Backports for v0.11.10 (#2655)

* Fix `validation_data` usage in torch. (#2643)

* Fix norm-freq to consider freq starts. (#2645)

* Fix call to `extractall` (#2648)

---------

Co-authored-by: Gerald Woo <[email protected]>
Co-authored-by: Jasper <[email protected]>

src/gluonts/shell/sagemaker/dyn.py

@@ -30,6 +30,8 @@
 from pathlib import Path
 from typing import Optional
 
+from gluonts.util import safe_extractall
+
 
 class Installer:
     def __init__(self, packages):
@@ -63,10 +65,12 @@ def pip_install(self, path: Path):
     def install(self, path):
         if path.is_file():
             if tarfile.is_tarfile(path):
-                self.handle_archive(tarfile.open, path)
+                self.handle_archive(tarfile.open, safe_extractall, path)
 
             elif zipfile.is_zipfile(path):
-                self.handle_archive(zipfile.ZipFile, path)
+                self.handle_archive(
+                    zipfile.ZipFile, zipfile.ZipFile.extractall, path
+                )
 
             elif path.suffix == ".py":
                 self.copy_install(path)
@@ -80,14 +84,14 @@ def install(self, path):
                 for subpath in path.iterdir():
                     self.install(subpath)
 
-    def handle_archive(self, open_fn, path):
+    def handle_archive(self, open_fn, extractall_fn, path):
         with open_fn(path) as archive:
             tempdir = tempfile.mkdtemp()
             self.cleanups.append(
                 partial(shutil.rmtree, tempdir, ignore_errors=True)
             )
 
-            archive.extractall(tempdir)
+            extractall_fn(archive, tempdir)
             self.install(Path(tempdir))
 
 

src/gluonts/time_feature/_base.py

@@ -176,7 +176,17 @@ def __call__(self, index: pd.PeriodIndex) -> np.ndarray:
 
 
 def norm_freq_str(freq_str: str) -> str:
-    return freq_str.split("-")[0]
+    base_freq = freq_str.split("-")[0]
+
+    # Pandas has start and end frequencies, e.g `AS` and `A` for yearly start
+    # and yearly end frequencies. We don't make that difference and instead
+    # rely only on the end frequencies which don't have the `S` prefix.
+    # Note: Secondly ("S") frequency exists, where we don't want to remove the
+    # "S"!
+    if len(base_freq) >= 2 and base_freq.endswith("S"):
+        return base_freq[:-1]
+
+    return base_freq
 
 
 def time_features_from_frequency_str(freq_str: str) -> List[TimeFeature]:

src/gluonts/torch/model/estimator.py

@@ -174,8 +174,8 @@ def train_model(
 
         validation_data_loader = None
 
-        with env._let(max_idle_transforms=max(len(training_data), 100)):
-            if validation_data is not None:
+        if validation_data is not None:
+            with env._let(max_idle_transforms=max(len(validation_data), 100)):
                 transformed_validation_data = transformation.apply(
                     validation_data, is_train=True
                 )

test/time_feature/test_base.py

@@ -0,0 +1,31 @@
+# Copyright 2018 Amazon.com, Inc. or its affiliates. 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.
+# A copy of the License is located at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# or in the "license" file accompanying this file. This file 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.
+
+from pandas.tseries.frequencies import to_offset
+
+from gluonts.time_feature import norm_freq_str
+
+
+def test_norm_freq_str():
+    assert norm_freq_str(to_offset("Y").name) == "A"
+    assert norm_freq_str(to_offset("YS").name) == "A"
+    assert norm_freq_str(to_offset("A").name) == "A"
+    assert norm_freq_str(to_offset("AS").name) == "A"
+
+    assert norm_freq_str(to_offset("Q").name) == "Q"
+    assert norm_freq_str(to_offset("QS").name) == "Q"
+
+    assert norm_freq_str(to_offset("M").name) == "M"
+    assert norm_freq_str(to_offset("MS").name) == "M"
+
+    assert norm_freq_str(to_offset("S").name) == "S"