Make kv cache pos buffer name more specific

examples/models/llama/export_llama_lib.py

@@ -778,7 +778,7 @@ def _export_llama(args) -> LLMEdgeManager:  # noqa: C901
 
     additional_passes = []
     if args.model in TORCHTUNE_DEFINED_MODELS:
-        additional_passes = [InitializedMutableBufferPass(["cache_pos"])]
+        additional_passes = [InitializedMutableBufferPass(["kv_cache_pos"])]
     if args.generate_etrecord:
         if not builder_exported_to_edge.edge_manager:
             raise ValueError("Unable to generate etrecord due to missing edge manager.")

extension/llm/modules/attention.py

@@ -284,13 +284,13 @@ def calculate_kv(y):
 
         def true_fn(y):
             kv_cache = self.kv_cache.clone()
-            return kv_cache.k_cache, kv_cache.v_cache, kv_cache.cache_pos
+            return kv_cache.k_cache, kv_cache.v_cache, kv_cache.kv_cache_pos
 
         def false_fn(y):
             k, v = calculate_kv(y)
             kv_cache = self.kv_cache.clone()
             kv_cache.update(k, v)
-            return kv_cache.k_cache, kv_cache.v_cache, kv_cache.cache_pos
+            return kv_cache.k_cache, kv_cache.v_cache, kv_cache.kv_cache_pos
 
         # If kv cache is None, we expect y to be provided
         if self.kv_cache is None:
@@ -308,7 +308,7 @@ def false_fn(y):
             # Update key-value cache
             self.kv_cache.k_cache.copy_(k)
             self.kv_cache.v_cache.copy_(v)
-            self.kv_cache.cache_pos.copy_(cache_pos)
+            self.kv_cache.kv_cache_pos.copy_(cache_pos)
 
         output = self._sdpa(q, k, v, b, s_x, mask=mask)
         return self.output_proj(output)

extension/llm/modules/kv_cache.py

@@ -55,8 +55,11 @@ def __init__(
         self.register_buffer(
             "v_cache", torch.zeros(cache_shape, dtype=dtype), persistent=False
         )
+        # We use "kv_cache_pos" here instead of "cache_pos" since the latter is too generic, and we have
+        # a InitMutableBuferPass that needs to single out this buffer to initialize (and not others)
+        # since it takes up space in the pte file.
         self.register_buffer(
-            "cache_pos", torch.arange(0, self.max_seq_len), persistent=False
+            "kv_cache_pos", torch.arange(0, self.max_seq_len), persistent=False
         )
         self.batch_size = batch_size
 
@@ -105,17 +108,17 @@ def update(
                 f", but found new key tensors with batch size {k_val.shape[0]}!"
             )
 
-        assert (self.cache_pos[0] + seq_len) <= self.max_seq_len
+        assert (self.kv_cache_pos[0] + seq_len) <= self.max_seq_len
 
         k_out = self.k_cache
         v_out = self.v_cache
 
         if self.transpose_cache:
-            k_out[:, :, self.cache_pos[:seq_len]] = k_val
-            v_out[:, :, self.cache_pos[:seq_len]] = v_val
+            k_out[:, :, self.kv_cache_pos[:seq_len]] = k_val
+            v_out[:, :, self.kv_cache_pos[:seq_len]] = v_val
         else:
-            k_out[:, self.cache_pos[:seq_len]] = k_val
-            v_out[:, self.cache_pos[:seq_len]] = v_val
+            k_out[:, self.kv_cache_pos[:seq_len]] = k_val
+            v_out[:, self.kv_cache_pos[:seq_len]] = v_val
 
         # forward cache_pos seq_len positions along
         # cache_pos starts at (0, 1, 2, 3, 4, 5, ...)
@@ -124,7 +127,7 @@ def update(
         # this allows us to track the current position in the cache
         # after the last update in a compile-friendly way without any dynamism
         # e.g. relying on an int size tracker, or re-creating cache_pos every time
-        self.cache_pos.add_(seq_len)
+        self.kv_cache_pos.add_(seq_len)
 
         return k_out, v_out
 
@@ -144,5 +147,5 @@ def clone(self) -> "KVCache":
         )
         clone.k_cache.copy_(self.k_cache)
         clone.v_cache.copy_(self.v_cache)
-        clone.cache_pos.copy_(self.cache_pos)
+        clone.kv_cache_pos.copy_(self.kv_cache_pos)
         return clone

extension/llm/modules/test/test_attention.py

@@ -219,7 +219,7 @@ def test_attention_executorch(self):
             ),
         ).to_executorch(
             config=ExecutorchBackendConfig(
-                passes=[InitializedMutableBufferPass(["cache_pos"])],
+                passes=[InitializedMutableBufferPass(["kv_cache_pos"])],
             )
         )
 
@@ -330,7 +330,7 @@ def test_attention_torch_cond_executorch(self):
             ),
         ).to_executorch(
             config=ExecutorchBackendConfig(
-                passes=[InitializedMutableBufferPass(["cache_pos"])],
+                passes=[InitializedMutableBufferPass(["kv_cache_pos"])],
             )
         )
 

extension/llm/modules/test/test_kv_cache.py

@@ -174,7 +174,7 @@ def test_kv_cache_executorch(self):
             ),
         )
         et_config = ExecutorchBackendConfig(
-            passes=[InitializedMutableBufferPass(["cache_pos"])],
+            passes=[InitializedMutableBufferPass(["kv_cache_pos"])],
         )
         et_program = edge_program.to_executorch(config=et_config)
 
@@ -198,7 +198,7 @@ def test_kv_cache_executorch_from_file(self):
             ),
         )
         et_config = ExecutorchBackendConfig(
-            passes=[InitializedMutableBufferPass(["cache_pos"])],
+            passes=[InitializedMutableBufferPass(["kv_cache_pos"])],
         )
         et_program = edge_program.to_executorch(config=et_config)