removing duplicate KV cache instance.

changing config paths.

Author: NicoGrande

src/MaxText/__init__.py

@@ -34,7 +34,6 @@
 from maxtext.trainers.post_train.dpo import dpo_utils
 from maxtext.utils import maxtext_utils
 from maxtext.utils import model_creation_utils
-from maxtext.utils.model_creation_utils import from_config
 
 Transformer = models.Transformer
 transformer_as_linen = models.transformer_as_linen

src/MaxText/integration/vllm/maxtext_vllm_adapter/adapter.py

@@ -23,7 +23,7 @@
 from jax.sharding import Mesh
 from MaxText import pyconfig
 from MaxText.common_types import MODEL_MODE_AUTOREGRESSIVE
-from MaxText.globals import MAXTEXT_PKG_DIR
+from MaxText.globals import MAXTEXT_CONFIGS_DIR
 from maxtext.utils import max_logging
 from maxtext.utils import model_creation_utils
 
@@ -73,7 +73,7 @@ def generate_maxtext_config(vllm_config: VllmConfig) -> pyconfig.HyperParameters
     raise ValueError("hf_config_path must be provided when using MaxTextForCausalLM.")
 
   # Add base config path to positional args
-  base_config_path = os.path.join(MAXTEXT_PKG_DIR, "configs", "vllm.yml")
+  base_config_path = os.path.join(MAXTEXT_CONFIGS_DIR, "inference", "vllm.yml")
   argv_list = ["", str(base_config_path)]
 
   maxtext_config = pyconfig.initialize(argv_list, **overrides)
@@ -151,7 +151,7 @@ def __call__(
 
     with self.mesh, nn.logical_axis_rules(self.maxtext_config.logical_axis_rules):
       aux_hidden_states = []
-      hidden, updated_kv_caches = self.model(
+      hidden, kv_caches = self.model(
           decoder_input_tokens=input_ids,
           decoder_positions=input_positions,
           kv_caches=kv_caches,
@@ -163,7 +163,7 @@ def __call__(
       # To be compatible with vLLM, we reshape to (batch * seq, dim).
       hidden = hidden.reshape((-1, hidden.shape[-1]))
 
-    return updated_kv_caches, hidden, aux_hidden_states
+    return kv_caches, hidden, aux_hidden_states
 
   def forward(self, *args, **kwargs):
     """Alias for __call__ for compatibility.

src/MaxText/rl/train_rl.py

@@ -73,7 +73,7 @@
 os.environ["SKIP_JAX_PRECOMPILE"] = "1"
 
 from MaxText import pyconfig
-from MaxText.globals import MAXTEXT_PKG_DIR
+from MaxText.globals import MAXTEXT_CONFIGS_DIR
 from MaxText.integration.tunix.tunix_adapter import TunixMaxTextAdapter
 from MaxText.rl.evaluate_rl import evaluate
 from MaxText.rl import utils_rl
@@ -370,7 +370,6 @@ def rl_train(trainer_config, sampler_config, trainer_devices, sampler_devices):
     max_logging.log("Creating policy model with same config as reference model on trainer mesh")
     actor_model, actor_mesh = get_maxtext_model(trainer_config, trainer_devices)
 
-
   if trainer_config.debug.rl:
     max_logging.log("Policy Model initialized successfully")
     nnx.display(actor_model)
@@ -495,8 +494,7 @@ def rl_train(trainer_config, sampler_config, trainer_devices, sampler_devices):
           "enable_tunix_perf_metrics is True but tunix.perf modules are not available, skipping Tunix-managed metrics."
       )
 
-  configs_dir = os.environ.get("MAXTEXT_CONFIGS_DIR", os.path.join(MAXTEXT_PKG_DIR, "configs"))
-  vllm_config_path = epath.Path(configs_dir) / "vllm.yml"
+  vllm_config_path = os.path.join(MAXTEXT_CONFIGS_DIR, "inference", "vllm.yml")
   argv_list = ["", str(vllm_config_path), "log_config=False"]
   vllm_config = pyconfig.initialize(argv_list)
 

src/maxtext/configs/vllm.yml src/maxtext/configs/inference/vllm.ymlsrc/maxtext/configs/vllm.yml renamed to src/maxtext/configs/inference/vllm.yml

@@ -47,7 +47,7 @@
 from maxtext.utils import model_creation_utils
 from MaxText import pyconfig
 from MaxText.common_types import Config
-from MaxText.globals import MAXTEXT_PKG_DIR
+from MaxText.globals import MAXTEXT_CONFIGS_DIR
 from MaxText.integration.tunix.tunix_adapter import TunixMaxTextAdapter
 from tunix.rl.rollout import base_rollout
 from tunix.rl.rollout.vllm_rollout import VllmRollout
@@ -185,7 +185,7 @@ def decode_with_vllm(
       f"and EP={ici_expert_parallelism if enable_expert_parallel else 0}..."
   )
 
-  vllm_config_path = os.path.join(MAXTEXT_PKG_DIR, "configs", "vllm.yml")
+  vllm_config_path = os.path.join(MAXTEXT_CONFIGS_DIR, "inference", "vllm.yml")
   argv_list = ["", str(vllm_config_path), "log_config=False"]
   vllm_config = pyconfig.initialize(argv_list)
 

src/maxtext/vllm_decode.py

@@ -31,14 +31,14 @@
 
 from flax.linen import partitioning as nn_partitioning
 
-import MaxText as mt
 from MaxText import pyconfig
 from MaxText.train import get_first_step
 from MaxText.layers import models
 from maxtext.common import checkpointing
 from maxtext.utils import max_logging
 from maxtext.utils import maxtext_utils
 from maxtext.utils import train_utils
+from maxtext.utils.model_creation_utils import from_config
 
 Transformer = models.transformer_as_linen
 
@@ -52,7 +52,7 @@ def checkpoint_loop(config, state=None):
     ckpt_path:
   Returns:
   """
-  model = mt.from_config(config)
+  model = from_config(config)
   mesh = model.mesh
   init_rng, checkpoint_manager, _, tx = train_utils.create_training_tools(config, model, mesh)