71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
# Copyright 2022 The MediaPipe 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.
|
|
"""Specifications for text classifier models."""
|
|
|
|
import dataclasses
|
|
import enum
|
|
import functools
|
|
|
|
from mediapipe.model_maker.python.core import hyperparameters as hp
|
|
from mediapipe.model_maker.python.text.core import bert_model_spec
|
|
from mediapipe.model_maker.python.text.text_classifier import model_options as mo
|
|
|
|
# BERT-based text classifier spec inherited from BertModelSpec
|
|
BertClassifierSpec = bert_model_spec.BertModelSpec
|
|
|
|
|
|
@dataclasses.dataclass
|
|
class AverageWordEmbeddingClassifierSpec:
|
|
"""Specification for an average word embedding classifier model.
|
|
|
|
Attributes:
|
|
hparams: Configurable hyperparameters for training.
|
|
model_options: Configurable options for the average word embedding model.
|
|
name: The name of the object.
|
|
"""
|
|
|
|
# `learning_rate` is unused for the average word embedding model
|
|
hparams: hp.BaseHParams = hp.BaseHParams(
|
|
epochs=10, batch_size=32, learning_rate=0)
|
|
model_options: mo.AverageWordEmbeddingClassifierModelOptions = (
|
|
mo.AverageWordEmbeddingClassifierModelOptions())
|
|
name: str = 'AverageWordEmbedding'
|
|
|
|
|
|
average_word_embedding_classifier_spec = functools.partial(
|
|
AverageWordEmbeddingClassifierSpec)
|
|
|
|
mobilebert_classifier_spec = functools.partial(
|
|
BertClassifierSpec,
|
|
hparams=hp.BaseHParams(
|
|
epochs=3,
|
|
batch_size=48,
|
|
learning_rate=3e-5,
|
|
distribution_strategy='off'),
|
|
name='MobileBert',
|
|
uri='https://tfhub.dev/tensorflow/mobilebert_en_uncased_L-24_H-128_B-512_A-4_F-4_OPT/1',
|
|
tflite_input_name={
|
|
'ids': 'serving_default_input_1:0',
|
|
'mask': 'serving_default_input_3:0',
|
|
'segment_ids': 'serving_default_input_2:0'
|
|
},
|
|
)
|
|
|
|
|
|
@enum.unique
|
|
class SupportedModels(enum.Enum):
|
|
"""Predefined text classifier model specs supported by Model Maker."""
|
|
AVERAGE_WORD_EMBEDDING_CLASSIFIER = average_word_embedding_classifier_spec
|
|
MOBILEBERT_CLASSIFIER = mobilebert_classifier_spec
|