Merge pull request #67 from lettercode/lettercode/upgrade-to-keras-v3

Add Keras v3 implementation

.github/workflows/python-test.yml

@@ -9,16 +9,19 @@ permissions:
   contents: read
 
 jobs:
-  build:
-
+  build_pytorch_backend:
     runs-on: ubuntu-latest
 
+    container:
+      image: pytorch/pytorch:2.3.1-cuda11.8-cudnn8-runtime
+      env:
+        KERAS_BACKEND: torch
+      volumes:
+        - my_docker_volume:/volume_mount
+
     steps:
     - uses: actions/checkout@v3
-    - name: Set up Python 3.10
-      uses: actions/setup-python@v3
-      with:
-        python-version: "3.10"
+
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
@@ -35,6 +38,35 @@ jobs:
         echo "PYTHONPATH=." >> $GITHUB_ENV
     - name: Test with pytest
       run: |
-        pytest ncps/tests/test_tf.py
-        pytest ncps/tests/test_torch.py
+        pytest ncps/tests/test_keras.py
 
+  build_tensorflow_backend:
+    runs-on: ubuntu-latest
+
+    container:
+      image: tensorflow/tensorflow:2.16.1
+      env:
+        KERAS_BACKEND: tensorflow
+      volumes:
+        - my_docker_volume:/volume_mount
+
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: set pythonpath
+      run: |
+        echo "PYTHONPATH=." >> $GITHUB_ENV
+    - name: Test with pytest
+      run: |
+        pytest ncps/tests/test_keras.py

ncps/keras/__init__.py

@@ -0,0 +1,44 @@
+# Copyright 2020-2021 Mathias Lechner
+#
+# 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
+#
+#     https://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.
+
+
+from __future__ import absolute_import
+
+from .ltc_cell import LTCCell
+from .mm_rnn import MixedMemoryRNN
+from .cfc_cell import CfCCell
+from .wired_cfc_cell import WiredCfCCell
+from .cfc import CfC
+from .ltc import LTC
+from packaging.version import parse
+
+try:
+    import keras
+except:
+    raise ImportWarning(
+        "It seems like the Keras package is not installed\n"
+        "Please run"
+        "`$ pip install keras`. \n",
+    )
+
+if parse(keras.__version__) < parse("3.0.0"):
+    raise ImportError(
+        "The Keras package version needs to be at least 3.0.0 \n"
+        "for ncps-keras to run. Currently, your Keras version is \n"
+        "{version}. Please upgrade with \n"
+        "`$ pip install --upgrade keras`. \n"
+        "You can use `pip freeze` to check afterwards that everything is "
+        "ok.".format(version=keras.__version__)
+    )
+__all__ = ["CfC", "CfCCell", "LTC", "LTCCell", "MixedMemoryRNN", "WiredCfCCell"]

ncps/keras/cfc.py

@@ -0,0 +1,99 @@
+# Copyright 2022 Mathias Lechner and Ramin Hasani
+#
+# 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
+#
+#     https://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.
+
+from typing import Union
+
+import keras
+
+import ncps
+from . import CfCCell, MixedMemoryRNN, WiredCfCCell
+
+
+@keras.utils.register_keras_serializable(package="ncps", name="CfC")
+class CfC(keras.layers.RNN):
+    def __init__(
+        self,
+        units: Union[int, ncps.wirings.Wiring],
+        mixed_memory: bool = False,
+        mode: str = "default",
+        activation: str = "lecun_tanh",
+        backbone_units: int = None,
+        backbone_layers: int = None,
+        backbone_dropout: float = None,
+        return_sequences: bool = False,
+        return_state: bool = False,
+        go_backwards: bool = False,
+        stateful: bool = False,
+        unroll: bool = False,
+        time_major: bool = False,
+        **kwargs,
+    ):
+        """Applies a `Closed-form Continuous-time <https://arxiv.org/abs/2106.13898>`_ RNN to an input sequence.
+
+        Examples::
+
+            >>> from ncps.keras import CfC
+            >>>
+            >>> rnn = CfC(50)
+            >>> x = keras.random.uniform((2, 10, 20))  # (B,L,C)
+            >>> y = rnn(x)
+
+        :param units: Number of hidden units
+        :param mixed_memory: Whether to augment the RNN by a `memory-cell <https://arxiv.org/abs/2006.04418>`_ to help learn long-term dependencies in the data (default False)
+        :param mode: Either "default", "pure" (direct solution approximation), or "no_gate" (without second gate). (default "default)
+        :param activation: Activation function used in the backbone layers (default "lecun_tanh")
+        :param backbone_units: Number of hidden units in the backbone layer (default 128)
+        :param backbone_layers: Number of backbone layers (default 1)
+        :param backbone_dropout: Dropout rate in the backbone layers (default 0)
+        :param return_sequences: Whether to return the full sequence or just the last output (default False)
+        :param return_state: Whether to return just the output of the RNN or a tuple (output, last_hidden_state) (default False)
+        :param go_backwards: If True, the input sequence will be process from back to the front (default False)
+        :param stateful: Whether to remember the last hidden state of the previous inference/training batch and use it as initial state for the next inference/training batch (default False)
+        :param unroll: Whether to unroll the graph, i.e., may increase speed at the cost of more memory (default False)
+        :param time_major: Whether the time or batch dimension is the first (0-th) dimension (default False)
+        :param kwargs:
+        """
+
+        if isinstance(units, ncps.wirings.Wiring):
+            if backbone_units is not None:
+                raise ValueError(f"Cannot use backbone_units in wired mode")
+            if backbone_layers is not None:
+                raise ValueError(f"Cannot use backbone_layers in wired mode")
+            if backbone_dropout is not None:
+                raise ValueError(f"Cannot use backbone_dropout in wired mode")
+            cell = WiredCfCCell(units, mode=mode, activation=activation)
+        else:
+            backbone_units = 128 if backbone_units is None else backbone_units
+            backbone_layers = 1 if backbone_layers is None else backbone_layers
+            backbone_dropout = 0.0 if backbone_dropout is None else backbone_dropout
+            cell = CfCCell(
+                units,
+                mode=mode,
+                activation=activation,
+                backbone_units=backbone_units,
+                backbone_layers=backbone_layers,
+                backbone_dropout=backbone_dropout,
+            )
+        if mixed_memory:
+            cell = MixedMemoryRNN(cell)
+        super(CfC, self).__init__(
+            cell,
+            return_sequences,
+            return_state,
+            go_backwards,
+            stateful,
+            unroll,
+            time_major,
+            **kwargs,
+        )