VivadoAccelerator complete build test

test/pytest/baselines/VivadoAccelerator/2020.1/test_keras_api_vivadoacc_test_dense_io_parallel-VivadoAccelerator.json

@@ -0,0 +1,34 @@
+{
+    "CSynthesisReport": {
+        "TargetClockPeriod": "5.00",
+        "EstimatedClockPeriod": "4.349",
+        "BestLatency": "11",
+        "WorstLatency": "11",
+        "IntervalMin": "12",
+        "IntervalMax": "12",
+        "BRAM_18K": "1",
+        "DSP": "2",
+        "FF": "622",
+        "LUT": "1947",
+        "URAM": "0",
+        "AvailableBRAM_18K": "1824",
+        "AvailableDSP": "2520",
+        "AvailableFF": "548160",
+        "AvailableLUT": "274080",
+        "AvailableURAM": "0"
+    },
+    "VivadoSynthReport": {
+        "LUT": "47",
+        "FF": "35",
+        "BRAM_18K": "0.5",
+        "DSP48E": "2"
+    },
+    "TimingReport": {
+        "WNS": 3.988,
+        "TNS": 0.0,
+        "WHS": 0.01,
+        "THS": 0.0,
+        "WPWS": 3.5,
+        "TPWS": 0.0
+    }
+}

test/pytest/ci-template.yml

@@ -14,11 +14,14 @@
     - if [ $EXAMPLEMODEL == 1 ]; then git submodule update --init example-models; fi
     - pip install .${EXTRA_DEPS}
 
-    # set up vivado_hls command
+    # set up Vivado commands
     - mkdir -p cmd_vivado_${VIVADO_VERSION}
     - echo '#!/bin/bash' > cmd_vivado_${VIVADO_VERSION}/vivado_hls
     - echo "apptainer exec --cleanenv --env LANG=C,LC_ALL=C /cvmfs/projects.cern.ch/hls4ml/vivado/${VIVADO_VERSION} vivado_hls \"\$@\"" >> cmd_vivado_${VIVADO_VERSION}/vivado_hls
+    - echo '#!/bin/bash' > cmd_vivado_${VIVADO_VERSION}/vivado
+    - echo "apptainer exec --cleanenv --env LANG=C,LC_ALL=C /cvmfs/projects.cern.ch/hls4ml/vivado/${VIVADO_VERSION} vivado \"\$@\"" >> cmd_vivado_${VIVADO_VERSION}/vivado
     - chmod +x cmd_vivado_${VIVADO_VERSION}/vivado_hls
+    - chmod +x cmd_vivado_${VIVADO_VERSION}/vivado
     - export PATH=$PWD/cmd_vivado_${VIVADO_VERSION}:$PATH
 
     # set up vitis-run command

test/pytest/conftest.py

@@ -56,12 +56,23 @@ def synthesis_config():
         'run_synthesis': str_to_bool(os.getenv('RUN_SYNTHESIS', 'false')),
         'tools_version': {
             'Vivado': os.getenv('VIVADO_VERSION', '2020.1'),
+            'VivadoAccelerator': os.getenv('VIVADO_VERSION', '2020.1'),
             'Vitis': os.getenv('VITIS_VERSION', '2024.1'),
             'Quartus': os.getenv('QUARTUS_VERSION', 'latest'),
             'oneAPI': os.getenv('ONEAPI_VERSION', '2025.0.1'),
         },
         'build_args': {
             'Vivado': {'csim': False, 'synth': True, 'export': False},
+            # Full accelerator flow: run C/RTL synthesis, downstream Vivado synthesis, and board project/bitfile.
+            'VivadoAccelerator': {
+                'csim': False,
+                'synth': True,
+                'cosim': False,
+                'validation': False,
+                'export': True,
+                'vsynth': True,
+                'bitfile': True,
+            },
             'Vitis': {'csim': False, 'synth': True, 'export': False},
             'Quartus': {'synth': True, 'fpgasynth': False},
             'oneAPI': {'build_type': 'report', 'run': False},

test/pytest/generate_ci_yaml.py

@@ -41,6 +41,7 @@
 # Value = chunk size per CI job
 SPLIT_BY_TEST_CASE = {
     'test_keras_api': 1,
+    'test_keras_api_vivadoacc': 1,
 }
 
