Dateien nach „/“ hochladen

convert_log_to_numpy.py

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+import os
+import glob
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+
+from tensorboard.backend.event_processing import event_accumulator  # type: ignore
+import numpy as np
+
+
+def get_data(path: str = "log_cnn"):
+    acc = event_accumulator.EventAccumulator(path)
+    acc.Reload()
+
+    which_scalar = "Test Number Correct"
+    te = acc.Scalars(which_scalar)
+
+    np_temp = np.zeros((len(te), 2))
+
+    for id in range(0, len(te)):
+        np_temp[id, 0] = te[id].step
+        np_temp[id, 1] = te[id].value
+
+    print(np_temp[:, 1] / 100)
+    np_temp = np.nan_to_num(np_temp)
+    return np_temp
+
+
+for path in glob.glob("log_*"):
+    print(path)
+    data = get_data(path)
+    np.save("data_" + path + ".npy", data)

plot.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+data = np.load("data_log.npy")
+plt.loglog(
+    data[:, 0],
+    100.0 * (1.0 - data[:, 1] / 10000.0),
+    "k",
+)
+
+plt.legend()
+plt.xlabel("Epoch")
+plt.ylabel("Error [%]")
+plt.title("CIFAR10")
+plt.show()