[sharktank] Update block_seq_stride for perplexity CI tests (#707)

- Update `block_seq_stride` for perplexity CI tests
- Update default value of `block_seq_stride` from `16` to `32` in
`export_paged_llm_v1.py`

.github/workflows/ci_eval.yaml

@@ -24,7 +24,7 @@ jobs:
   test_perplexity_iree:
     if: ${{ github.repository_owner == 'nod-ai' || github.event_name != 'schedule' }}
     timeout-minutes: 1000
-    name: "Perplexity-IREE"
+    name: "IREE Perplexity"
     strategy:
       matrix:
         version: [3.11]
@@ -83,7 +83,7 @@ jobs:
   test_perplexity_torch:
     if: ${{ github.repository_owner == 'nod-ai' || github.event_name != 'schedule' }}
     timeout-minutes: 1000
-    name: "Perplexity-Torch"
+    name: "Torch Perplexity"
     strategy:
       matrix:
         version: [3.11]

.github/workflows/ci_eval_short.yaml

@@ -23,7 +23,7 @@ concurrency:
 
 jobs:
   test_perplexity_iree:
-    name: "Llama3.1 8B FP16"
+    name: "IREE Perplexity"
     strategy:
       matrix:
         version: [3.11]

app_tests/integration_tests/llm/utils.py

@@ -90,6 +90,7 @@ def export_paged_llm_v1(mlir_path, config_path, model_path, batch_sizes):
             "python",
             "-m",
             "sharktank.examples.export_paged_llm_v1",
+            "--block-seq-stride=16",
             f"--{model_path.suffix.strip('.')}-file={model_path}",
             f"--output-mlir={mlir_path}",
             f"--output-config={config_path}",

sharktank/sharktank/evaluate/perplexity_iree.py

@@ -68,12 +68,14 @@ def __init__(
         kv_cache_type,
         tensor_parallelism_size,
         attention_kernel,
+        block_seq_stride,
     ):
         self.torch_device = torch_device
         self.iree_device = iree_device
         self.iree_hip_target = iree_hip_target
         self.iree_hal_target_backends = iree_hal_target_backends
         self.kv_cache_type = kv_cache_type
+        self.block_seq_stride = block_seq_stride
         self.activation_dtype = torch.float16
         self.attention_dtype = torch.float16
         self.tensor_parallelism_size = tensor_parallelism_size
@@ -136,6 +138,7 @@ def compile_model(self, weight_path_str):
             iree_hal_target_backends=self.iree_hal_target_backends,
             attention_kernel=self.attention_kernel,
             tensor_parallelism_size=self.tensor_parallelism_size,
+            block_seq_stride=self.block_seq_stride,
         )
         vmfb_path = export_artifacts.get_artifacts()
         return vmfb_path
@@ -145,7 +148,7 @@ def load_model(self, weight_path, tokenizer, vmfb_path):
 
         self.config = LlamaModelConfig(
             hp=configs.LlamaHParams.from_gguf_props(weight_path.properties),
-            block_seq_stride=16,
+            block_seq_stride=self.block_seq_stride,
             kv_cache_type=self.kv_cache_type,
             device=self.torch_device,
             activation_dtype=self.activation_dtype,
@@ -394,6 +397,7 @@ def run_perplexity(
     tensor_parallelism_size,
     attention_kernel,
     num_prompts,
+    block_seq_stride,
 ):
     start = time.time()
     perplexity = Perplexity(
@@ -404,6 +408,7 @@ def run_perplexity(
         kv_cache_type=kv_cache_type,
         tensor_parallelism_size=tensor_parallelism_size,
         attention_kernel=attention_kernel,
+        block_seq_stride=block_seq_stride,
     )
 
     perplexity.get_prompts(num_prompts=num_prompts)
@@ -425,8 +430,18 @@ def run_perplexity(
 
