コード例 #1
0
    def test_fc_layer_1_forward(self):
        print('\n==================================')
        print('       Test FC layer forward      ')
        print('==================================')
        np.random.seed(123)
        in_dim, out_dim = 5, 7
        x = np.random.randn(5, in_dim)
        fc_layer = FCLayer(in_dim, out_dim)

        fc_out = fc_layer.forward(x)
        correct_out = [[
            -2.61587108, -1.61266299, -0.0669421, -2.54145585, 1.28682999,
            1.1125263, -0.68786543
        ],
                       [
                           4.32876618, 2.55437969, -2.24952545, 1.52993583,
                           -3.05818339, -3.06667247, -0.76003621
                       ],
                       [
                           -0.09513516, -1.28239277, -1.76747871, -1.4526619,
                           0.94121269, 0.3876754, 0.23826321
                       ],
                       [
                           -0.57981942, -2.07002539, 0.17966919, 0.89441346,
                           0.64115475, 1.20433427, 0.8938306
                       ],
                       [
                           0.27645953, 0.52337315, 1.11057732, 0.96039962,
                           -3.09284442, -1.62932547, -1.67869927
                       ]]

        e = rel_error(correct_out, fc_out)
        print('Relative difference:', e)
        self.assertTrue(e <= 5e-8)
コード例 #2
0
    def test_fc_layer_2_backward(self):
        print('\n==================================')
        print('       Test FC layer backward     ')
        print('==================================')
        np.random.seed(123)
        in_dim, out_dim = 5, 7
        x = np.random.randn(5, in_dim)
        fc_layer = FCLayer(in_dim, out_dim)

        fc_out = fc_layer.forward(x)
        d_prev = np.random.randn(*fc_out.shape)
        dx = fc_layer.backward(d_prev, 0.01)
        dw = fc_layer.dw
        db = fc_layer.db

        correct_dx = [
            [-0.38227102, 1.17252013, 0.12788217, -4.28457506, 2.23774842],
            [1.39190197, 1.971887, 0.19018213, -1.17233471, -0.07123409],
            [0.3228319, 0.29698036, -1.09577096, -0.24408399, -0.85236351],
            [3.38556938, 0.8984432, -2.31575898, -0.52158556, -1.97062228],
            [-1.37065069, -0.89799099, -0.33241037, 0.8274308, 0.10209643]
        ]
        correct_dw = [[
            3.72943234, -4.14214785, 0.75059198, 1.50031574, -1.74298193,
            3.31825892, -2.45157517
        ],
                      [
                          1.57658455, 7.50683015, 3.36883864, -5.0322751,
                          1.38427174, -1.71863439, -0.59066825
                      ],
                      [
                          -6.74286032, 5.76269827, 0.07986016, -0.26893331,
                          -3.03193173, -5.36704897, 0.01743584
                      ],
                      [
                          4.00285798, -1.51490194, 2.20612597, 0.87921304,
                          -3.53759088, 1.92435603, -3.85981001
                      ],
                      [
                          -1.2963323, 0.55252352, -1.29937229, 1.89050352,
                          -0.36306998, -2.51168386, 0.3259339
                      ]]
        correct_db = [
            -1.73065675, 2.46168233, 2.06794376, -2.56596612, -1.15623993,
            0.80887778, -1.34400948
        ]

        dx_e = rel_error(correct_dx, dx)
        dw_e = rel_error(correct_dw, dw)
        db_e = rel_error(correct_db, db)

        print('Relative difference dx:', dx_e)
        print('Relative difference dw:', dw_e)
        print('Relative difference db:', db_e)

        self.assertTrue(dx_e <= 5e-8)
        self.assertTrue(dw_e <= 5e-6)
        self.assertTrue(db_e <= 5e-8)
コード例 #3
0
    def test_fc_layer_3_update(self):
        print('\n==================================')
        print('        Test fc layer update      ')
        print('==================================')
        np.random.seed(123)
        in_dim, out_dim = 5, 7
        x = np.random.randn(5, in_dim)
        fc_layer = FCLayer(in_dim, out_dim)

