sciwork demo code

Author: dboyliao

.gitignore

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+uTensor

.vscode/settings.json

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+{
+    "python.pythonPath": ".venv/bin/python"
+}

gen_inputs_header.py

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+import tensorflow as tf
+import numpy as np
+import argparse
+
+
+def main(num_samples=5, seed=None):
+    mnist = tf.keras.datasets.mnist
+    (_, _), (x_test, y_test) = mnist.load_data()
+    x_test = x_test / 255.0
+
+    # Add a channels dimension
+    x_test = x_test[..., np.newaxis]
+    total_N = y_test.shape[0]
+    num_samples = min(num_samples, total_N)
+    np.random.seed(seed)
+    idxs = np.random.choice(range(total_N), num_samples, replace=False)
+    x_selected = x_test[idxs].reshape(num_samples, -1)
+    y_selected = y_test[idxs]
+    with open("input_image.h", "w") as fid:
+        fid.write("// clang-format off\n")
+        fid.write(
+            "const float arr_input_image[{}][{}] = {{\n".format(
+                x_selected.shape[0], x_selected.shape[1]
+            )
+        )
+        for i in range(x_selected.shape[0]):
+            arr = x_selected[i]
+            fid.write("    {{ {}".format(", ".join(map(str, arr))))
+            fid.write("},\n")
+        fid.write("};\n")
+        fid.write("const int ref_labels[{}] = {{\n".format(y_selected.shape[0]))
+        fid.write("    " + ", ".join(map(str, y_selected)) + "\n")
+        fid.write("};\n\n")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--num-samples",
+        dest="num_samples",
+        default=5,
+        help="the number of inpute samples [default: %(default)s]",
+        type=int,
+        metavar="INTEGER",
+    )
+    parser.add_argument("--seed", default=None, help="the random seed", type=int)
+    args = vars(parser.parse_args())
+    main(**args)