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Running
on
Zero
Running
on
Zero
""" | |
Not in original Open-MAGVIT2. | |
""" | |
import json | |
from dataclasses import dataclass | |
class VQConfig: | |
# Model Arch | |
in_channels: int = 3 | |
z_channels: int = 18 | |
out_channels: int = 3 | |
base_channels: int = 128 # Initial hidden width, all subsequent blocks are multiples (`ch_mult`) of this width | |
ch_mult: tuple[int] = (1, 1, 2, 2, 4) | |
num_res_blocks: int = 2 | |
# Loss Config (uncertain about some of the types) | |
# Hardcoding for `magvit2.modules.losses.vqperceptual.VQLPIPSWithDiscriminator` | |
disc_conditional: bool = False | |
disc_in_channels: int = 3 | |
disc_start: int = 0 # from 0 epoch | |
disc_loss: str = "hinge" | |
disc_ndf: int = 64 | |
disc_num_layers: int = 3 | |
use_actnorm: bool = False | |
disc_factor: float = 1.0 | |
disc_weight: float = 0.8 | |
gen_loss_weight: float = 0.1 | |
lecam_loss_weight: float = 0.005 | |
codebook_weight: float = 0.1 | |
commit_weight: float = 0.25 | |
pixelloss_weight: float = 1.0 | |
perceptual_weight: float = 1.0 | |
codebook_enlarge_ratio: float = 0 | |
codebook_enlarge_steps: int = 2000 | |
num_codebooks: int = 1 | |
codebook_size: int = 262144 | |
sample_minimization_weight: float = 1.0 | |
batch_maximization_weight: float = 1.0 | |
token_factorization: bool = False | |
# TODO: duplicated from GenieConfig | |
def save_pretrained(self, json_path): | |
with open(json_path, "w") as f: | |
json.dump(vars(self), f) | |
def from_pretrained(cls, json_path): | |
with open(json_path, "r") as f: | |
config = json.load(f) | |
return cls(**config) | |