from __future__ import division from __future__ import print_function import os.path as osp import numpy as np from easydict import EasyDict as edict __C = edict() cfg = __C # Dataset name: flowers, birds __C.DATASET_NAME = "birds" __C.CONFIG_NAME = "" __C.DATA_DIR = "" __C.GPU_ID = 0 __C.CUDA = True __C.WORKERS = 6 __C.RNN_TYPE = "LSTM" # 'GRU' __C.B_VALIDATION = False __C.TREE = edict() __C.TREE.BRANCH_NUM = 3 __C.TREE.BASE_SIZE = 64 # Training options __C.TRAIN = edict() __C.TRAIN.BATCH_SIZE = 64 __C.TRAIN.MAX_EPOCH = 600 __C.TRAIN.SNAPSHOT_INTERVAL = 2000 __C.TRAIN.DISCRIMINATOR_LR = 2e-4 __C.TRAIN.GENERATOR_LR = 2e-4 __C.TRAIN.ENCODER_LR = 2e-4 __C.TRAIN.RNN_GRAD_CLIP = 0.25 __C.TRAIN.FLAG = True __C.TRAIN.NET_E = "" __C.TRAIN.NET_G = "" __C.TRAIN.B_NET_D = True __C.TRAIN.SMOOTH = edict() __C.TRAIN.SMOOTH.GAMMA1 = 5.0 __C.TRAIN.SMOOTH.GAMMA3 = 10.0 __C.TRAIN.SMOOTH.GAMMA2 = 5.0 __C.TRAIN.SMOOTH.LAMBDA = 1.0 # Modal options __C.GAN = edict() __C.GAN.DF_DIM = 64 __C.GAN.GF_DIM = 128 __C.GAN.Z_DIM = 100 __C.GAN.CONDITION_DIM = 100 __C.GAN.R_NUM = 2 __C.GAN.B_ATTENTION = True __C.GAN.B_DCGAN = False __C.TEXT = edict() __C.TEXT.CAPTIONS_PER_IMAGE = 10 __C.TEXT.EMBEDDING_DIM = 256 __C.TEXT.WORDS_NUM = 18 def _merge_a_into_b(a, b): """Merge config dictionary a into config dictionary b, clobbering the options in b whenever they are also specified in a. """ if type(a) is not edict: return for k, v in a.items(): # a must specify keys that are in b if k not in b: raise KeyError("{} is not a valid config key".format(k)) # the types must match, too old_type = type(b[k]) if old_type is not type(v): if isinstance(b[k], np.ndarray): v = np.array(v, dtype=b[k].dtype) else: raise ValueError( ("Type mismatch ({} vs. {}) " "for config key: {}").format( type(b[k]), type(v), k ) ) # recursively merge dicts if type(v) is edict: try: _merge_a_into_b(a[k], b[k]) except: print("Error under config key: {}".format(k)) raise else: b[k] = v def cfg_from_file(filename): """Load a config file and merge it into the default options.""" import yaml with open(filename, "r") as f: yaml_cfg = edict(yaml.load(f)) _merge_a_into_b(yaml_cfg, __C)