def test_electra_get_pretrained(model_name, ctx):
assert len(list_pretrained_electra()) > 0
with tempfile.TemporaryDirectory() as root, ctx:
cfg, tokenizer, backbone_params_path, (disc_params_path, gen_params_path) =\
get_pretrained_electra(model_name, root=root,
load_backbone=True, load_disc=True, load_gen=True)
assert cfg.MODEL.vocab_size == len(tokenizer.vocab)
electra_model = ElectraModel.from_cfg(cfg)
electra_model.load_parameters(backbone_params_path)
electra_disc_model = ElectraDiscriminator(cfg)
electra_disc_model.load_parameters(disc_params_path)
electra_disc_model = ElectraDiscriminator(cfg)
electra_disc_model.backbone_model.load_parameters(backbone_params_path)
gen_cfg = get_generator_cfg(cfg)
electra_gen_model = ElectraGenerator(gen_cfg)
electra_gen_model.load_parameters(gen_params_path)
electra_gen_model.tie_embeddings(
electra_disc_model.backbone_model.word_embed.collect_params(),
electra_disc_model.backbone_model.token_type_embed.collect_params(
),
electra_disc_model.backbone_model.token_pos_embed.collect_params(),
electra_disc_model.backbone_model.embed_layer_norm.collect_params(
))
electra_gen_model = ElectraGenerator(cfg)
electra_gen_model.backbone_model.load_parameters(backbone_params_path)
def test_list_pretrained_electra():
assert len(list_pretrained_electra()) > 0
contextual_embedding, pooled_out = electra_model(
inputs, token_types, valid_length)
electra_model_tn = ElectraModel.from_cfg(cfg_tn)
electra_model_tn.share_parameters(electra_model.collect_params())
electra_model_tn.hybridize()
contextual_embedding_tn, pooled_out_tn = electra_model_tn(
inputs.T, token_types.T, valid_length)
assert_allclose(contextual_embedding.asnumpy(),
np.swapaxes(contextual_embedding_tn.asnumpy(), 0, 1),
1E-4, 1E-4)
assert_allclose(pooled_out.asnumpy(), pooled_out_tn.asnumpy(), 1E-4,
1E-4)
@pytest.mark.remote_required
@pytest.mark.parametrize('model_name', list_pretrained_electra())
def test_electra_get_pretrained(model_name, ctx):
assert len(list_pretrained_electra()) > 0
with tempfile.TemporaryDirectory() as root, ctx:
cfg, tokenizer, backbone_params_path, (disc_params_path, gen_params_path) =\
get_pretrained_electra(model_name, root=root,
load_backbone=True, load_disc=True, load_gen=True)
assert cfg.MODEL.vocab_size == len(tokenizer.vocab)
electra_model = ElectraModel.from_cfg(cfg)
electra_model.load_parameters(backbone_params_path)
electra_disc_model = ElectraDiscriminator(cfg)
electra_disc_model.load_parameters(disc_params_path)
electra_disc_model = ElectraDiscriminator(cfg)
electra_disc_model.backbone_model.load_parameters(backbone_params_path)