[Inductor][CuTeDSL] Move load_template up two directories

Summary:
This is a reland of D84527470

Moves the function used to load CuTeDSL Jinja templates up one level out of the flex attention folder. This way it can be used for more generate Inductor templates in the future.

Test Plan: INDUCTOR_TEST_DISABLE_FRESH_CACHE=1 TORCHINDUCTOR_CACHE_DIR=~/cutetest buck2 run mode/opt //caffe2/test/inductor:cutedsl_grouped_mm -c fbcode.nvcc_arch=b200a -c fbcode.enable_gpu_sections=true -c fbcode.platform010_cuda_version=12.8

Differential Revision: D85013024

torch/_inductor/kernel/flex/common.py

@@ -3,6 +3,7 @@
 
 import math
 from collections.abc import Sequence
+from functools import partial
 from pathlib import Path
 from typing import Any, Optional, Union
 
@@ -36,6 +37,7 @@ from ...lowering import (
     to_dtype,
 )
 from ...select_algorithm import realize_inputs
+from ...utils import load_template
 
 
 SubgraphResults = Union[list[Optional[ComputedBuffer]], Optional[ComputedBuffer]]
@@ -337,13 +339,8 @@ def next_power_of_two(n):
     return 2 ** math.ceil(math.log2(n))
 
 
-_TEMPLATE_DIR = Path(__file__).parent / "templates"
-
-
-def load_template(name: str) -> str:
-    """Load a template file and return its content."""
-    with open(_TEMPLATE_DIR / f"{name}.py.jinja") as f:
-        return f.read()
+_FLEX_TEMPLATE_DIR = Path(__file__).parent / "templates"
+load_flex_template = partial(load_template, template_dir=_FLEX_TEMPLATE_DIR)
 
 
 # Template strings have been moved to templates/common.py.jinja

torch/_inductor/kernel/flex/flex_attention.py

@@ -29,7 +29,7 @@ from .common import (
     freeze_irnodes,
     get_fwd_subgraph_outputs,
     infer_dense_strides,
-    load_template,
+    load_flex_template,
     maybe_realize,
     set_head_dim_values,
     SubgraphResults,
@@ -79,9 +79,9 @@ def get_float32_precision():
 flex_attention_template = TritonTemplate(
     name="flex_attention",
     grid=flex_attention_grid,
-    source=load_template("flex_attention")
-    + load_template("utilities")
-    + load_template("common"),
+    source=load_flex_template("flex_attention")
+    + load_flex_template("utilities")
+    + load_flex_template("common"),
 )
 
 
@@ -464,7 +464,7 @@ def flex_attention_backward_grid(
 flex_attention_backward_template = TritonTemplate(
     name="flex_attention_backward",
     grid=flex_attention_backward_grid,
-    source=load_template("flex_backwards") + load_template("utilities"),
+    source=load_flex_template("flex_backwards") + load_flex_template("utilities"),
 )
 
 

torch/_inductor/kernel/flex/flex_decoding.py

@@ -22,7 +22,7 @@ from .common import (
     create_num_blocks_fake_generator,
     freeze_irnodes,
     get_fwd_subgraph_outputs,
-    load_template,
+    load_flex_template,
     maybe_realize,
     set_head_dim_values,
 )
@@ -97,9 +97,9 @@ def flex_decoding_grid(batch_size, kv_heads, gqa_group_size, n_keys, d_model, me
 flex_decoding_template = TritonTemplate(
     name="flex_decoding",
     grid=flex_decoding_grid,
-    source=load_template("flex_decode")
-    + load_template("utilities")
-    + load_template("common"),
+    source=load_flex_template("flex_decode")
+    + load_flex_template("utilities")
+    + load_flex_template("common"),
 )
 
 

torch/_inductor/kernel/flex/flex_flash_attention.py

@@ -12,7 +12,7 @@ from torch.fx import GraphModule
 
 from ...ir import FixedLayout, ShapeAsConstantBuffer, Subgraph, TensorBox
 from ...lowering import empty_strided
-from .common import infer_dense_strides, load_template, SubgraphResults
+from .common import infer_dense_strides, load_flex_template, SubgraphResults
 
 
 aten = torch.ops.aten
@@ -36,7 +36,7 @@ from ...codegen.cutedsl.cutedsl_template import CuteDSLTemplate
 
 
 flash_attention_cutedsl_template = CuteDSLTemplate(
-    name="flash_attention_cutedsl", source=load_template("flash_attention")
+    name="flash_attention_cutedsl", source=load_flex_template("flash_attention")
 )
 
 

torch/_inductor/utils.py

@@ -67,6 +67,9 @@ from torch.utils._ordered_set import OrderedSet
 from torch.utils._pytree import tree_flatten, tree_map_only
 
 
+if TYPE_CHECKING:
+    from pathlib import Path
+
 OPTIMUS_EXCLUDE_POST_GRAD = [
     "activation_quantization_aten_pass",
     "inductor_autotune_lookup_table",
@@ -3885,3 +3888,10 @@ def is_nonfreeable_buffers(dep: Dep) -> bool:
     return dep_name.startswith(
         ("primals_", "arg", "fwd_rng_state", "bwd_rng_state", "tangents")
     )
+
+
+# Make sure to also include your jinja templates within torch_package_data in setup.py, or this function won't be able to find them
+def load_template(name: str, template_dir: Path) -> str:
+    """Load a template file and return its content."""
+    with open(template_dir / f"{name}.py.jinja") as f:
+        return f.read()