        before_w = np.array(fc_layer.w, copy=True)
        before_b = np.array(fc_layer.b, copy=True)

        fc_out = fc_layer.forward(x)
        d_prev = np.random.randn(*fc_out.shape)
        dx = fc_layer.backward(d_prev, 0.01)
        fc_layer.update(learning_rate=0.05)

        after_w = fc_layer.w
        after_b = fc_layer.b

        correct_before_w = [[
            -0.40334947, 0.5737037, -0.90357701, -0.08858724, -0.54502165,
            -0.16166788, -1.76998316
        ],
                            [
                                -1.12041591, -0.44264123, 0.58657875,
                                -0.10981685, 0.00179992, 0.43527026,
                                -0.55626763
                            ],
                            [
                                0.17938167, -0.50935851, -1.09267413,
                                -0.24722674, 0.36290669, 0.21414252,
                                -0.00748226
                            ],
                            [
                                1.51306465, 0.26114858, 0.619007, 1.41552614,
                                -0.81845142, -0.65698735, 1.10282044
                            ],
                            [
                                -0.50473919, 0.01877332, 0.6762948, 0.56333218,
                                1.10988747, 0.94592841, 0.67634331
                            ]]
        correct_before_b = [0., 0., 0., 0., 0., 0., 0.]

        correct_after_w = [[
            -0.58982108, 0.78081109, -0.94110661, -0.16360302, -0.45787255,
            -0.32758083, -1.6474044
        ],
                           [
                               -1.19924514, -0.81798274, 0.41813681,
                               0.14179691, -0.06741367, 0.52120198, -0.52673421
                           ],
                           [
                               0.51652469, -0.79749342, -1.09666714,
                               -0.23378007, 0.51450328, 0.48249497, -0.00835405
                           ],
                           [
                               1.31292175, 0.33689368, 0.5087007, 1.37156548,
                               -0.64157188, -0.75320515, 1.29581094
                           ],
                           [
                               -0.43992258, -0.00885285, 0.74126341,
                               0.46880701, 1.12804097, 1.0715126, 0.66004662
                           ]]
        correct_after_b = [
            0.08653284, -0.12308412, -0.10339719, 0.12829831, 0.057812,
            -0.04044389, 0.06720047
        ]

        before_w_e = rel_error(correct_before_w, before_w)
        before_b_e = rel_error(correct_before_b, before_b)
        after_w_e = rel_error(correct_after_w, after_w)
        after_b_e = rel_error(correct_after_b, after_b)

        print('Relative difference before_w:', before_w_e)
        print('Relative difference before_b:', before_b_e)
        print('Relative difference after_w :', after_w_e)
        print('Relative difference after_b :', after_b_e)

        self.assertTrue(before_w_e <= 5e-6)
        self.assertTrue(before_b_e <= 1e-11)
        self.assertTrue(after_w_e <= 5e-7)
        self.assertTrue(after_b_e <= 5e-8)
コード例 #4
0
ファイル: Checker.py プロジェクト: siisee11/ML-numpy
print('Difference pool out: ', (correct_pooled - pooled).sum())
print('Difference d_pool: ', (correct_d_pool - d_pool).sum())
print()

# ===========================================================================

print(
    '=============================== 5. FC Layer ==============================='
)
fc_layer = FCLayer(2, 2)
fc_layer.W = np.array([[-2.0, 1.25], [0.01, -1.0]])
fc_layer.b = np.array([-1.0, 1.0])
temp6 = np.array([[-1, 3], [0.0, 1.0]])
temp7 = np.array([[-1, 3], [0.0, 1.0]])

fc_forward = fc_layer.forward(temp6)
fc_backward = fc_layer.backward(temp7)
fc_dW = fc_layer.dW
fc_db = fc_layer.db

# Difference should be
# => in the order of 1e-15 for forward
# => 0.0 for Backward, dW, db
print('Forward difference: ', (correct_fc_forward - fc_forward).sum())
print('Backward difference: ', (correct_fc_backward - fc_backward).sum())
print('dW difference: ', (correct_fc_dW - fc_dW).sum())
print('db difference: ', (correct_fc_db - fc_db).sum())
print()

# ===========================================================================