image-recognizer/test.py

import numpy as np

# Your softmax outputs
outputs = np.array([
    [
        [
            0.90924643, 0.0, 0.26800049, 0.0, 0.14153697, 0.07644807,
            0.0, 0.63928418, 0.14899383, 0.29679539, 0.29560591, 0.46324955,
            0.38955634, 0.0, 0.05094845, 0.0, 0.0, 0.26734416, 0.0,
            0.28399383, 0.0429699, 0.68988006, 0.0, 0.0, 0.0, 0.02901288,
            0.0, 0.01076904, 0.0, 0.41230365, 0.58630857, 0.0, 0.29906131,
            0.0, 0.00339327, 0.47909497, 0.07787446, 0.0, 0.0, 0.0, 0.0,
            0.0, 0.0, 0.59843748, 0.18691183, 0.0, 0.0, 0.0, 0.84100045,
            0.24468988, 0.0144432, 0.0, 0.27832373, 0.0, 0.45574082,
            0.16037272, 0.0, 0.28562163, 0.0, 0.0, 0.44667622, 0.0, 0.0,
            0.29725156, 0.0, 0.01500714, 0.51253602, 0.18559459, 0.07919077,
            0.0, 0.15155614, 0.0, 0.16996095, 0.26832836, 0.0, 0.56057083,
            0.47535547, 0.0, 0.08280879, 0.0, 0.07266015, 0.43079376,
            0.55633086, 0.0, 0.13123258, 0.33282808, 0.0, 0.73207594, 0.0,
            0.08246748, 0.0, 0.0, 0.0, 0.03605279, 0.56645505, 0.0,
            0.66074054, 0.0, 0.0, 0.07871833, 0.0, 0.0, 0.0, 0.0,
            0.0, 0.0, 0.26077944, 0.0, 0.0, 0.19883228, 0.26075606,
            0.0, 0.55120887, 0.0, 0.0, 0.13896239, 0.8079261, 0.0
        ],
        [
            1.3890246, 0.0, 0.0176582, 0.41937874, 0.01668789, 0.08115837,
            0.0, 0.0, 0.0, 0.03283852, 0.0, 0.28331658, 0.0, 0.56971081,
            1.29951652, 0.0, 0.05585489, 0.0, 0.0, 0.0, 0.4555721, 0.0,
            0.0, 0.0, 1.13440652, 0.3462467, 0.53066361, 0.85311426,
            0.13320967, 0.61478612, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04859889,
            0.0, 0.0884254, 0.0, 0.56573542, 0.18211658, 0.0, 0.24407104,
            0.0, 0.07133323, 0.0, 0.0, 0.98712028, 0.0, 0.06996351,
            0.70575429, 0.30689567, 0.47709064, 0.07469221, 0.40548246,
            0.09671662, 0.56150121, 0.0, 0.7116001, 0.57194077, 0.0,
            0.10528511, 0.20317026, 0.03516737, 0.0, 0.0, 0.10198436,
            0.0, 0.0, 0.0, 0.35702522, 0.0, 0.0, 0.32883485, 0.0,
            0.0, 0.18996724, 0.0, 0.0, 0.0, 0.06601356, 0.0,
            0.41925782, 0.0, 0.0, 0.07929863, 0.28089351, 0.0,
            0.25405591, 0.09954264, 1.05735563, 0.0, 0.57732162, 0.0,
            0.05791431, 0.0, 0.42524903, 0.0, 0.0, 0.0, 0.0, 0.0,
            0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.13586283, 0.23484103,
            0.69677156, 0.0, 0.0, 0.08609836, 0.89882583
        ]
    ]
])

labels = [7, 2]

# Convert labels to one-hot encoding
num_classes = 10
labels_one_hot = np.zeros((len(labels), num_classes))
for i, label in enumerate(labels):
    labels_one_hot[i, label] = 1

# Calculate the loss derivative
loss_derivative = outputs - labels_one_hot

print("Loss Derivative:")
print(loss_derivative)