqlm::code2x8_lut_matmat.out(Tensor input, Tensor codes, Tensor codebooks, Tensor scales, Tensor? bias, Tensor(a!) out) -> Tensor(a!)"
+  },
   {
     "name": "aten::Bool.Tensor(Tensor a) -> bool"
   },
@@ -2562,7 +2565,8 @@
     "category": "Transform"
   },
   {
-    "name": "aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)"
+    "name": "aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)",
+    "category": "Transform"
   },
   {
     "name": "aten::embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False) -> (Tensor, Tensor, Tensor, Tensor)",
@@ -3115,7 +3119,8 @@
     "category": "Activation"
   },
   {
-    "name": "aten::gelu.out(Tensor self, *, str approximate=\"none\", Tensor(a!) out) -> Tensor(a!)"
+    "name": "aten::gelu.out(Tensor self, *, str approximate=\"none\", Tensor(a!) out) -> Tensor(a!)",
+    "category": "Activation"
   },
   {
     "name": "aten::gelu_(Tensor(a!) self, *, str approximate=\"none\") -> Tensor(a!)",
@@ -4518,7 +4523,8 @@
     "category": "Normalization"
   },
   {
-    "name": "aten::native_layer_norm.out(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"
+    "name": "aten::native_layer_norm.out(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))",
+    "category": "Normalization"
   },
   {
     "name": "aten::ne.Tensor(Tensor self, Tensor other) -> Tensor"
@@ -5843,10 +5849,12 @@
     "category": "Tensor"
   },
   {
-    "name": "aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]"
+    "name": "aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]",
+    "category": "Tensor"
   },
   {
-    "name": "aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()"
+    "name": "aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()",
+    "category": "Tensor"
   },
   {
     "name": "aten::splitlines(str self, bool keepends=False) -> str[]"
diff --git a/tools/pytorch_script.py b/tools/pytorch_script.py
@@ -65,6 +65,7 @@ def _write_metadata(metadata):
     'aten::randint_like.generator_out(Tensor self, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)', # noqa E501
     'aten::randint_like.generator_with_low_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor', # noqa E501
     'aten::randint_like.generator_with_low_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)', # noqa E501
+    'aqlm::code2x8_lut_matmat.out(Tensor input, Tensor codes, Tensor codebooks, Tensor scales, Tensor? bias, Tensor(a!) out) -> Tensor(a!)', # noqa E501
     'detectron2::nms_rotated(Tensor boxes, Tensor scores, float iou_threshold) -> Tensor', # noqa E501
     'detectron2::roi_align_rotated_forward(Tensor input, Tensor rois, float spatial_scale, int pooled_height, int pooled_width, int sampling_ratio) -> Tensor', # noqa E501
     'dim_order_ops::_empty_dim_order.out(int[] size, *, int[]? dim_order=None, Tensor(a!) out) -> Tensor(a!)', # noqa E501

Original file line number	Diff line number	Diff line change
`@@ -435,6 +435,9 @@`
`435`	`435`	`{`
`436`	`436`	`"name": "_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"`
`437`	`437`	`},`
	`438`	`+ {`
	`439`	`+ "name": "aqlm::code2x8_lut_matmat.out(Tensor input, Tensor codes, Tensor codebooks, Tensor scales, Tensor? bias, Tensor(a!) out) -> Tensor(a!)"`
	`440`	`+ },`
`438`	`441`	`{`
`439`	`442`	`"name": "aten::Bool.Tensor(Tensor a) -> bool"`
`440`	`443`	`},`
`@@ -2562,7 +2565,8 @@`
`2562`	`2565`	`"category": "Transform"`
`2563`	`2566`	`},`
`2564`	`2567`	`{`
`2565`		`- "name": "aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)"`
	`2568`	`+ "name": "aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)",`
	`2569`	`+ "category": "Transform"`
`2566`	`2570`	`},`
`2567`	`2571`	`{`
`2568`	`2572`	`"name": "aten::embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False) -> (Tensor, Tensor, Tensor, Tensor)",`
`@@ -3115,7 +3119,8 @@`
`3115`	`3119`	`"category": "Activation"`
`3116`	`3120`	`},`
`3117`	`3121`	`{`
`3118`		`- "name": "aten::gelu.out(Tensor self, *, str approximate=\"none\", Tensor(a!) out) -> Tensor(a!)"`
	`3122`	`+ "name": "aten::gelu.out(Tensor self, *, str approximate=\"none\", Tensor(a!) out) -> Tensor(a!)",`
	`3123`	`+ "category": "Activation"`
`3119`	`3124`	`},`
`3120`	`3125`	`{`
`3121`	`3126`	`"name": "aten::gelu_(Tensor(a!) self, *, str approximate=\"none\") -> Tensor(a!)",`
`@@ -4518,7 +4523,8 @@`
`4518`	`4523`	`"category": "Normalization"`
`4519`	`4524`	`},`
`4520`	`4525`	`{`
`4521`		`- "name": "aten::native_layer_norm.out(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"`
	`4526`	`+ "name": "aten::native_layer_norm.out(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))",`
	`4527`	`+ "category": "Normalization"`
`4522`	`4528`	`},`
`4523`	`4529`	`{`
`4524`	`4530`	`"name": "aten::ne.Tensor(Tensor self, Tensor other) -> Tensor"`
`@@ -5843,10 +5849,12 @@`
`5843`	`5849`	`"category": "Tensor"`
`5844`	`5850`	`},`
`5845`	`5851`	`{`
`5846`		`- "name": "aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]"`
	`5852`	`+ "name": "aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]",`
	`5853`	`+ "category": "Tensor"`
`5847`	`5854`	`},`
`5848`	`5855`	`{`
`5849`		`- "name": "aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()"`
	`5856`	`+ "name": "aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()",`
	`5857`	`+ "category": "Tensor"`
`5850`	`5858`	`},`
`5851`	`5859`	`{`
`5852`	`5860`	`"name": "aten::splitlines(str self, bool keepends=False) -> str[]"`