Make it possible to specify multiple config files

Summary:

Make it possible to specify multiple config files.
Parsing CLI is not a special case anymore, just uses the same config inheritance method.

Test Plan:

Test that this iterpolates in the right order via unit tests

Sample usage, loads the internal config, which references bytelatent/configs/entropy_model.yaml. The precendence order is:

- Default pydantic args
- Included configs, eg `config`
- CLI args

```
python -m bytelatent.print_config config=internal/configs/entropy_model.yaml eval=null

```


Summary:

Test Plan:

bytelatent/args.py

@@ -5,7 +5,6 @@
 
 import numpy as np
 import yaml
-from omegaconf import OmegaConf
 from pydantic import BaseModel, ConfigDict
 
 from bytelatent.checkpoint import CheckpointArgs
@@ -38,19 +37,6 @@ def get_rng_state(seed: int, rank: int, world_size: int) -> dict[str, Any]:
     return np.random.default_rng((seed, rank, world_size)).bit_generator.state
 
 
-def parse_args(args_cls):
-    cli_args = OmegaConf.from_cli()
-    file_cfg = OmegaConf.load(cli_args.config)
-    # We remove 'config' attribute from config as the underlying DataClass does not have it
-    del cli_args.config
-
-    default_cfg = OmegaConf.create(args_cls().model_dump())
-    cfg = OmegaConf.merge(default_cfg, file_cfg, cli_args)
-    cfg = OmegaConf.to_container(cfg, resolve=True, throw_on_missing=True)
-    pydantic_args = args_cls.model_validate(cfg)
-    return pydantic_args
-
-
 TRAIN_DATA_FILE_PATTERN = "*.chunk.*.jsonl"
 
 

bytelatent/config_parser.py

@@ -0,0 +1,73 @@
+import copy
+from typing import Type, TypeVar
+
+import omegaconf
+from omegaconf import DictConfig, OmegaConf
+from pydantic import BaseModel
+
+
+def parse_file_config(path: str) -> DictConfig:
+    file_cfg = OmegaConf.load(path)
+    if not isinstance(file_cfg, DictConfig):
+        raise ValueError(
+            f"File paths must parse to DictConfig, but it was: {type(file_cfg)}"
+        )
+    return file_cfg
+
+
+def recursively_parse_config(cfg: DictConfig) -> list[DictConfig]:
+    if "config" not in cfg:
+        return [cfg]
+
+    ordered_cfgs = []
+    cfg = copy.deepcopy(cfg)
+    config_arg = cfg["config"]
+    del cfg["config"]
+    ordered_cfgs.append(cfg)
+
+    if isinstance(config_arg, str):
+        file_cfg = parse_file_config(config_arg)
+        sub_configs = recursively_parse_config(file_cfg)
+        ordered_cfgs = sub_configs + ordered_cfgs
+    elif isinstance(config_arg, omegaconf.listconfig.ListConfig):
+        sub_configs = []
+        for c in config_arg:
+            if not isinstance(c, str):
+                raise ValueError(
+                    f'If "config" is specified, it must be either a string path or a list of string paths. It was config={config_arg}'
+                )
+            config_to_parse = parse_file_config(c)
+            sub_configs.extend(recursively_parse_config(config_to_parse))
+        ordered_cfgs = sub_configs + ordered_cfgs
+    else:
+        raise ValueError(
+            f'If "config" is specified, it must be either a string path or a list of string paths, it was config={config_arg}'
+        )
+    return ordered_cfgs
+
+
+def parse_args_with_default(
+    *, default_cfg: DictConfig | None = None, cli_args: DictConfig | None = None
+):
+    if cli_args is None:
+        cli_args = OmegaConf.from_cli()
+        assert isinstance(
+            cli_args, DictConfig
+        ), f"CLI Args must be a DictConfig, not {type(cli_args)}"
+    ordered_cfgs = recursively_parse_config(cli_args)
+    if default_cfg is not None:
+        ordered_cfgs.insert(0, default_cfg)
+    cfg = OmegaConf.merge(*ordered_cfgs)
+    return OmegaConf.to_container(cfg, resolve=True, throw_on_missing=True)
+
+
+T = TypeVar("T", bound=BaseModel)
+
+
+def parse_args_to_pydantic_model(
+    args_cls: Type[T], cli_args: DictConfig | None = None
+) -> T:
+    default_cfg = OmegaConf.create(args_cls().model_dump())
+    parsed_cfg = parse_args_with_default(default_cfg=default_cfg, cli_args=cli_args)
+    pydantic_args = args_cls.model_validate(parsed_cfg)
+    return pydantic_args

bytelatent/configs/debug.yaml

@@ -56,13 +56,11 @@ model:
   recompute_attn: false
   custom_bwd: false
   layer_ckpt: "none"
-  patch_only_encoder: false
-  patch_only_decoder: false
   use_local_encoder_transformer: true
   init_use_gaussian: true
   init_use_depth: "current"
-  attn_bias_type: "block_causal"
   attn_impl: "xformers"
+  attn_bias_type: "block_causal"
   alpha_depth: "disabled"
   max_length: 256
   local_attention_window_len: 512

bytelatent/configs/entropy_model.yaml

@@ -2,9 +2,10 @@
 # Evals can be activated by uncommenting its config
 # python -m launchers.stool config=apps/main/configs/debug.yaml nodes=8 account=fair_amaia_cw_codegen qos=lowest
 
