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[Pallas] Switch gather to jnp.take_along_axis (for JAX issue filing) #2061

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[Pallas] Switch gather to jnp.take_along_axis (for JAX issue filing) #2061

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35 changes: 6 additions & 29 deletions helion/_compiler/aten_lowering.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2513,12 +2513,11 @@ def codegen_gather(ctx: LoweringContext, node: Node) -> object:

@gather_lowering.register_codegen("pallas")
def codegen_gather_pallas(ctx: LoweringContext, node: Node) -> object:
"""Generate gather for Pallas using one_hot + multiply + sum.
"""Generate gather for Pallas using jnp.take_along_axis.

TPU Mosaic has limited lax.gather support, so we implement
gather(input, dim, index) as:
mask = one_hot(index.squeeze(dim), input.shape[dim], dtype=input.dtype)
result = sum(input * mask, axis=dim, keepdims=True)
This is the natural JAX equivalent of torch.gather but currently fails
on TPU Mosaic due to limited lax.gather lowering support.
See: https://github.com/jax-ml/jax/issues/XXXXX
"""
assert not node.kwargs, "gather does not support keyword arguments"
assert len(node.args) == 3, f"gather expects 3 arguments, got {len(node.args)}"
Expand Down Expand Up @@ -2551,35 +2550,13 @@ def codegen_gather_pallas(ctx: LoweringContext, node: Node) -> object:
index_ast = _env_arg(ctx, index_node)
assert isinstance(index_ast, ast.AST)

idx_var = fn.new_var("gather_idx")
mask_var = fn.new_var("gather_mask")
result_var = fn.new_var("gather_result")

ctx.cg.add_statement(
statement_from_string(
f"{idx_var} = jnp.squeeze({{index}}.astype(jnp.int32), axis={dim})",
index=index_ast,
)
)

ctx.cg.add_statement(
statement_from_string(
f"{mask_var} = jax.nn.one_hot({idx_var}, {{input}}.shape[{dim}], dtype={{input}}.dtype)",
input=input_ast,
)
)

if dim != ndim - 1:
ctx.cg.add_statement(
statement_from_string(
f"{mask_var} = jnp.moveaxis({mask_var}, -1, {dim})",
)
)

ctx.cg.add_statement(
statement_from_string(
f"{result_var} = jnp.sum({{input}} * {mask_var}, axis={dim}, keepdims=True)",
f"{result_var} = jnp.take_along_axis({{input}}, {{index}}.astype(jnp.int32), axis={dim})",
input=input_ast,
index=index_ast,
)
)

Expand Down
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