test transpose1d

Author: jmduarte

test/pytest/test_transpose.py

@@ -0,0 +1,47 @@
+from hls4ml.converters.keras_to_hls import keras_to_hls
+import pytest
+import hls4ml
+import numpy as np
+from sklearn.metrics import accuracy_score
+import tensorflow as tf
+from tensorflow.keras.models import model_from_json, Model
+from tensorflow.keras.layers import Input, Permute
+import yaml
+
+@pytest.fixture(scope='module')
+def data():
+    X = np.random.rand(1, 2, 3)
+    return X
+
+@pytest.fixture(scope='module')
+def keras_model():
+    inp = Input(shape=(2, 3), name='input_1')
+    out = Permute((2, 1))(inp)
+    model = Model(inputs=inp, outputs=out)
+    return model
+
+@pytest.fixture      
+@pytest.mark.parametrize('io_type', ['io_parallel',
+                                     'io_stream'])
+def hls_model(keras_model, io_type):
+    hls_config = hls4ml.utils.config_from_keras_model(keras_model, 
+                                                      default_precision='ap_fixed<16,3,AP_RND_CONV,AP_SAT>',
+                                                      granularity='name')
+    hls_model = hls4ml.converters.convert_from_keras_model(keras_model,
+                                                           hls_config=hls_config,
+                                                           io_type=io_type,
+                                                           output_dir='hls4mlprj_transpose_{}'.format(io_type))
+
+    hls_model.compile()
+    return hls_model
+
+@pytest.mark.parametrize('io_type', ['io_parallel', 
+                                     'io_stream'])
+def test_accuracy(data, keras_model, hls_model):
+    X = data
+    model = keras_model
+    # model under test predictions and accuracy
+    y_keras = model.predict(X)
+    y_hls4ml   = hls_model.predict(X).reshape(y_keras.shape)
+    # "accuracy" of hls4ml predictions vs keras
+    np.testing.assert_allclose(y_keras, y_hls4ml, rtol=0, atol=1e-04, verbose=True)