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render(self, mode='human', close=False, view='agent')
self.window.close()
self.render_obs(self.vis_fb)
self.render_top_view(self.vis_fb)
self.render_obs()
pyglet.gl.Config(double_buffer=True)
self.window.clear()
self.window.switch_to()
glBindFramebuffer(GL_FRAMEBUFFER, 0)
glClearColor(0, 0, 0, 1.0)
glClearDepth(1.0)
glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
glMatrixMode(GL_PROJECTION)
glLoadIdentity()
glMatrixMode(GL_MODELVIEW)
glLoadIdentity()
glOrtho(0, window_width, 0, window_height, 0, 10)
np.ascontiguousarray(np.flip(img, axis=0)
img_flip.ctypes.data_as(POINTER(GLubyte)
np.ascontiguousarray(np.flip(obs, axis=0)
obs.ctypes.data_as(POINTER(GLubyte)
int(self.agent.dir * 180 / math.pi)
self.text_label.draw()
glFlush()
self.window.flip()
self.window.dispatch_events()
admin.site.register(Question)
admin.site.register(Choice)
Copyright (c)
logging.get_logger(__name__)
PretrainedConfig(PushToHubMixin)
attributes (overridden by derived classes)
attributes (present in all subclasses)
matrix (this attribute may be missing for models that don't have a text modality like ViT)
name_or_path (:obj:`str`, `optional`, defaults to :obj:`""`)
output_hidden_states (:obj:`bool`, `optional`, defaults to :obj:`False`)
output_attentions (:obj:`bool`, `optional`, defaults to :obj:`False`)
return_dict (:obj:`bool`, `optional`, defaults to :obj:`True`)
is_encoder_decoder (:obj:`bool`, `optional`, defaults to :obj:`False`)
is_decoder (:obj:`bool`, `optional`, defaults to :obj:`False`)
not (in which case it's used as an encoder)
add_cross_attention (:obj:`bool`, `optional`, defaults to :obj:`False`)
tie_encoder_decoder (:obj:`bool`, `optional`, defaults to :obj:`False`)
prune_heads (:obj:`Dict[int, List[int]]`, `optional`, defaults to :obj:`{}`)
chunk_size_feed_forward (:obj:`int`, `optional`, defaults to :obj:`0`)
original (TensorFlow or PyTorch)
of (:obj:`"regression"`, :obj:`"single_label_classification"`, :obj:`"multi_label_classification"`)
scalars (only used by some TensorFlow models)
__setattr__(self, key, value)
super()
__getattribute__("attribute_map")
super()
__getattribute__("attribute_map")
super()
__setattr__(key, value)
__getattribute__(self, key)
super()
__getattribute__("attribute_map")
super()
__getattribute__("attribute_map")
super()
__getattribute__(key)
__init__(self, **kwargs)
kwargs.pop("return_dict", True)
kwargs.pop("output_hidden_states", False)
kwargs.pop("output_attentions", False)
kwargs.pop("torchscript", False)
kwargs.pop("torch_dtype", None)
kwargs.pop("use_bfloat16", False)
kwargs.pop("pruned_heads", {})
kwargs.pop("is_encoder_decoder", False)
kwargs.pop("is_decoder", False)
kwargs.pop("add_cross_attention", False)
kwargs.pop("tie_encoder_decoder", False)
kwargs.pop("max_length", 20)
kwargs.pop("min_length", 0)
kwargs.pop("do_sample", False)
kwargs.pop("early_stopping", False)
kwargs.pop("num_beams", 1)
kwargs.pop("num_beam_groups", 1)
kwargs.pop("diversity_penalty", 0.0)
kwargs.pop("temperature", 1.0)
kwargs.pop("top_k", 50)
kwargs.pop("top_p", 1.0)
kwargs.pop("repetition_penalty", 1.0)
kwargs.pop("length_penalty", 1.0)
kwargs.pop("no_repeat_ngram_size", 0)
kwargs.pop("encoder_no_repeat_ngram_size", 0)
kwargs.pop("bad_words_ids", None)
kwargs.pop("num_return_sequences", 1)
kwargs.pop("chunk_size_feed_forward", 0)
kwargs.pop("output_scores", False)
kwargs.pop("return_dict_in_generate", False)
kwargs.pop("forced_bos_token_id", None)
kwargs.pop("forced_eos_token_id", None)
kwargs.pop("remove_invalid_values", False)
kwargs.pop("architectures", None)
kwargs.pop("finetuning_task", None)
kwargs.pop("id2label", None)
kwargs.pop("label2id", None)