class_docstr: Represents a batch of Caps and/or Floors.
  
  An interest Cap (or Floor) is a portfolio of call (or put) options where the
  underlying for the individual options are successive forward rates. The
  individual options comprising a Cap are called Caplets and the corresponding
  options comprising a Floor are called Floorlets. For example, a
  caplet on forward rate `F(T_i, T_{i+1})` has the following payoff at time
  `T_{i_1}`:
  
  caplet payoff = tau_i * max[F(T_i, T_{i+1}), 0]
  
  where `tau_i` is the daycount fraction.
  
  The CapAndFloor class can be used to create and price multiple Caps/Floors
  simultaneously. However all instruments within an object must be priced using
  common reference/discount curve.
  
  ### Example:
  The following example illustrates the construction of an IRS instrument and
  calculating its price.
  
  ```python
  import numpy as np
  import tensorflow as tf
  import tf_quant_finance as tff
  dates = tff.datetime
  instruments = tff.experimental.instruments
  rc = tff.experimental.instruments.rates_common
  
  dtype = np.float64
  notional = 100.0
  maturity_date = dates.convert_to_date_tensor([(2022, 1, 15)])
  start_date = dates.convert_to_date_tensor([(2021, 1, 15)])
  valuation_date = dates.convert_to_date_tensor([(2021, 1, 1)])
  
  period3m = dates.periods.months(3)
  cap = instruments.CapAndFloor(
      start_date,
      maturity_date,
      period3m,
      0.005,
      daycount_convention=instruments.DayCountConvention.ACTUAL_365,
      notional=notional,
      dtype=dtype)
  curve_dates = valuation_date + dates.periods.months([0, 3, 12, 24])
  reference_curve = instruments.RateCurve(
      curve_dates,
      np.array([0.005, 0.01, 0.015, 0.02], dtype=np.float64),
      valuation_date=valuation_date,
      dtype=np.float64)
  market = instruments.InterestRateMarket(
      reference_curve=reference_curve, discount_curve=reference_curve)
  
  price = cap.price(
            valuation_date,
            market,
            model=instruments.InterestRateModelType.LOGNORMAL_RATE,
            pricing_context=0.5)
  # Expected result: 1.0474063612452953
  ```
  
  ### References:
  [1]: Leif B.G. Andersen and Vladimir V. Piterbarg. Interest Rate Modeling,
      Volume I: Foundations and Vanilla Models. Chapter 5. 2010.
docstr: Sets up tensors for efficient computations.
code: def _setup_tensors(self):
      """Sets up tensors for efficient computations."""
      date_schedule = dates.PeriodicSchedule(
          start_date=self._start_date,
          end_date=self._maturity_date,
          tenor=self._reset_frequency,
      ).dates()
  
      # rates reset at the beginning of coupon period
      reset_dates = date_schedule[:, :-1]
      # payments occur at the end of the coupon period
      payment_dates = date_schedule[:, 1:]
      daycount_fractions = rc.get_daycount_fraction(
          date_schedule[:, :-1],
          date_schedule[:, 1:],
          self._daycount_convention,
          dtype=self._dtype,
      )
      contract_index = tf.repeat(
          tf.range(0, self._batch_size),
          payment_dates.shape.as_list()[-1],
      )
  
      self._num_caplets = daycount_fractions.shape.as_list()[-1]
      # TODO(b/152164086): Use the functionality from dates library
      self._rate_term = tf.repeat(
          tf.cast(
              reset_dates[:, 0].days_until(payment_dates[:, 0]),
              dtype=self._dtype,
          )
          / 365.0,
          self._num_caplets,
      )
      self._reset_dates = dates.DateTensor.reshape(reset_dates, [-1])
      self._payment_dates = dates.DateTensor.reshape(
          payment_dates, [-1]
      )
      self._accrual_start_dates = dates.DateTensor.reshape(
          reset_dates, [-1]
      )
      self._accrual_end_dates = dates.DateTensor.reshape(
          payment_dates, [-1]
      )
      self._daycount_fractions = tf.reshape(daycount_fractions, [-1])
      self._contract_index = contract_index
      self._strike = tf.repeat(self._strike, self._num_caplets)
      self._is_cap = tf.repeat(self._is_cap, self._num_caplets)
  
file_path: tf-quant-finance/tf_quant_finance/experimental/instruments/cap_floor.py
imports: import tensorflow.compat.v2
  from tf_quant_finance import black_scholes
  from tf_quant_finance import datetime
  from tf_quant_finance.experimental.instruments import rates_common
label_desc: Use image node_id 4 for calling the CapAndFloor obj's underlying member method code with example usage: obj._setup_tensors() without return types