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[pallas] Do not use pl.{load,store} which will soon be removed from Pallas #66

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[pallas] Do not use pl.{load,store} which will soon be removed from Pallas #66

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16 changes: 8 additions & 8 deletions recml/core/ops/hstu_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -125,9 +125,9 @@ def _apply_mask(
masks = []
if mask_ref is not None:
if k_in_lanes:
mask = pl.load(mask_ref, (slice(None), k_slice))
mask = mask_ref[:, k_slice]
else:
mask = pl.load(mask_ref, (k_slice, slice(None)))
mask = mask_ref[k_slice, :]

snm = jnp.where(should_not_mask, 1, 0)
masks.append(jnp.bitwise_or(mask, jnp.broadcast_to(snm, mask.shape)) != 0)
Expand Down Expand Up @@ -156,7 +156,7 @@ def _apply_mask(
k_sequence = k_offset + jax.lax.broadcasted_iota(
jnp.int32, (k_slice.size, bq), 0
)
q_sequence = pl.load(q_sequence_ref, (pl.ds(1), slice(None))) # [1, bq]
q_sequence = q_sequence_ref[:1, :] # [1, bq]
q_sequence = jnp.broadcast_to(q_sequence, (k_slice.size, bq))

assert q_sequence.shape == k_sequence.shape
Expand All @@ -170,7 +170,7 @@ def _apply_mask(

if q_segment_ids_ref is not None:
if k_in_lanes:
kv_ids = pl.load(kv_segment_ids_ref, (pl.ds(1), k_slice)) # [1, k_slice]
kv_ids = kv_segment_ids_ref[:1, k_slice] # [1, k_slice]
repeats, rem = divmod(kv_ids.shape[1], NUM_LANES)
if rem:
raise NotImplementedError(f"block_kv must be a multiple of {NUM_LANES}")
Expand All @@ -181,9 +181,9 @@ def _apply_mask(
if rem:
raise NotImplementedError(f"block_q must be a multiple of {NUM_LANES}")
kv_ids = pltpu.repeat(
pl.load(kv_segment_ids_ref, (k_slice, slice(None))), repeats, axis=1
kv_segment_ids_ref[k_slice, :], repeats, axis=1
) # [k_slice, bq]
q_ids = pl.load(q_segment_ids_ref, (pl.ds(1), slice(None))) # [1, bq]
q_ids = q_segment_ids_ref[:1, :] # [1, bq]
masks.append(q_ids == kv_ids)

if masks:
Expand Down Expand Up @@ -228,7 +228,7 @@ def body(kv_compute_index, _):
slice_k = pl.ds(kv_compute_index * bkv_compute, bkv_compute)

q = q_ref[...]
k = pl.load(k_ref, (slice_k, slice(None)))
k = k_ref[slice_k, :]
qk = jax.lax.dot_general(
q, k, NT_DIM_NUMBERS, preferred_element_type=jnp.float32
)
Expand Down Expand Up @@ -256,7 +256,7 @@ def body(kv_compute_index, _):
)

sv_dims = NN_DIM_NUMBERS
v = pl.load(v_ref, (slice_k, slice(None)))
v = v_ref[slice_k, :]

to_float32 = lambda x: x.astype(jnp.float32)
v = to_float32(v)
Expand Down