Add Qwen SFT config and make necessary updates in tokenizer.py

apps/sft_v2/qwen3_8b.yaml

@@ -0,0 +1,63 @@
+# >>> python -m apps.sft_v2.main --config apps/sft_v2/qwen3_8b.yaml
+
+
+# TODO: required by torchtitan
+# https://github.com/pytorch/torchtitan/blob/2f1c814da071cc8ad165d00be6f9c1a66f8e1cce/torchtitan/distributed/utils.py#L265
+comm:
+  trace_buf_size: 0
+
+model_name: "Qwen/Qwen3-8B"
+
+model:
+  name: qwen3
+  flavor: 8B
+  hf_assets_path: hf://${model_name}
+
+processes:
+  procs: 8
+  with_gpus: true
+
+optimizer:
+  name: AdamW
+  lr: 1e-5
+  eps: 1e-8
+
+lr_scheduler:
+  warmup_steps: 200
+
+training:
+  local_batch_size: 1
+  seq_len: 2048
+  max_norm: 1.0
+  steps: 1000
+  compile: false
+  dataset: "c4"
+
+parallelism:
+  data_parallel_replicate_degree: 1
+  data_parallel_shard_degree: -1
+  tensor_parallel_degree: 1
+  pipeline_parallel_degree: 1
+  context_parallel_degree: 1
+  expert_parallel_degree: 1
+  disable_loss_parallel: false
+
+checkpoint:
+  enable: true
+  initial_load_path: hf://${model_name}
+  initial_load_in_hf: true
+  last_save_in_hf: true
+  interval: 500
+  async_mode: "disabled"
+
+activation_checkpoint:
+  mode: selective
+  selective_ac_option: op
+
+# profiling:
+#   enable_profiling: false
+
+# metrics:
+#   log_freq: 10
+#   enable_tensorboard: true
+#   save_tb_folder: "tb"

src/forge/data/tokenizer.py

@@ -5,7 +5,7 @@
 # LICENSE file in the root directory of this source tree.
 
 import json
-from typing import Any
+from typing import Any, Optional
 
 import jinja2
 from jinja2 import StrictUndefined
@@ -61,7 +61,7 @@ def __init__(
         self._infer_bos_eos_tokens()
         self._infer_should_add_bos_eos()
 
-    def _get_token_from_config(self, config: dict[str, Any], key: str) -> str:
+    def _get_token_from_config(self, config: dict[str, Any], key: str) -> Optional[str]:
         """
         HF BOS/EOS tokens are either stored as e.g. {'bos_token': 5}
         or {'bos_token': {'content': 5, ...}}. This utility handles both.
@@ -72,7 +72,7 @@ def _get_token_from_config(self, config: dict[str, Any], key: str) -> str:
                 raise ValueError(f"Could not parse {key} from config")
             token = token["content"]
         else:
-            if not isinstance(token, str):
+            if token is not None and not isinstance(token, str):
                 raise ValueError(f"Could not parse {key} from config")
         return token
 
@@ -137,7 +137,12 @@ def encode(
             list[int]: The list of token ids.
         """
         token_ids = self.tokenizer.encode(text).ids
-        if add_bos and not self.hf_adds_bos and self.bos_token not in text:
+        if (
+            add_bos
+            and not self.hf_adds_bos
+            and self.bos_token is not None
+            and self.bos_token not in text
+        ):
             token_ids.insert(0, self.bos_id)
         if add_eos and not self.hf_adds_eos:
             token_ids.append(self.eos_id)
@@ -262,8 +267,14 @@ def extract_top_level_variables(self, config):
     def render_template(
         self, messages: list[dict[str, str]], add_eos: bool = True
     ) -> str:
+        # Need to set tool_calls to something for qwen chat_template
+        if self.base_tokenizer.config["tokenizer_class"] == "Qwen2Tokenizer":
+            for message in messages:
+                if "tool_calls" not in message:
+                    message["tool_calls"] = {}
         rendered = self.template.render(
             messages=messages,
+            tools=None,
             add_generation_prompt=add_eos,
             **self.special_tokens_mapping,  # We assume that the naming is consistent
             **self.top_level_variables,
@@ -291,10 +302,13 @@ def tokenize_messages(
                 add_eos=add_eos if i == len(messages) - 1 else False,
             )
 
-            current_tokens = self.base_tokenizer.encode(rendered, add_eos=False)
+            current_tokens = self.base_tokenizer.encode(
+                rendered, add_bos=False, add_eos=False
+            )
 
             if (
-                self.base_tokenizer.bos_token in rendered
+                self.base_tokenizer.bos_token is not None
+                and self.base_tokenizer.bos_token in rendered
                 and self.base_tokenizer.hf_adds_bos
             ):
                 del current_tokens[0]