Merge branch 'main' into hls4ml-optimization-api-part-1

Author: bo3z

.github/workflows/build-sphinx.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         fetch-depth: 0
         ref: ${{ github.event.pull_request.head.sha }}

.github/workflows/pre-commit.yml

@@ -16,7 +16,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           submodules: recursive
 

.github/workflows/pypi-publish.yml

@@ -12,7 +12,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - name: Checkout source
-      uses: actions/checkout@v3
+      uses: actions/checkout@v4
       with:
         submodules: recursive
         fetch-depth: 0

.github/workflows/test-sphinx.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         fetch-depth: 0
         ref: ${{ github.event.pull_request.head.sha }}

.github/workflows/update-branch-on-pr.yml

@@ -9,7 +9,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - name: Checkout repo
-      uses: actions/checkout@v3
+      uses: actions/checkout@v4
       if: ${{ github.event.pull_request.head.repo.full_name != github.event.pull_request.base.repo.full_name && github.event.label.name == 'please test' }}
       with:
         ref: ${{ github.event.pull_request.head.sha }}

.gitignore

@@ -13,3 +13,4 @@ docs/_build
 docs/autodoc/*
 hls4mlprj_*
 *~
+*.ipynb_checkpoints/

.gitlab-ci.yml

@@ -5,7 +5,7 @@ stages:
 
 generator:
   stage: generate
-  image: python:3.7-alpine
+  image: python:3.8-alpine
   tags:
     - docker
   before_script:

.pre-commit-config.yaml

@@ -2,7 +2,7 @@ exclude: (^hls4ml\/templates\/(vivado|quartus)\/(ap_types|ac_types)\/|^test/pyte
 
 repos:
 - repo: https://github.com/psf/black
-  rev: 23.3.0
+  rev: 23.7.0
   hooks:
   - id: black
     language_version: python3
@@ -30,18 +30,18 @@ repos:
     args: ["--profile", "black", --line-length=125]
 
 - repo: https://github.com/asottile/pyupgrade
-  rev: v3.4.0
+  rev: v3.10.1
   hooks:
   - id: pyupgrade
     args: ["--py36-plus"]
 
 - repo: https://github.com/asottile/setup-cfg-fmt
-  rev: v2.3.0
+  rev: v2.4.0
   hooks:
   - id: setup-cfg-fmt
 
 - repo: https://github.com/pycqa/flake8
-  rev: 6.0.0
+  rev: 6.1.0
   hooks:
   - id: flake8
     exclude: docs/conf.py

contrib/garnet.py

@@ -313,35 +313,36 @@ def _setup_transforms(self, n_aggregators, n_filters, n_propagate):
                     name=('Fout%d' % it),
                 )
 
-                # Check for correctness. This commented out because pre-commit showed it was unused.
-
-                # if self._output_activation is None or self._output_activation == "linear":
-                #     output_activation_transform = (QActivation("quantized_bits(%i, %i)"
-                #                                    % (self._total_bits, self._int_bits)))
-                # else:
-                #     output_activation_transform = QActivation(
-                #         "quantized_%s(%i, %i)" % (self._output_activation, self._total_bits, self._int_bits)
-                #     )
+                if self._output_activation is None or self._output_activation == "linear":
+                    output_activation_transform = QActivation("quantized_bits(%i, %i)" % (self._total_bits, self._int_bits))
+                else:
+                    output_activation_transform = QActivation(
+                        "quantized_%s(%i, %i)" % (self._output_activation, self._total_bits, self._int_bits)
+                    )
             else:
                 input_feature_transform = NamedDense(p, name=('FLR%d' % it))
                 output_feature_transform = NamedDense(f, name=('Fout%d' % it))
-                # output_activation_transform = keras.layers.Activation(self._output_activation)
+                output_activation_transform = keras.layers.Activation(self._output_activation)
 
             aggregator_distance = NamedDense(a, name=('S%d' % it))
 
-            self._transform_layers.append((input_feature_transform, aggregator_distance, output_feature_transform))
+            self._transform_layers.append(
+                (input_feature_transform, aggregator_distance, output_feature_transform, output_activation_transform)
+            )
 
         self._sublayers = sum((list(layers) for layers in self._transform_layers), [])
 
     def _build_transforms(self, data_shape):
-        for in_transform, d_compute, out_transform in self._transform_layers:
+        for in_transform, d_compute, out_transform, act_transform in self._transform_layers:
             in_transform.build(data_shape)
             d_compute.build(data_shape)
             if self._simplified:
-                out_transform.build(data_shape[:2] + (d_compute.units * in_transform.units,))
+                act_transform.build(out_transform.build(data_shape[:2] + (d_compute.units * in_transform.units,)))
             else:
-                out_transform.build(
-                    data_shape[:2] + (data_shape[2] + d_compute.units * in_transform.units + d_compute.units,)
+                act_transform.build(
+                    out_transform.build(
+                        data_shape[:2] + (data_shape[2] + d_compute.units * in_transform.units + d_compute.units,)
+                    )
                 )
 
             data_shape = data_shape[:2] + (out_transform.units,)

docs/requirements.txt

@@ -7,7 +7,6 @@ pandas
 pyyaml
 seaborn
 setuptools_scm[toml]>=5
-six
 sphinx>=3.2.1
 sphinx_contributors
 sphinx_github_changelog