# Path: disentanglement_lib/data/ground_truth/ground_truth_data.py
# class GroundTruthData(object):
#   def num_factors(self):
#   def factors_num_values(self):
#   def observation_shape(self):
#   def sample_factors(self, num, random_state):
#   def sample_observations_from_factors(self, factors, random_state):
#   def sample(self, num, random_state):
#   def sample_observations(self, num, random_state):
# 
# Path: disentanglement_lib/data/ground_truth/util.py
# def tf_data_set_from_ground_truth_data(ground_truth_data, random_seed):
#   def generator():
#   def __init__(self, factor_sizes, latent_factor_indices):
#   def num_latent_factors(self):
#   def sample_latent_factors(self, num, random_state):
#   def sample_all_factors(self, latent_factors, random_state):
#   def _sample_factor(self, i, num, random_state):
#   def __init__(self, factor_sizes, features):
#   def features_to_index(self, features):
#   def _features_to_state_space_index(self, features):
# class SplitDiscreteStateSpace(object):
# class StateSpaceAtomIndex(object):


import os
import numpy as np
import tensorflow.compat.v1 as tf
from disentanglement_lib.data.ground_truth import ground_truth_data
from disentanglement_lib.data.ground_truth import util
from six.moves import range
# coding=utf-8
# Copyright 2018 The DisentanglementLib Authors.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Shapes3D data set."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function


SHAPES3D_PATH = os.path.join(
    os.environ.get("DISENTANGLEMENT_LIB_DATA", "."), "3dshapes",
    "look-at-object-room_floor-hueXwall-hueXobj-"
    "hueXobj-sizeXobj-shapeXview-azi.npz"
)




# Path: disentanglement_lib/data/ground_truth/ground_truth_data.py
# class GroundTruthData(object):
#   def num_factors(self):
#   def factors_num_values(self):
#   def observation_shape(self):
#   def sample_factors(self, num, random_state):
#   def sample_observations_from_factors(self, factors, random_state):
#   def sample(self, num, random_state):
#   def sample_observations(self, num, random_state):
# 
# Path: disentanglement_lib/data/ground_truth/util.py
# def tf_data_set_from_ground_truth_data(ground_truth_data, random_seed):
#   def generator():
#   def __init__(self, factor_sizes, latent_factor_indices):
#   def num_latent_factors(self):
#   def sample_latent_factors(self, num, random_state):
#   def sample_all_factors(self, latent_factors, random_state):
#   def _sample_factor(self, i, num, random_state):
#   def __init__(self, factor_sizes, features):
#   def features_to_index(self, features):
#   def _features_to_state_space_index(self, features):
# class SplitDiscreteStateSpace(object):
# class StateSpaceAtomIndex(object):


# Path: disentanglement_lib/data/ground_truth/shapes3d.py
import os
import numpy as np
import tensorflow.compat.v1 as tf
from disentanglement_lib.data.ground_truth import ground_truth_data
from disentanglement_lib.data.ground_truth import util
from six.moves import range

# coding=utf-8
# Copyright 2018 The DisentanglementLib Authors.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Shapes3D data set."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function


SHAPES3D_PATH = os.path.join(
    os.environ.get("DISENTANGLEMENT_LIB_DATA", "."), "3dshapes",
    "look-at-object-room_floor-hueXwall-hueXobj-"
    "hueXobj-sizeXobj-shapeXview-azi.npz"
)




class Shapes3D(ground_truth_data.GroundTruthData):