models/biggan/pytorch_biggan/pytorch_pretrained_biggan/config.py

# coding: utf-8
"""
BigGAN config.
"""
from __future__ import (absolute_import, division, print_function, unicode_literals)

import copy
import json

class BigGANConfig(object):
    """ Configuration class to store the configuration of a `BigGAN`. 
        Defaults are for the 128x128 model.
        layers tuple are (up-sample in the layer ?, input channels, output channels)
    """
    def __init__(self,
                 output_dim=128,
                 z_dim=128,
                 class_embed_dim=128,
                 channel_width=128,
                 num_classes=1000,
                 layers=[(False, 16, 16),
                         (True, 16, 16),
                         (False, 16, 16),
                         (True, 16, 8),
                         (False, 8, 8),
                         (True, 8, 4),
                         (False, 4, 4),
                         (True, 4, 2),
                         (False, 2, 2),
                         (True, 2, 1)],
                 attention_layer_position=8,
                 eps=1e-4,
                 n_stats=51):
        """Constructs BigGANConfig. """
        self.output_dim = output_dim
        self.z_dim = z_dim
        self.class_embed_dim = class_embed_dim
        self.channel_width = channel_width
        self.num_classes = num_classes
        self.layers = layers
        self.attention_layer_position = attention_layer_position
        self.eps = eps
        self.n_stats = n_stats

    @classmethod
    def from_dict(cls, json_object):
        """Constructs a `BigGANConfig` from a Python dictionary of parameters."""
        config = BigGANConfig()
        for key, value in json_object.items():
            config.__dict__[key] = value
        return config

    @classmethod
    def from_json_file(cls, json_file):
        """Constructs a `BigGANConfig` from a json file of parameters."""
        with open(json_file, "r", encoding='utf-8') as reader:
            text = reader.read()
        return cls.from_dict(json.loads(text))

    def __repr__(self):
        return str(self.to_json_string())

    def to_dict(self):
        """Serializes this instance to a Python dictionary."""
        output = copy.deepcopy(self.__dict__)
        return output

    def to_json_string(self):
        """Serializes this instance to a JSON string."""
        return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"