Removed the code path for ttir being an ir.Module

This was only necessary when Pallas GPU was using `jax_triton` for lowering.

PiperOrigin-RevId: 675675608

jax_triton/triton_lib.py

@@ -14,9 +14,9 @@
 
 """Module for calling Triton kernels from JAX."""
 
-# b/301982023
 from __future__ import annotations
 
+from collections.abc import Callable, Sequence
 import copy
 import dataclasses
 import functools
@@ -26,9 +26,7 @@
 import tempfile
 import types
 from typing import Any, Protocol, Union
-from collections.abc import Callable, Sequence
 import zlib
-from functools import partial
 
 from absl import logging
 import jax
@@ -44,6 +42,7 @@
 import jax.numpy as jnp
 import numpy as np
 
+
 CAN_USE_TRITON = False
 try:
   import triton
@@ -226,19 +225,6 @@ def compile_ttir_to_ptx_inplace(
 ) -> CompilationResult:
   if cuda_options.debug:
     print(ttir)
-  if isinstance(ttir, ir.Module):
-    context = _triton.ir.context()
-    _triton.ir.load_dialects(context)
-    cuda_backend.load_dialects(context)
-
-    # Triton compilation APIs only accept Triton-specific MLIR wrappers.
-    # So, here we serialize an ir.Module to a file and then deserialize
-    # it as a tl_ir.module.
-    with tempfile.NamedTemporaryFile(mode="wb") as f:
-      ttir.operation.write_bytecode(f)
-      f.flush()
-      ttir = tl_ir.parse_mlir_module(f.name, context)
-    ttir.context = context
   try:
     metadata = {}
     opt_ttir = cuda_backend.make_ttir(ttir, metadata, cuda_options)
@@ -295,19 +281,6 @@ def compile_ttir_to_hsaco_inplace(
 ) -> CompilationResult:
   if hip_options.debug:
     print(ttir)
-  if isinstance(ttir, ir.Module):
-    context = _triton.ir.context()
-    _triton.ir.load_dialects(context)
-    hip_backend.load_dialects(context)
-
-    # Triton compilation APIs only accept Triton-specific MLIR wrappers.
-    # So, here we serialize an ir.Module to a file and then deserialize
-    # it as a tl_ir.module.
-    with tempfile.NamedTemporaryFile(mode="wb") as f:
-      ttir.operation.write_bytecode(f)
-      f.flush()
-      ttir = tl_ir.parse_mlir_module(f.name, context)
-    ttir.context = context
   try:
     metadata = {}
     opt_ttir = hip_backend.make_ttir(ttir, metadata, hip_options)
@@ -554,7 +527,6 @@ def triton_kernel_call_lowering(
         "`input_output_aliases` only supported on `jaxlib>=0.3.22"
     )
 
-
   kernel_call_name = name
   args = list(ctx.avals_in)
   arg_dtypes = list(map(get_triton_type, ctx.avals_in))
@@ -720,13 +692,17 @@ def prune_configs(configs, named_args, **kwargs):
       operand_output_aliases=dict(input_output_aliases),
   ).results
 
-mlir.register_lowering(triton_kernel_call_p,
-                       partial(triton_kernel_call_lowering, get_cuda_backend),
-                       platform='cuda')
+mlir.register_lowering(
+    triton_kernel_call_p,
+    functools.partial(triton_kernel_call_lowering, get_cuda_backend),
+    platform="cuda",
+)
 
-mlir.register_lowering(triton_kernel_call_p,
-                       partial(triton_kernel_call_lowering, get_hip_backend),
-                       platform='rocm')
+mlir.register_lowering(
+    triton_kernel_call_p,
+    functools.partial(triton_kernel_call_lowering, get_hip_backend),
+    platform="rocm",
+)
 
 class ShapeDtype(Protocol):