 def main(argv):
     parser = cli.create_parser()
-    parser.add_argument("--kv-cache-type", default="paged", help="KV cache type")
-    parser.add_argument("--torch-device", help="Torch device (or default)")
+    parser.add_argument(
+        "--attention-kernel",
+        type=str,
+        default="decomposed",
+        choices=["decomposed", "torch_sdpa"],
+    )
+    parser.add_argument(
+        "--block-seq-stride",
+        help="Block sequence stride for paged KV cache, must divide evenly into the context length",
+        type=int,
+        default=32,
+    )
     parser.add_argument("--iree-device", help="List an IREE device (e.g., 'hip://0')")
     parser.add_argument(
         "--iree-hip-target",
@@ -440,48 +455,42 @@ def main(argv):
         default="rocm",
         help="Specify the iree-hal target backends (e.g., rocm)",
     )
+    parser.add_argument("--kv-cache-type", default="paged", help="KV cache type")
     parser.add_argument(
-        "--attention-kernel",
-        type=str,
-        default="decomposed",
-        choices=["decomposed", "torch_sdpa"],
+        "--num-prompts",
+        type=int,
+        default=100,
+        help="Number of prompts for perplexity test (1 to 100)",
     )
     parser.add_argument(
         "--tensor-parallelism-size",
         type=int,
         default=1,
         help="Number of devices for tensor parallel sharding",
     )
-    parser.add_argument(
-        "--num-prompts",
-        type=int,
-        default=100,
-        help="Number of prompts for perplexity test",
-    )
+    parser.add_argument("--torch-device", help="Torch device (or default)")
 
     cli.add_tokenizer_options(parser)
     cli.add_input_dataset_options(parser)
     args = cli.parse(parser, args=argv)
 
     torch_device = torch.device(args.torch_device) if args.torch_device else None
-    iree_device = args.iree_device
-    kv_cache_type = args.kv_cache_type
     weight_path = cli.get_input_dataset(args)
     tokenizer = cli.get_tokenizer(args)
-    weight_path_str = str(args.irpa_file)
 
     ppl = run_perplexity(
         weight_path=weight_path,
-        weight_path_str=weight_path_str,
+        weight_path_str=str(args.irpa_file),
         tokenizer=tokenizer,
         torch_device=torch_device,
-        iree_device=iree_device,
+        iree_device=args.iree_device,
         iree_hip_target=args.iree_hip_target,
         iree_hal_target_backends=args.iree_hal_target_backends,
-        kv_cache_type=kv_cache_type,
+        kv_cache_type=args.kv_cache_type,
         tensor_parallelism_size=args.tensor_parallelism_size,
         attention_kernel=args.attention_kernel,
         num_prompts=args.num_prompts,
+        block_seq_stride=args.block_seq_stride,
     )
 
     logger.info(f"\n{json.dumps(ppl, indent=2)}")

sharktank/sharktank/examples/export_paged_llm_v1.py

@@ -49,7 +49,7 @@ def main():
         "--block-seq-stride",
         help="Block sequence stride for paged KV cache, must divide evenly into the context length",
         type=int,
-        default="16",
+        default=32,
     )
     parser.add_argument(
         "--verbose",

sharktank/sharktank/layers/configs/llm_configs.py

@@ -144,7 +144,7 @@ class LlamaModelConfig:
 
     # Block sequence stride for a paged KV cache. This must divide evenly
     # into the context length.
-    block_seq_stride: int = 16
+    block_seq_stride: int = 32
 
     # Either "paged" or "direct".
     kv_cache_type: str = "paged"

sharktank/sharktank/utils/export_artifacts.py

@@ -92,7 +92,7 @@ def __init__(
         iree_hal_target_backends: str,
         attention_kernel: str,
         tensor_parallelism_size: int,
-        block_seq_stride: Optional[int] = None,
+        block_seq_stride: int,
     ):
         self.sharktank_dir = str(
             Path(os.path.dirname(os.path.abspath(__file__))).parent.parent.parent
@@ -180,14 +180,13 @@ def export_to_mlir(
             f"--output-mlir={mlir_path}",
             f"--output-config={json_path}",
             f"--bs={str(self.batch_size)}",
+            f"--block-seq-stride={self.block_seq_stride}",
         ]
         if skip_decode:
             export_args.append("--skip-decode")
         if self.attention_kernel in ["decomposed", "torch"]:
             export_args.append("--attention-kernel")
             export_args.append(self.attention_kernel)
-        if self.block_seq_stride:
-            export_args.append(f"--block-seq-stride={self.block_seq_stride}")
 
         cwd = self.sharktank_dir
         cmd = subprocess.list2cmdline(export_args)