mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

This means that now, if you set a value in a context variable before `yield`, the value would still be available after `yield` (as you would intuitively expect). And it also means that you can reset the context variable with a token afterwards.

For example, this works correctly now:

```Python

keyLength || int64(numBlocks) > maxBlocks { return nil, errors.New("pbkdf2: keyLength too long") } var buf [4]byte dk := make([]byte, 0, numBlocks*hashLen) U := make([]byte, hashLen) for block := 1; block <= numBlocks; block++ { // N.B.: || means concatenation, ^ means XOR // for each block T_i = U_1 ^ U_2 ^ ... ^ U_iter // U_1 = PRF(password, salt || uint(i)) prf.Reset() prf.Write(salt) buf[0] = byte(block >> 24) buf[1] = byte(block >> 16) buf[2] = byte(block >> 8) buf[3] = byte(block) prf.Write(buf[:4])...

keyLength || int64(numBlocks) > maxBlocks { return nil, errors.New("pbkdf2: keyLength too long") } var buf [4]byte dk := make([]byte, 0, numBlocks*hashLen) U := make([]byte, hashLen) for block := 1; block <= numBlocks; block++ { // N.B.: || means concatenation, ^ means XOR // for each block T_i = U_1 ^ U_2 ^ ... ^ U_iter // U_1 = PRF(password, salt || uint(i)) prf.Reset() prf.Write(salt) buf[0] = byte(block >> 24) buf[1] = byte(block >> 16) buf[2] = byte(block >> 8) buf[3] = byte(block) prf.Write(buf[:4])...