*Last updated: 2023-03-16.*
# tf_quant_finance.rates.analytics.swap.rate_leg_cashflows
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Computes cashflows for a batch or interest rate legs.
```python
tf_quant_finance.rates.analytics.swap.rate_leg_cashflows(
coupon_rates, notional, daycount_fractions, dtype=None, name=None
)
```
#### Example
```python
coupon_rates = [[0.1, 0.1, 0.1], [0.02, 0.12, 0.14]]
notional = 1000
daycount_fractions = [[1, 1, 1], [1, 2, 1]]
rate_leg_cashflows(
coupon_rates, notional, daycount_fractions, dtype=tf.float64)
# Expected:
# [[100.0, 100.0, 100.0],
# [ 20.0, 240.0, 140.0]]
```
#### Args:
* `coupon_rates`: A real `Tensor` of shape `batch_shape + [num_cashflows]`,
where `num_cashflows` is the number of cashflows for each batch element.
Coupon rates for each cashflow of the leg. Can be a scalar for a fixed
leg or represent forward rates for a floating leg.
* `notional`: A `Tensor` of the same `dtype` as `coupon_rates` and of
compatible shape. Notional amount for each cashflow.
* `daycount_fractions`: A `Tensor` of the same `dtype` as `coupon_rates` and of
compatible shape. Year fractions for the coupon accrual.
* `dtype`: `tf.Dtype`. If supplied the dtype for the input and output `Tensor`s.
Default value: None which maps to the default dtype inferred from
`coupon_rates`.
* `name`: Python str. The name to give to the ops created by this function.
Default value: None which maps to 'rate_leg_cashflows'.
#### Returns:
A `Tensor` of the same `dtype` as `coupon_rates` and of shape
`batch_shape + [num_cashflows]`.