Delete config.py

config.py

@@ -1,180 +0,0 @@
-from __future__ import annotations
-
-import json
-from dataclasses import dataclass
-from pathlib import Path
-from typing import List, Optional
-
-
-@dataclass(frozen=True)
-class DataConfig:
-    channels: int
-    text_vocab_size: int
-    audio_vocab_size: int
-    action_vocab_size: int
-    text_pad_token_id: int
-    text_new_word_token_id: int
-    text_zero_token_id: int
-    audio_pad_token_id: int
-    audio_bos_token_id: int
-    action_pad_token_id: int
-    action_new_word_token_id: int
-    delay_pattern: List[int]
-    first_word_min_start: int
-    max_pad: int
-    second_stream_ahead: int
-    tokenizer_path: Optional[str] = None
-
-
-@dataclass(frozen=True)
-class DecoderConfig:
-    n_layer: int
-    n_embd: int
-    n_hidden: int
-    gqa_query_heads: int
-    kv_heads: int
-    gqa_head_dim: int
-    dropout: float
-    low_rank_dim: int | None = None
-
-
-@dataclass(frozen=True)
-class DepformerConfig:
-    n_layer: int
-    n_embd: int
-    n_hidden: int
-    gqa_query_heads: int
-    kv_heads: int
-    gqa_head_dim: int
-    apply_rope: bool
-    text_embedding: bool
-    mlp_activations: List[str]
-
-
-@dataclass(frozen=True)
-class LinearHeadConfig:
-    mlp_activations: List[str]
-
-
-@dataclass(frozen=True)
-class ModelConfig:
-    decoder: DecoderConfig
-    depformer: DepformerConfig
-    linear: LinearHeadConfig
-    dropout: float
-    rope_min_timescale: int
-    rope_max_timescale: int
-    normalization_layer_epsilon: float
-
-
-@dataclass(frozen=True)
-class RuntimeConfig:
-    weights_schedule: List[int]
-    max_context_steps: int
-
-
-@dataclass(frozen=True)
-class AssetsConfig:
-    tokenizer: Optional[str]
-    mimi: Optional[str]
-
-
-@dataclass(frozen=True)
-class DiaConfig:
-    data: DataConfig
-    model: ModelConfig
-    runtime: RuntimeConfig
-    assets: AssetsConfig
-
-
-def _resolve_runtime(block: dict | None, data_cfg: DataConfig) -> RuntimeConfig:
-    block = block or {}
-    weights_schedule = block.get("weights_schedule")
-    if weights_schedule is None:
-        audio_channels = max(0, data_cfg.channels - 2)
-        weights_schedule = list(range(max(audio_channels - 1, 0)))
-    max_context = block.get("max_context_steps", 1500)
-    return RuntimeConfig(
-        weights_schedule=list(weights_schedule),
-        max_context_steps=int(max_context),
-    )
-
-
-def load_config(path: str | Path) -> DiaConfig:
-    cfg = json.loads(Path(path).read_text())
-    data = cfg["data"]
-    model = cfg["model"]
-    runtime_cfg_raw = cfg.get("runtime")
-    if runtime_cfg_raw is None:
-        raise ValueError(f"Config '{path}' is missing a runtime block")
-
-    decoder_cfg = DecoderConfig(
-        n_layer=model["decoder"]["n_layer"],
-        n_embd=model["decoder"]["n_embd"],
-        n_hidden=model["decoder"]["n_hidden"],
-        gqa_query_heads=model["decoder"]["gqa_query_heads"],
-        kv_heads=model["decoder"]["kv_heads"],
-        gqa_head_dim=model["decoder"]["gqa_head_dim"],
-        dropout=model.get("dropout", 0.0),
-        low_rank_dim=model["decoder"].get("low_rank_dim"),
-    )
-
-    depformer_cfg = DepformerConfig(
-        n_layer=model["depformer"]["n_layer"],
-        n_embd=model["depformer"]["n_embd"],
-        n_hidden=model["depformer"]["n_hidden"],
-        gqa_query_heads=model["depformer"]["gqa_query_heads"],
-        kv_heads=model["depformer"]["kv_heads"],
-        gqa_head_dim=model["depformer"]["gqa_head_dim"],
-        apply_rope=model["depformer"].get("apply_rope", True),
-        text_embedding=model["depformer"].get("text_embedding", True),
-        mlp_activations=model["depformer"].get("mlp_activations", ["silu", "linear"]),
-    )
-
-    data_cfg = DataConfig(
-        channels=data["channels"],
-        text_vocab_size=data["text_vocab_size"],
-        audio_vocab_size=data["audio_vocab_size"],
-        action_vocab_size=data["action_vocab_size"],
-        text_pad_token_id=data["text_pad_token_id"],
-        text_new_word_token_id=data["text_new_word_token_id"],
-        text_zero_token_id=data.get("text_zero_token_id", 7),
-        audio_pad_token_id=data.get("audio_pad_token_id", data["audio_vocab_size"] - 1),
-        audio_bos_token_id=data.get("audio_bos_token_id", data["audio_vocab_size"] - 2),
-        action_pad_token_id=data["action_pad_token_id"],
-        action_new_word_token_id=data["action_new_word_token_id"],
-        delay_pattern=list(data.get("delay_pattern", [])),
-        first_word_min_start=data.get("first_word_min_start", 0),
-        max_pad=data.get("max_pad", 0),
-        second_stream_ahead=data.get("second_stream_ahead", 0),
-        tokenizer_path=data.get("tokenizer_path"),
-    )
-
-    runtime_cfg = _resolve_runtime(runtime_cfg_raw, data_cfg)
-
-    linear_cfg = LinearHeadConfig(
-        mlp_activations=model.get("linear", {}).get("mlp_activations", ["silu", "linear"]),
-    )
-
-    model_cfg = ModelConfig(
-        decoder=decoder_cfg,
-        depformer=depformer_cfg,
-        linear=linear_cfg,
-        dropout=model.get("dropout", 0.0),
-        rope_min_timescale=model.get("rope_min_timescale", 1),
-        rope_max_timescale=model.get("rope_max_timescale", 10000),
-        normalization_layer_epsilon=model.get("normalization_layer_epsilon", 1e-5),
-    )
-
-    assets_raw = cfg.get("assets") or {}
-    assets_cfg = AssetsConfig(
-        tokenizer=assets_raw.get("tokenizer") or data_cfg.tokenizer_path,
-        mimi=assets_raw.get("mimi"),
-    )
-
-    return DiaConfig(
-        data=data_cfg,
-        model=model_cfg,
-        runtime=runtime_cfg,
-        assets=assets_cfg,
-    )