 

test/pytest/synthesis_helpers.py

@@ -119,13 +119,15 @@ def compare_oneapi_backend(data, baseline):
 
 COMPARE_FUNCS = {
     'Vivado': compare_vitis_backend,
+    'VivadoAccelerator': compare_vitis_backend,
     'Vitis': compare_vitis_backend,
     'oneAPI': compare_oneapi_backend,
 }
 
 
 EXPECTED_REPORT_KEYS = {
     'Vivado': {'CSynthesisReport'},
+    'VivadoAccelerator': {'CSynthesisReport'},
     'Vitis': {'CSynthesisReport'},
     'oneAPI': {'report'},
 }

test/pytest/test_keras_api_vivadoacc.py

@@ -0,0 +1,80 @@
+from pathlib import Path
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from synthesis_helpers import run_synthesis_test
+from tensorflow.keras.layers import (
+    Activation,
+    Dense,
+)
+
+import hls4ml
+
+test_root_path = Path(__file__).parent
+VIVADOACC_BOARD = 'zcu102'
+VIVADOACC_PART = 'xczu9eg-ffvb1156-2-e'
+
+
+@pytest.mark.parametrize('backend', ['VivadoAccelerator'])
+@pytest.mark.parametrize('io_type', ['io_parallel'])
+def test_dense(test_case_id, backend, io_type, synthesis_config):
+    model = tf.keras.models.Sequential()
+    model.add(
+        Dense(
+            2,
+            input_shape=(1,),
+            name='Dense',
+            use_bias=True,
+            kernel_initializer=tf.keras.initializers.RandomUniform(minval=1, maxval=10),
+            bias_initializer='zeros',
+            kernel_regularizer=None,
+            bias_regularizer=None,
+            activity_regularizer=None,
+            kernel_constraint=None,
+            bias_constraint=None,
+        )
+    )
+    model.add(Activation(activation='elu', name='Activation'))
+    model.compile(optimizer='adam', loss='mse')
+
+    X_input = np.random.rand(100, 1)
+
+    keras_prediction = model.predict(X_input)
+
+    config = hls4ml.utils.config_from_keras_model(model)
+    output_dir = str(test_root_path / test_case_id)
+    baseline_file_name = f'{test_case_id}.json'
+
+    hls_model = hls4ml.converters.convert_from_keras_model(
+        model,
+        hls_config=config,
+        output_dir=output_dir,
+        backend=backend,
+        io_type=io_type,
+        board=VIVADOACC_BOARD,
+        part=VIVADOACC_PART,
+    )
+
+    hls_model.compile()
+
+    hls_prediction = hls_model.predict(X_input)
+
+    np.testing.assert_allclose(hls_prediction, keras_prediction, rtol=1e-2, atol=0.01)
+
+    assert len(model.layers) + 1 == len(hls_model.get_layers())
+    assert list(hls_model.get_layers())[0].attributes['class_name'] == 'InputLayer'
+    assert list(hls_model.get_layers())[1].attributes['class_name'] == model.layers[0]._name
+    assert list(hls_model.get_layers())[2].attributes['class_name'] == 'ELU'
+    assert list(hls_model.get_layers())[0].attributes['input_shape'] == list(model.layers[0].input_shape[1:])
+    assert list(hls_model.get_layers())[1].attributes['n_in'] == model.layers[0].input_shape[1:][0]
+    assert list(hls_model.get_layers())[1].attributes['n_out'] == model.layers[0].output_shape[1:][0]
+    assert list(hls_model.get_layers())[2].attributes['activation'] == str(model.layers[1].activation).split()[1]
+    assert list(hls_model.get_layers())[1].attributes['activation'] == str(model.layers[0].activation).split()[1]
+
+    run_synthesis_test(
+        config=synthesis_config,
+        hls_model=hls_model,
+        baseline_file_name=baseline_file_name,
+        backend=backend,
+    )