-dump_dir: /tmp/
+dump_dir: /tmp/blt-entropy
 name: "debug"
 steps: 100_000
+max_steps: null
 probe_freq: null
 seed: 777
 optim:
@@ -35,7 +36,6 @@ entropy_model:
   attn_impl: "xformers"
 
 data:
-  s3_profile: blt
   root_dir: ???
   sources:
     dclm_baseline_1.0: 1.0

bytelatent/eval.py

@@ -5,18 +5,15 @@
 import os
 from collections import defaultdict
 from datetime import datetime
-from pathlib import Path
-from typing import Any
 
 import torch
 from lm_eval import simple_evaluate
 from lm_eval.api.instance import Instance
 from lm_eval.api.model import LM
-from omegaconf import OmegaConf
-from pydantic import BaseModel, ConfigDict
 
-from bytelatent.args import EvalArgs, ValidationArgs, parse_args
+from bytelatent.args import EvalArgs, ValidationArgs
 from bytelatent.checkpoint import CONSOLIDATE_FOLDER, consolidate_checkpoints
+from bytelatent.config_parser import parse_args_to_pydantic_model
 from bytelatent.data.file_util import get_fs
 from bytelatent.distributed import (
     DistributedArgs,
@@ -29,7 +26,6 @@
     PackedCausalTransformerGenerator,
     load_consolidated_model_and_tokenizer,
 )
-from bytelatent.transformer import LMTransformer, LMTransformerArgs
 
 EVAL_FOLDER_NAME = "{:010d}"
 

bytelatent/print_config.py

@@ -0,0 +1,11 @@
+from bytelatent.args import TrainArgs
+from bytelatent.config_parser import parse_args_to_pydantic_model
+
+
+def main():
+    train_args = parse_args_to_pydantic_model(TrainArgs)
+    print(train_args.model_dump_json(indent=4))
+
+
+if __name__ == "__main__":
+    main()

