Bump versions

Author: abdulfatir

pyproject.toml

@@ -1,25 +1,21 @@
 [project]
 name = "chronos-forecasting"
-version = "1.5.2"
+version = "1.5.3"
 authors = [
-  { name="Abdul Fatir Ansari", email="[email protected]" },
-  { name="Lorenzo Stella", email="[email protected]" },
-  { name="Caner Turkmen", email="[email protected]" },
+  { name = "Abdul Fatir Ansari", email = "[email protected]" },
+  { name = "Lorenzo Stella", email = "[email protected]" },
+  { name = "Caner Turkmen", email = "[email protected]" },
 ]
 description = "Chronos: Pretrained models for time series forecasting"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"
-dependencies = [
-    "torch>=2.0,<3",         # package was tested on 2.2
-    "transformers>=4.48,<5",
-    "accelerate>=0.32,<2",
-]
+dependencies = ["torch>=2.0,<3", "transformers>=4.48,<5", "accelerate>=0.32,<2"]
 classifiers = [
-    "Programming Language :: Python :: 3",
-    "License :: OSI Approved :: Apache Software License",
-    "Operating System :: OS Independent",
-    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+  "Programming Language :: Python :: 3",
+  "License :: OSI Approved :: Apache Software License",
+  "Operating System :: OS Independent",
+  "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 
 [build-system]
@@ -30,10 +26,19 @@ build-backend = "hatchling.build"
 packages = ["src/chronos"]
 
 [project.optional-dependencies]
-test = ["pytest~=8.0", "numpy~=1.21"]
+test = ["pytest~=8.0", "numpy~=2.0"]
 typecheck = ["mypy~=1.9"]
-training = ["gluonts[pro]~=0.15", "numpy~=1.21", "datasets~=2.18", "typer", "typer-config", "joblib", "scikit-learn", "tensorboard"]
-evaluation = ["gluonts[pro]~=0.15", "numpy~=1.21", "datasets~=2.18", "typer"]
+training = [
+  "gluonts[pro]~=0.15",
+  "numpy~=2.0",
+  "datasets~=3.0",
+  "typer",
+  "typer-config",
+  "joblib",
+  "scikit-learn",
+  "tensorboard",
+]
+evaluation = ["gluonts[pro]~=0.15", "numpy~=2.0", "datasets~=3.0", "typer"]
 
 [project.urls]
 Homepage = "https://github.com/amazon-science/chronos-forecasting"
@@ -42,3 +47,11 @@ Paper = "https://arxiv.org/abs/2403.07815"
 
 [tool.mypy]
 ignore_missing_imports = true
+
+[tool.ruff]
+line-length = 88
+lint.ignore = [
+  "E501", # Line too long
+  "E731", # Do not assign a `lambda` expression, use a `def`
+  "E722", # Do not use bare `except`
+]

src/chronos/chronos.py

@@ -302,9 +302,9 @@ def encode(
             A tensor of encoder embeddings with shape
             (batch_size, sequence_length, d_model).
         """
-        assert (
-            self.config.model_type == "seq2seq"
-        ), "Encoder embeddings are only supported for encoder-decoder models"
+        assert self.config.model_type == "seq2seq", (
+            "Encoder embeddings are only supported for encoder-decoder models"
+        )
         assert hasattr(self.model, "encoder")
 
         return self.model.encoder(

src/chronos/chronos_bolt.py

@@ -179,7 +179,6 @@ def __init__(self, config: T5Config):
         encoder_config = copy.deepcopy(config)
         encoder_config.is_decoder = False
         encoder_config.use_cache = False
-        encoder_config.is_encoder_decoder = False
         self.encoder = T5Stack(encoder_config, self.shared)
 
         self._init_decoder(config)
@@ -381,7 +380,6 @@ def forward(
     def _init_decoder(self, config):
         decoder_config = copy.deepcopy(config)
         decoder_config.is_decoder = True
-        decoder_config.is_encoder_decoder = False
         decoder_config.num_layers = config.num_decoder_layers
         self.decoder = T5Stack(decoder_config, self.shared)