transformers/tests/test_configuration_common.py
Sylvain Gugger 558f8543ba
Update Transformers to huggingface_hub >= 0.1.0 (#14251)
* Update Transformers to huggingface_hub >= 0.1.0

* Forgot to save...

* Style

* Fix test
2021-11-02 18:58:42 -04:00

270 lines
11 KiB
Python

# coding=utf-8
# Copyright 2019 HuggingFace Inc.
#
# 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.
import copy
import json
import os
import tempfile
import unittest
from huggingface_hub import delete_repo, login
from requests.exceptions import HTTPError
from transformers import BertConfig, GPT2Config, is_torch_available
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import PASS, USER, is_staging_test
config_common_kwargs = {
"return_dict": False,
"output_hidden_states": True,
"output_attentions": True,
"torchscript": True,
"torch_dtype": "float16",
"use_bfloat16": True,
"pruned_heads": {"a": 1},
"tie_word_embeddings": False,
"is_decoder": True,
"cross_attention_hidden_size": 128,
"add_cross_attention": True,
"tie_encoder_decoder": True,
"max_length": 50,
"min_length": 3,
"do_sample": True,
"early_stopping": True,
"num_beams": 3,
"num_beam_groups": 3,
"diversity_penalty": 0.5,
"temperature": 2.0,
"top_k": 10,
"top_p": 0.7,
"repetition_penalty": 0.8,
"length_penalty": 0.8,
"no_repeat_ngram_size": 5,
"encoder_no_repeat_ngram_size": 5,
"bad_words_ids": [1, 2, 3],
"num_return_sequences": 3,
"chunk_size_feed_forward": 5,
"output_scores": True,
"return_dict_in_generate": True,
"forced_bos_token_id": 2,
"forced_eos_token_id": 3,
"remove_invalid_values": True,
"architectures": ["BertModel"],
"finetuning_task": "translation",
"id2label": {0: "label"},
"label2id": {"label": "0"},
"tokenizer_class": "BertTokenizerFast",
"prefix": "prefix",
"bos_token_id": 6,
"pad_token_id": 7,
"eos_token_id": 8,
"sep_token_id": 9,
"decoder_start_token_id": 10,
"task_specific_params": {"translation": "some_params"},
"problem_type": "regression",
}
class ConfigTester(object):
def __init__(self, parent, config_class=None, has_text_modality=True, **kwargs):
self.parent = parent
self.config_class = config_class
self.has_text_modality = has_text_modality
self.inputs_dict = kwargs
def create_and_test_config_common_properties(self):
config = self.config_class(**self.inputs_dict)
common_properties = ["hidden_size", "num_attention_heads", "num_hidden_layers"]
# Add common fields for text models
if self.has_text_modality:
common_properties.extend(["vocab_size"])
# Test that config has the common properties as getters
for prop in common_properties:
self.parent.assertTrue(hasattr(config, prop), msg=f"`{prop}` does not exist")
# Test that config has the common properties as setter
for idx, name in enumerate(common_properties):
try:
setattr(config, name, idx)
self.parent.assertEqual(
getattr(config, name), idx, msg=f"`{name} value {idx} expected, but was {getattr(config, name)}"
)
except NotImplementedError:
# Some models might not be able to implement setters for common_properties
# In that case, a NotImplementedError is raised
pass
# Test if config class can be called with Config(prop_name=..)
for idx, name in enumerate(common_properties):
try:
config = self.config_class(**{name: idx})
self.parent.assertEqual(
getattr(config, name), idx, msg=f"`{name} value {idx} expected, but was {getattr(config, name)}"
)
except NotImplementedError:
# Some models might not be able to implement setters for common_properties
# In that case, a NotImplementedError is raised
pass
def create_and_test_config_to_json_string(self):
config = self.config_class(**self.inputs_dict)
obj = json.loads(config.to_json_string())
for key, value in self.inputs_dict.items():
self.parent.assertEqual(obj[key], value)
def create_and_test_config_to_json_file(self):
config_first = self.config_class(**self.inputs_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
json_file_path = os.path.join(tmpdirname, "config.json")
config_first.to_json_file(json_file_path)
config_second = self.config_class.from_json_file(json_file_path)
self.parent.assertEqual(config_second.to_dict(), config_first.to_dict())
def create_and_test_config_from_and_save_pretrained(self):
config_first = self.config_class(**self.inputs_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
