fix: base and trainer save & from pretrained

Author: LongxingTan

.github/workflows/codeql-analysis.yml

@@ -12,9 +12,9 @@ jobs:
       runs-on: ubuntu-latest
       steps:
         - name: Checkout
-          uses: actions/checkout@v2
+          uses: actions/checkout@v4
         - name: Set up Python 3.8
-          uses: actions/setup-python@v2
+          uses: actions/setup-python@v5
           with:
             python-version: 3.8
         - name: Install Black
@@ -27,9 +27,9 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
       - name: Set up Python 3.8
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
           python-version: 3.8
       - name: Install isort
@@ -43,8 +43,8 @@ jobs:
     timeout-minutes: 10
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
+        uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: 3.8
 
@@ -59,8 +59,8 @@ jobs:
     timeout-minutes: 10
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
+        uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: 3.8
       - name: Install dependencies

.github/workflows/lint.yml

@@ -45,25 +45,17 @@ jobs:
         shell: bash
         run: poetry config virtualenvs.in-project true
 
-      - name: Set up cache
-        uses: actions/cache@v4
-        id: cache
-        with:
-          path: .venv
-          key: venv-${{ runner.os }}-${{ steps.full-python-version.outputs.version }}-${{ hashFiles('**/poetry.lock') }}
-
-      - name: Ensure cache is healthy
-        if: steps.cache.outputs.cache-hit == 'true'
-        shell: bash
-        run: poetry run pip --version >/dev/null 2>&1 || rm -rf .venv
-
-      - name: Upgrade pip
+      - name: Check for healthy virtualenv manually
         shell: bash
-        run: poetry run python -m pip install pip -U
+        run: |
+          if [ -d .venv ]; then
+            poetry run pip --version >/dev/null 2>&1 || rm -rf .venv
+          fi
 
       - name: Install dependencies
         shell: bash
         run: |
+          poetry run python -m pip install pip -U
           poetry install --no-interaction --no-root
           poetry run python -m pip install tensorflow==${{ matrix.tf-version }}
           poetry run python -m pip install matplotlib
@@ -102,13 +94,11 @@ jobs:
         with:
           python-version: '3.10'
 
-      - name: Cache pip
-        uses: actions/cache@v4
-        with:
-          path: ~/.cache/pip
-          key: ${{ runner.os }}-pip-${{ hashFiles('docs/requirements_docs.txt') }}
-          restore-keys: |
-            ${{ runner.os }}-pip-
+      - name: Create pip cache directory manually
+        run: |
+          CACHE_DIR="$HOME/.cache/pip"
+          mkdir -p "$CACHE_DIR"
+          echo "Using manual pip cache at $CACHE_DIR"
 
       - name: Install dependencies
         run: |

.github/workflows/test.yml

@@ -3,14 +3,14 @@
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v4.2.0
     hooks:
     - id: trailing-whitespace
     - id: end-of-file-fixer
     - id: check-yaml
     - id: check-ast
   - repo: https://github.com/PyCQA/flake8
-    rev: "3.9.2"
+    rev: "5.0.4"
     hooks:
     - id: flake8
       exclude: 'tests|.venv|docs'

.pre-commit-config.yaml

@@ -1,22 +1,24 @@
-.PHONY: style test docs pre-release
+.PHONY: style test docs pre-release help
 
-check_dirs := tfts examples tests
+# Directories to run style checks on
+CHECK_DIRS := tfts examples tests
 
-# run checks on all files and potentially modifies some of them
-
-style:
-	black $(check_dirs)
-	isort $(check_dirs)
-	flake8
+## Format code and run linting tools
+style:  ## Run formatters and linters (black, isort, flake8, pre-commit)
+	black $(CHECK_DIRS)
+	isort $(CHECK_DIRS)
+	flake8 $(check_dirs)
 	pre-commit run --all-files
 
-# run tests for the library
-
-test:
-	python -m unittest
+## Run all unit tests
+test:  ## Run unit tests using unittest
+	python -m unittest discover
 
-# run tests for the docs
-
-docs:
+## Build the documentation
+docs:  ## Build HTML documentation using Sphinx
 	make -C docs clean M=$(shell pwd)
 	make -C docs html M=$(shell pwd)
+
+## Display help for make targets
+help:  ## Show this help
+	@awk 'BEGIN {FS = ":.*##"; printf "\nUsage:\n  make \033[33m<target>\033[0m\n\nTargets:\n"} /^[a-zA-Z\/_-]+:.*?##/ { printf "  \033[36m%-20s\033[0m %s\n", $$1, $$2 }' $(MAKEFILE_LIST)

Makefile

@@ -5,7 +5,7 @@ coverage:
   status:
     project:
       default:
-        threshold: 1%
+        threshold: 3%
 
     patch:
       default:

codecov.yml

@@ -1,4 +1,4 @@
-From tensorflow/tensorflow:2.8.3-gpu
+From tensorflow/tensorflow:2.16.1-gpu
 
 RUN apt-get update
 RUN apt-get install -y libgl1-mesa-dev wget vim python3.8

docker/Dockerfile

@@ -12,7 +12,7 @@ cloudpickle
 
 pandas >= 1.3
 numpy < 2
-tensorflow==2.10.0
+tensorflow==2.16.1
 matplotlib
 optuna>=2.0
 scikit-learn>0.23

docs/requirements_docs.txt

@@ -44,6 +44,30 @@ The tfts library supports the SOTA deep learning models for time series.
 - `TFTS Seq2Seq model <https://github.com/LongxingTan/Data-competitions/tree/master/tianchi-enso-prediction>`_ wins the 4th place in `Alibaba Tianchi ENSO prediction <https://tianchi.aliyun.com/competition/entrance/531871/introduction>`_
 - :ref:`Learn more models <models>`
 
+.. code-block:: python
+
+   import tensorflow as tf
+   from tfts import AutoConfig, AutoModel
+
+
+   def build_model(use_model, input_shape):
+      inputs = tf.keras.layers.Input(input_shape)
+      config = AutoConfig.for_model(use_model)
+
+      backbone = AutoModel.from_config(config)
+      outputs = backbone(inputs)
+      model = tf.keras.Model(inputs, outputs=outputs)
+
+      optimizer = tf.keras.optimizers.Adam(0.003)
+      loss_fn = tf.keras.losses.MeanSquaredError()
+
+      model.compile(optimizer, loss_fn)
+      return model
+
+
+   model = build_model(use_model="bert", input_shape=(24, 3))
+   model.summary()
+
 
 Tricks
 -------

docs/source/_static/logo.svg

@@ -19,7 +19,7 @@ You can you below models in ``AutoModel``
 * WaveNet
 * Bert
 * Transformer
-* Dlinear
+* DLinear
 * NBeats
 * AutoFormer
 * Informer