e5de887cc58750981974397fad0a5e97dff14b03,tensornets/utils.py,,load_torch_weights,#Any#Any#Any#,137

Before Change

            val = np.transpose(val, [2, 3, 1, 0])
        if val.ndim == 2:
            val = np.transpose(val, [1, 0])
            val = np.flip(val, 0)
        values.append(val)

    for scope in scopes:
        weights = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=scope)

After Change

            val = np.transpose(val, [2, 3, 1, 0])
        if val.ndim == 2:
            val = np.transpose(val, [1, 0])
        if (val.ndim == 4) and (val.shape[3] // val.shape[2] == 32):
            values += np.split(val, 32, axis=3)
        else:
            values.append(val)

    for scope in scopes:
        weights = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=scope)
        assert len(weights) == len(values), "The sizes of symbolic and " \
                                            "actual weights do not match." \

Instances