config_first.save_pretrained(tmpdirname)
config_second = self.config_class.from_pretrained(tmpdirname)
self.parent.assertEqual(config_second.to_dict(), config_first.to_dict())
def create_and_test_config_with_num_labels(self):
config = self.config_class(**self.inputs_dict, num_labels=5)
self.parent.assertEqual(len(config.id2label), 5)
self.parent.assertEqual(len(config.label2id), 5)
config.num_labels = 3
self.parent.assertEqual(len(config.id2label), 3)
self.parent.assertEqual(len(config.label2id), 3)
def check_config_can_be_init_without_params(self):
if self.config_class.is_composition:
return
config = self.config_class()
self.parent.assertIsNotNone(config)
def check_config_arguments_init(self):
kwargs = copy.deepcopy(config_common_kwargs)
config = self.config_class(**kwargs)
wrong_values = []
for key, value in config_common_kwargs.items():
if key == "torch_dtype":
if not is_torch_available():
continue
else:
import torch
if config.torch_dtype != torch.float16:
wrong_values.append(("torch_dtype", config.torch_dtype, torch.float16))
elif getattr(config, key) != value:
wrong_values.append((key, getattr(config, key), value))
if len(wrong_values) > 0:
errors = "\n".join([f"- {v[0]}: got {v[1]} instead of {v[2]}" for v in wrong_values])
raise ValueError(f"The following keys were not properly sey in the config:\n{errors}")
def run_common_tests(self):
self.create_and_test_config_common_properties()
self.create_and_test_config_to_json_string()
self.create_and_test_config_to_json_file()
self.create_and_test_config_from_and_save_pretrained()
self.create_and_test_config_with_num_labels()
self.check_config_can_be_init_without_params()
self.check_config_arguments_init()
@is_staging_test
class ConfigPushToHubTester(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls._token = login(username=USER, password=PASS)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, name="test-config")
except HTTPError:
pass
try:
delete_repo(token=cls._token, name="test-config-org", organization="valid_org")
except HTTPError:
pass
def test_push_to_hub(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(os.path.join(tmp_dir, "test-config"), push_to_hub=True, use_auth_token=self._token)
new_config = BertConfig.from_pretrained(f"{USER}/test-config")
for k, v in config.__dict__.items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
def test_push_to_hub_in_organization(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(
os.path.join(tmp_dir, "test-config-org"),
push_to_hub=True,
use_auth_token=self._token,
organization="valid_org",
)
new_config = BertConfig.from_pretrained("valid_org/test-config-org")
for k, v in config.__dict__.items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
class ConfigTestUtils(unittest.TestCase):
def test_config_from_string(self):
c = GPT2Config()
# attempt to modify each of int/float/bool/str config records and verify they were updated
n_embd = c.n_embd + 1 # int
resid_pdrop = c.resid_pdrop + 1.0 # float
scale_attn_weights = not c.scale_attn_weights # bool
summary_type = c.summary_type + "foo" # str
c.update_from_string(
f"n_embd={n_embd},resid_pdrop={resid_pdrop},scale_attn_weights={scale_attn_weights},summary_type={summary_type}"
)
self.assertEqual(n_embd, c.n_embd, "mismatch for key: n_embd")
self.assertEqual(resid_pdrop, c.resid_pdrop, "mismatch for key: resid_pdrop")
self.assertEqual(scale_attn_weights, c.scale_attn_weights, "mismatch for key: scale_attn_weights")
self.assertEqual(summary_type, c.summary_type, "mismatch for key: summary_type")
def test_config_common_kwargs_is_complete(self):
base_config = PretrainedConfig()
missing_keys = [key for key in base_config.__dict__ if key not in config_common_kwargs]
# If this part of the test fails, you have arguments to addin config_common_kwargs above.
self.assertListEqual(missing_keys, ["is_encoder_decoder", "_name_or_path", "transformers_version"])
keys_with_defaults = [key for key, value in config_common_kwargs.items() if value == getattr(base_config, key)]
if len(keys_with_defaults) > 0:
raise ValueError(
"The following keys are set with the default values in `test_configuration_common.config_common_kwargs` "
f"pick another value for them: {', '.join(keys_with_defaults)}."
)