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# Copyright 2023 The TensorFlow 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.
"""The generic parser interface."""
import abc
class Parser(object):
"""Parses data and produces tensors to be consumed by models."""
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def _parse_train_data(self, decoded_tensors):
"""Generates images and labels that are usable for model training.
Args:
decoded_tensors: a dict of Tensors produced by the decoder.
Returns:
images: the image tensor.
labels: a dict of Tensors that contains labels.
"""
pass
@abc.abstractmethod
def _parse_eval_data(self, decoded_tensors):
"""Generates images and labels that are usable for model evaluation.
Args:
decoded_tensors: a dict of Tensors produced by the decoder.
Returns:
images: the image tensor.
labels: a dict of Tensors that contains labels.
"""
pass
def parse_fn(self, is_training):
"""Returns a parse fn that reads and parses raw tensors from the decoder.
Args:
is_training: a `bool` to indicate whether it is in training mode.
Returns:
parse: a `callable` that takes the serialized example and generate the
images, labels tuple where labels is a dict of Tensors that contains
labels.
"""
def parse(decoded_tensors):
"""Parses the serialized example data."""
if is_training:
return self._parse_train_data(decoded_tensors)
else:
return self._parse_eval_data(decoded_tensors)
return parse
@classmethod
def inference_fn(cls, inputs):
"""Parses inputs for predictions.
Args:
inputs: A Tensor, or dictionary of Tensors.
Returns:
processed_inputs: An input tensor to the model.
"""
pass
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