Delete export_saved_model_lib.py

The file is not required. export_module was made in export_saved_model.py as passed as an argument.

official/vision/beta/projects/deepmac_maskrcnn/serving/export_saved_model_lib.py

-# Copyright 2021 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.
-
-# Lint as: python3
-r"""Vision models export utility function for serving/inference."""
-
-import os
-from typing import Optional, List
-
-import tensorflow as tf
-
-from official.core import config_definitions as cfg
-from official.core import export_base
-from official.core import train_utils
-from official.vision.beta.projects.deepmac_maskrcnn import configs
-from official.vision.beta.projects.deepmac_maskrcnn.serving import detection
-
-def export_inference_graph(
-    input_type: str,
-    batch_size: Optional[int],
-    input_image_size: List[int],
-    params: cfg.ExperimentConfig,
-    checkpoint_path: str,
-    export_dir: str,
-    num_channels: Optional[int] = 3,
-    export_module: Optional[export_base.ExportModule] = None,
-    export_checkpoint_subdir: Optional[str] = None,
-    export_saved_model_subdir: Optional[str] = None):
-  """Exports inference graph for the model specified in the exp config.
-  Saved model is stored at export_dir/saved_model, checkpoint is saved
-  at export_dir/checkpoint, and params is saved at export_dir/params.yaml.
-  Args:
-    input_type: One of `image_tensor`, `image_bytes`, `tf_example`.
-    batch_size: 'int', or None.
-    input_image_size: List or Tuple of height and width.
-    params: Experiment params.
-    checkpoint_path: Trained checkpoint path or directory.
-    export_dir: Export directory path.
-    num_channels: The number of input image channels.
-    export_module: Optional export module to be used instead of using params
-      to create one. If None, the params will be used to create an export
-      module.
-    export_checkpoint_subdir: Optional subdirectory under export_dir
-      to store checkpoint.
-    export_saved_model_subdir: Optional subdirectory under export_dir
-      to store saved model.
-  """
-
-  if export_checkpoint_subdir:
-    output_checkpoint_directory = os.path.join(
-        export_dir, export_checkpoint_subdir)
-  else:
-    output_checkpoint_directory = export_dir
-
-  if export_saved_model_subdir:
-    output_saved_model_directory = os.path.join(
-        export_dir, export_saved_model_subdir)
-  else:
-    output_saved_model_directory = export_dir
-
-  # TODO(arashwan): Offers a direct path to use ExportModule with Task objects.
-  if not export_module:
-    if isinstance(params.task, configs.deep_mask_head_rcnn.DeepMaskHeadRCNNTask):
-      export_module = detection.DetectionModule(
-          params=params,
-          batch_size=batch_size,
-          input_image_size=input_image_size,
-          num_channels=num_channels)
-    else:
-      raise ValueError('Export module not implemented for {} task.'.format(
-          type(params.task)))
-
-  export_base.export(
-      export_module,
-      function_keys=[input_type],
-      export_savedmodel_dir=output_saved_model_directory,
-      checkpoint_path=checkpoint_path,
-      timestamped=False)
-
-  ckpt = tf.train.Checkpoint(model=export_module.model)
-  ckpt.save(os.path.join(output_checkpoint_directory, 'ckpt'))
-  train_utils.serialize_config(params, export_dir)
\ No newline at end of file