bytelatent/test_config_parser.py

@@ -0,0 +1,180 @@
+import os
+
+import pytest
+from omegaconf import DictConfig, MissingMandatoryValue, OmegaConf
+from pydantic import BaseModel, ConfigDict
+
+from bytelatent.config_parser import (
+    parse_args_to_pydantic_model,
+    parse_file_config,
+    recursively_parse_config,
+)
+
+FIXTURE_DIR = "fixtures/test-cfgs"
+
+
+def test_parse_file_config():
+    with pytest.raises(ValueError):
+        cfg = parse_file_config(os.path.join(FIXTURE_DIR, "list.yaml"))
+        assert isinstance(cfg, DictConfig)
+
+
+def test_nop():
+    cfg = OmegaConf.create({"a": 1})
+    parsed_cfgs = recursively_parse_config(cfg)
+    assert len(parsed_cfgs) == 1
+    assert parsed_cfgs[0] == cfg
+
+
+def test_root():
+    cli_cfg = OmegaConf.create({"config": os.path.join(FIXTURE_DIR, "root.yaml")})
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 2
+    assert len(parsed_cfgs[1]) == 0
+    assert parsed_cfgs[0]["seed"] == -1
+    with pytest.raises(MissingMandatoryValue):
+        assert parsed_cfgs[0]["b"]["y"] is not None
+
+    # Test basic cli override
+    cli_cfg = OmegaConf.create(
+        {"config": os.path.join(FIXTURE_DIR, "root.yaml"), "seed": 42}
+    )
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert parsed_cfgs[1]["seed"] == 42
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["seed"] == 42
+
+
+def test_one_level_include():
+    cli_cfg = OmegaConf.create({"config": os.path.join(FIXTURE_DIR, "middle.yaml")})
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 3
+    assert parsed_cfgs[0]["seed"] == -1
+    assert parsed_cfgs[1]["b"]["y"] == 10
+    assert len(parsed_cfgs[2]) == 0
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["b"]["y"] == 10
+
+    cli_cfg = OmegaConf.create(
+        {"config": os.path.join(FIXTURE_DIR, "middle.yaml"), "b": {"y": 100}}
+    )
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 3
+    assert parsed_cfgs[0]["seed"] == -1
+    assert parsed_cfgs[1]["b"]["y"] == 10
+    assert parsed_cfgs[2]["b"]["y"] == 100
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["b"]["y"] == 100
+
+
+def test_two_level_include():
+    cli_cfg = OmegaConf.create(
+        {"config": os.path.join(FIXTURE_DIR, "top.yaml"), "p": 500, "b": {"z": -2}}
+    )
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 4
+    assert parsed_cfgs[0]["seed"] == -1
+    assert parsed_cfgs[1]["b"]["y"] == 10
+    assert parsed_cfgs[2]["hello"] == "world"
+    assert parsed_cfgs[3]["p"] == 500
+    assert parsed_cfgs[3]["b"]["z"] == -2
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["a"] == 1
+    assert cfg["seed"] == -1
+    assert cfg["b"]["x"] == 0
+    assert cfg["b"]["y"] == 10
+    assert cfg["b"]["z"] == -2
+    assert cfg["hello"] == "world"
+
+
+def test_multiple_includes():
+    cli_cfg = OmegaConf.create(
+        {
+            "config": [
+                os.path.join(FIXTURE_DIR, "top.yaml"),
+                os.path.join(FIXTURE_DIR, "override.yaml"),
+            ],
+            "p": 500,
+            "b": {"z": -2},
+        }
+    )
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 5
+    assert parsed_cfgs[0]["seed"] == -1
+    assert parsed_cfgs[1]["b"]["y"] == 10
+    assert parsed_cfgs[2]["hello"] == "world"
+    assert parsed_cfgs[3]["a"] == 100
+    assert parsed_cfgs[4]["p"] == 500
+    assert parsed_cfgs[4]["b"]["z"] == -2
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["a"] == 100
+    assert cfg["seed"] == -1
+    assert cfg["b"]["x"] == 0
+    assert cfg["b"]["y"] == 10
+    assert cfg["b"]["z"] == -2
+    assert cfg["hello"] == "world"
+
+    cli_cfg = OmegaConf.create(
+        {
+            "config": [
+                os.path.join(FIXTURE_DIR, "top.yaml"),
+                os.path.join(FIXTURE_DIR, "override.yaml"),
+            ],
+            "p": 500,
+            "b": {"z": -2},
+            "a": 1000,
+        }
+    )
+    parsed_cfgs = recursively_parse_config(cli_cfg)
+    assert len(parsed_cfgs) == 5
+    assert parsed_cfgs[0]["seed"] == -1
+    assert parsed_cfgs[1]["b"]["y"] == 10
+    assert parsed_cfgs[2]["hello"] == "world"
+    assert parsed_cfgs[3]["a"] == 100
+    assert parsed_cfgs[4]["p"] == 500
+    assert parsed_cfgs[4]["b"]["z"] == -2
+    cfg = OmegaConf.merge(*parsed_cfgs)
+    assert cfg["a"] == 1000
+    assert cfg["seed"] == -1
+    assert cfg["b"]["x"] == 0
+    assert cfg["b"]["y"] == 10
+    assert cfg["b"]["z"] == -2
+    assert cfg["hello"] == "world"
+
+
+class SubConfig(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+    x: int = -100
+    y: int = -100
+    z: int = -5
+
+
+class SampleConfig(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+    a: int = -100
+    seed: int = -100
+    b: SubConfig = SubConfig()
+    hello: str = ""
+    p: int = -100
+
+
+def test_pydantic_parse():
+    cli_cfg = OmegaConf.create(
+        {
+            "config": [
+                os.path.join(FIXTURE_DIR, "top.yaml"),
+                os.path.join(FIXTURE_DIR, "override.yaml"),
+            ],
+            "p": 500,
+            "a": 1000,
+        }
+    )
+    cfg = parse_args_to_pydantic_model(SampleConfig, cli_args=cli_cfg)
+    assert isinstance(cfg, SampleConfig)
+    assert cfg.a == 1000
+    assert cfg.p == 500
+    assert cfg.seed == -1
+    assert cfg.b.x == 0
+    assert cfg.b.y == 10
+    assert cfg.b.z == -5
+    assert cfg.hello == "world"

bytelatent/train.py

@@ -23,8 +23,9 @@
 from torch.distributed.checkpoint.stateful import Stateful
 from torch.optim import lr_scheduler
 
-from bytelatent.args import TrainArgs, parse_args
+from bytelatent.args import TrainArgs
 from bytelatent.checkpoint import CheckpointManager, load_from_checkpoint
+from bytelatent.config_parser import parse_args_to_pydantic_model
 from bytelatent.data.file_util import get_fs
 from bytelatent.data.iterators.abstract_iterator import get_state_and_refresh
 from bytelatent.data.iterators.multiprocess_iterator import (
@@ -824,7 +825,7 @@ class LMTransformerArgsgs:
 
     Plus all the default values in TrainArgs dataclass.
     """
-    train_args = parse_args(TrainArgs)
+    train_args = parse_args_to_pydantic_model(TrainArgs)
     if train_args.debug_dynamo:
         import torch._dynamo
 

fixtures/test-cfgs/list.yaml

@@ -0,0 +1 @@
+[1, 2, 3]

fixtures/test-cfgs/middle.yaml

@@ -0,0 +1,3 @@
+config: fixtures/test-cfgs/root.yaml
+b:
+  y: 10

fixtures/test-cfgs/override.yaml

@@ -0,0 +1 @@
+a: 100

fixtures/test-cfgs/root.yaml

@@ -0,0 +1,6 @@
+seed: -1
+a: 1
+b:
+  x: 0
+  y: ???
+  z: ???

fixtures/test-cfgs/top.yaml

@@ -0,0 +1,3 @@
+config: fixtures/test-cfgs/middle.yaml
+
+hello: world