add test for multiout test 2

fastmachinelearning · Oct 29, 2024 · 42766b5 · 42766b5
1 parent 38cf8ed
commit 42766b5
Showing 1 changed file with 44 additions and 8 deletions.
diff --git a/test/pytest/test_multiout_network.py b/test/pytest/test_multiout_network.py
@@ -19,25 +19,40 @@ def model():
     return model
 
 
+@pytest.fixture(scope='module')
+def model2():
+    in1 = keras.layers.Input(shape=(24, 8))
+    in2 = keras.layers.Input(shape=(16))
+    out1 = keras.layers.Conv1D(1, 3)(in1)
+    out1 = keras.layers.Flatten()(out1)
+    out2 = keras.layers.Dense(16, activation='relu')(out1)
+    out2 = keras.layers.Add()([out2, in2])
+    out3 = keras.layers.Dense(2)(out1)
+    model = keras.models.Model(inputs=[in1, in2], outputs=[out1, out2, out3])
+    return model
+
+
 @pytest.fixture(scope='module')
 def data():
     X = np.random.normal(0, 1, (1000, 10))
     X = np.clip(X, -16, 15)
     return X
 
 
+@pytest.fixture(scope='module')
+def data2():
+    X1 = np.random.normal(0, 1, (1000, 24, 8))
+    X2 = np.random.normal(0, 1, (1000, 16))
+    X1 = np.clip(X1, -16, 15)
+    X2 = np.clip(X2, -16, 15)
+    return X1, X2
+
+
 @pytest.mark.parametrize('backend', ['Vivado', 'Quartus', 'Vitis'])
 @pytest.mark.parametrize('io_type', ['io_parallel', 'io_stream'])
-def test_multi_clone(model, data, backend: str, io_type: str):
+def test_multi_output_nn(model, data, backend: str, io_type: str):
     output_dir = str(test_root_path / f'hls4mlprj_multiout_network_{backend}_{io_type}')
     hls_config = {'Model': {'Precision': 'fixed<32,5>', 'ReuseFactor': 1}}
-    layer_config = {
-        'dense1': {'Precision': {'result': 'fixed<35,5>'}},
-        'dense2': {'Precision': {'result': 'fixed<40,5>'}},
-        'dense1_linear': {'Precision': {'result': 'fixed<35,5>'}},
-        'dense2_linear': {'Precision': {'result': 'fixed<40,5>'}},
-    }
-    hls_config['LayerName'] = layer_config
     model_hls = convert_from_keras_model(
         model, backend=backend, output_dir=output_dir, hls_config=hls_config, io_type=io_type
     )
@@ -50,3 +65,24 @@ def test_multi_clone(model, data, backend: str, io_type: str):
 
     assert np.allclose(r_hls[0], r_keras[0], atol=1e-5, rtol=0)
     assert np.allclose(r_hls[1], r_keras[1], atol=1e-5, rtol=0)
+
+
+@pytest.mark.parametrize('backend', ['Vivado', 'Quartus', 'Vitis'])
+@pytest.mark.parametrize('io_type', ['io_parallel', 'io_stream'])
+@pytest.mark.parametrize('strategy', ['latency', 'resource'])
+def test_multi_output_nn_2(model2, data2, backend: str, io_type: str, strategy: str):
+    """Cover corner case where a flatten layer is cloned multiple times, and used as model output"""
+    output_dir = str(test_root_path / f'hls4mlprj_multiout_network_2_{backend}_{io_type}_{strategy}')
+    hls_config = {'Model': {'Precision': 'fixed<32,5>', 'ReuseFactor': 1}, 'Strategy': strategy}
+
+    model_hls = convert_from_keras_model(
+        model2, backend=backend, output_dir=output_dir, hls_config=hls_config, io_type=io_type
+    )
+
+    model_hls.compile()
+    r_hls = model_hls.predict(data2)
+    r_keras = model2.predict(data2, verbose=0, batch_size=1000)
+
+    assert np.allclose(r_hls[0], r_keras[0], atol=1e-5, rtol=0)
+    assert np.allclose(r_hls[1], r_keras[1], atol=1e-5, rtol=0)
+    assert np.allclose(r_hls[2], r_keras[2], atol=1e-5, rtol=0)