65 lines
2.4 KiB
Python
65 lines
2.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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from dataclasses import dataclass, field
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from typing import Any
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from fastvideo.configs.models.base import ArchConfig, ModelConfig
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from fastvideo.layers.quantization import QuantizationConfig
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from fastvideo.platforms import AttentionBackendEnum
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@dataclass
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class DiTArchConfig(ArchConfig):
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_fsdp_shard_conditions: list = field(default_factory=list)
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_compile_conditions: list = field(default_factory=list)
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param_names_mapping: dict = field(default_factory=dict)
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reverse_param_names_mapping: dict = field(default_factory=dict)
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lora_param_names_mapping: dict = field(default_factory=dict)
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_supported_attention_backends: tuple[AttentionBackendEnum,
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...] = (AttentionBackendEnum.SAGE_ATTN, AttentionBackendEnum.FLASH_ATTN,
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AttentionBackendEnum.TORCH_SDPA,
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AttentionBackendEnum.VIDEO_SPARSE_ATTN,
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AttentionBackendEnum.VMOBA_ATTN, AttentionBackendEnum.SAGE_ATTN_THREE,
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AttentionBackendEnum.SLA_ATTN, AttentionBackendEnum.SAGE_SLA_ATTN)
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hidden_size: int = 0
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num_attention_heads: int = 0
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num_channels_latents: int = 0
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in_channels: int = 0
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out_channels: int = 0
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exclude_lora_layers: list[str] = field(default_factory=list)
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boundary_ratio: float | None = None
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def __post_init__(self) -> None:
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if not self._compile_conditions:
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self._compile_conditions = self._fsdp_shard_conditions.copy()
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@dataclass
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class DiTConfig(ModelConfig):
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arch_config: DiTArchConfig = field(default_factory=DiTArchConfig)
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# FastVideoDiT-specific parameters
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prefix: str = ""
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quant_config: QuantizationConfig | None = None
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@staticmethod
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def add_cli_args(parser: Any, prefix: str = "dit-config") -> Any:
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"""Add CLI arguments for DiTConfig fields"""
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parser.add_argument(
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f"--{prefix}.prefix",
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type=str,
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dest=f"{prefix.replace('-', '_')}.prefix",
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default=DiTConfig.prefix,
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help="Prefix for the DiT model",
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)
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parser.add_argument(
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f"--{prefix}.quant-config",
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type=str,
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dest=f"{prefix.replace('-', '_')}.quant_config",
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default=None,
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help="Quantization configuration for the DiT model",
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)
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return parser
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