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Fix LlamaRotaryEmbedding Tests [#520] #532

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Fix LlamaRotaryEmbedding Tests [#520] #532

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16 changes: 14 additions & 2 deletions benchmark/scripts/benchmark_rope.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,13 @@ def bench_speed_rope(input: SingleBenchmarkRunInput) -> SingleBenchmarkRunOutput
seq_len = extra_benchmark_config["seq_len"] if "seq_len" in extra_benchmark_config else input.x

head_dim = hidden_size // num_q_heads
rotary_emb = LlamaRotaryEmbedding(head_dim, device=device)

config = LlamaConfig(
max_position_embeddings=512,
head_dim=head_dim,
)

rotary_emb = LlamaRotaryEmbedding(config=config, device=device)
q = torch.randn(
(1, seq_len, num_q_heads, head_dim),
device=device,
Expand Down Expand Up @@ -105,7 +111,13 @@ def bench_memory_rope(input: SingleBenchmarkRunInput) -> SingleBenchmarkRunOutpu
seq_len = extra_benchmark_config["seq_len"] if "seq_len" in extra_benchmark_config else input.x

head_dim = hidden_size // num_q_heads
rotary_emb = LlamaRotaryEmbedding(head_dim, device=device)

config = LlamaConfig(
max_position_embeddings=512,
head_dim=head_dim,
)

rotary_emb = LlamaRotaryEmbedding(config=config, device=device)
q = torch.randn(
(1, seq_len, num_q_heads, head_dim),
device=device,
Expand Down
16 changes: 14 additions & 2 deletions test/transformers/test_rope.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
from test.utils import supports_bfloat16
from transformers.models.llama.modeling_llama import LlamaRotaryEmbedding
from transformers.models.llama.modeling_llama import apply_rotary_pos_emb
from transformers.models.llama.configuration_llama import LlamaConfig

from liger_kernel.ops.rope import LigerRopeFunction
from liger_kernel.transformers.functional import liger_rope
Expand Down Expand Up @@ -57,7 +58,13 @@ def test_correctness(
atol,
rtol,
):
rotary_emb = LlamaRotaryEmbedding(head_dim, device=device)

config = LlamaConfig(
max_position_embeddings=512,
head_dim=head_dim,
)

rotary_emb = LlamaRotaryEmbedding(config=config, device=device)

_tensor_q = torch.randn((bsz, seq_len, num_q_heads, head_dim), device=device).transpose(1, 2).to(dtype)

Expand Down Expand Up @@ -133,7 +140,12 @@ def test_functional_correctness(
k1 = _k.clone().requires_grad_(True)
k2 = _k.clone().requires_grad_(True)

rotary_emb = LlamaRotaryEmbedding(head_dim, device=device)
config = LlamaConfig(
max_position_embeddings=512,
head_dim=head_dim,
)

rotary_emb = LlamaRotaryEmbedding(config=config, device=device)

pos_ids = torch.arange(seq_len, device=device, dtype=torch.long).unsqueeze(0)
if expand_position_ids:
Expand Down