From 705ec54538bf938884eb777f6215358afca4b728 Mon Sep 17 00:00:00 2001
From: Remi Cresson <remi.cresson@inrae.fr>
Date: Mon, 19 Sep 2022 19:23:23 +0200
Subject: [PATCH 1/2] REFAC: move _is_chief() and cropped_tensor_name() into
model.py
---
otbtf/model.py | 35 ++++++++++++++++++++++++++++++++++-
otbtf/utils.py | 34 ----------------------------------
2 files changed, 34 insertions(+), 35 deletions(-)
diff --git a/otbtf/model.py b/otbtf/model.py
index a6306e27..38fc6ca6 100644
--- a/otbtf/model.py
+++ b/otbtf/model.py
@@ -3,7 +3,6 @@
import abc
import logging
import tensorflow
-from otbtf.utils import _is_chief, cropped_tensor_name
class ModelBase(abc.ABC):
@@ -165,3 +164,37 @@ class ModelBase(abc.ABC):
model_simplified = tensorflow.keras.Model(inputs=inputs, outputs=outputs,
name=self.__class__.__name__ + '_simplified')
tensorflow.keras.utils.plot_model(model_simplified, output_path)
+
+
+def _is_chief(strategy):
+ """
+ Tell if the current worker is the chief.
+
+ :param strategy: strategy
+ :return: True if the current worker is the chief, False else
+ """
+ # Note: there are two possible `TF_CONFIG` configuration.
+ # 1) In addition to `worker` tasks, a `chief` task type is use;
+ # in this case, this function should be modified to
+ # `return task_type == 'chief'`.
+ # 2) Only `worker` task type is used; in this case, worker 0 is
+ # regarded as the chief. The implementation demonstrated here
+ # is for this case.
+ # For the purpose of this Colab section, the `task_type is None` case
+ # is added because it is effectively run with only a single worker.
+
+ if strategy.cluster_resolver: # this means MultiWorkerMirroredStrategy
+ task_type, task_id = strategy.cluster_resolver.task_type, strategy.cluster_resolver.task_id
+ return (task_type == 'chief') or (task_type == 'worker' and task_id == 0) or task_type is None
+ # strategy with only one worker
+ return True
+
+
+def cropped_tensor_name(tensor_name, crop):
+ """
+ A name for the padded tensor
+ :param tensor_name: tensor name
+ :param pad: pad value
+ :return: name
+ """
+ return "{}_crop{}".format(tensor_name, crop)
diff --git a/otbtf/utils.py b/otbtf/utils.py
index 7aa777af..069638a5 100644
--- a/otbtf/utils.py
+++ b/otbtf/utils.py
@@ -63,37 +63,3 @@ def read_as_np_arr(gdal_ds, as_patches=True, dtype=None):
buffer = buffer.astype(dtype)
return buffer
-
-
-def _is_chief(strategy):
- """
- Tell if the current worker is the chief.
-
- :param strategy: strategy
- :return: True if the current worker is the chief, False else
- """
- # Note: there are two possible `TF_CONFIG` configuration.
- # 1) In addition to `worker` tasks, a `chief` task type is use;
- # in this case, this function should be modified to
- # `return task_type == 'chief'`.
- # 2) Only `worker` task type is used; in this case, worker 0 is
- # regarded as the chief. The implementation demonstrated here
- # is for this case.
- # For the purpose of this Colab section, the `task_type is None` case
- # is added because it is effectively run with only a single worker.
-
- if strategy.cluster_resolver: # this means MultiWorkerMirroredStrategy
- task_type, task_id = strategy.cluster_resolver.task_type, strategy.cluster_resolver.task_id
- return (task_type == 'chief') or (task_type == 'worker' and task_id == 0) or task_type is None
- # strategy with only one worker
- return True
-
-
-def cropped_tensor_name(tensor_name, crop):
- """
- A name for the padded tensor
- :param tensor_name: tensor name
- :param pad: pad value
- :return: name
- """
- return "{}_crop{}".format(tensor_name, crop)
--
GitLab
From abd9d433ba746aac22e29b98b4118fd5053c512e Mon Sep 17 00:00:00 2001
From: Remi Cresson <remi.cresson@inrae.fr>
Date: Mon, 19 Sep 2022 19:33:33 +0200
Subject: [PATCH 2/2] ADD: warning when otbtf is imported w/o GDAL
---
otbtf/__init__.py | 9 ++++++---
1 file changed, 6 insertions(+), 3 deletions(-)
diff --git a/otbtf/__init__.py b/otbtf/__init__.py
index 5321e3db..6ee17f9e 100644
--- a/otbtf/__init__.py
+++ b/otbtf/__init__.py
@@ -20,9 +20,12 @@
"""
OTBTF python module
"""
+try:
+ from otbtf.utils import read_as_np_arr, gdal_open
+ from otbtf.dataset import Buffer, PatchesReaderBase, PatchesImagesReader, IteratorBase, RandomIterator, Dataset, \
+ DatasetFromPatchesImages
+except ImportError:
+ print("Warning: otbtf.utils and otbtf.dataset were not imported. Using OTBTF without GDAL.")
-from otbtf.utils import read_as_np_arr, gdal_open
-from otbtf.dataset import Buffer, PatchesReaderBase, PatchesImagesReader, IteratorBase, RandomIterator, Dataset, \
- DatasetFromPatchesImages
from otbtf.tfrecords import TFRecords
from otbtf.model import ModelBase
--
GitLab