class_docstr: Represents a collection of Eurodollar futures contracts.
  
  Interest rate futures are exchange traded futures contracts on Libor rates
  liquidly traded on exchanges such as Chicago Mercantile Exchange (CME) or
  London International Financial Futures and Options Exchange (LIFFE). Contracts
  on CME on a US Dollar spot Libor rate are called Eurodollar (ED) Futures.
  An ED future contract at maturity T settles at the price
  100 * (1 - F(T, T1, T2))
  where F(T, T1, T2) is the spot Libor rate at time T with start T1 and
  maturity T2 (ref [1]).
  
  The EurodollarFutures class can used to create and price multiple contracts
  simultaneously. However all contracts within an object must be priced using a
  common reference curve.
  
  #### Example:
  The following example illustrates the construction of an ED future 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
  
  dtype = np.float64
  notional = 1.
  expiry_date = dates.convert_to_date_tensor([(2021, 2, 8)])
  valuation_date = dates.convert_to_date_tensor([(2020, 2, 8)])
  rate_term = dates.periods.months(3)
  
  edfuture = instruments.EurodollarFutures(
      expiry_date, notional, rate_term=rate_term, dtype=dtype)
  
  curve_dates = valuation_date + dates.periods.months([1, 2, 3, 12, 24, 60])
  reference_curve = instruments.RateCurve(
      curve_dates,
      np.array([0.02, 0.025, 0.0275, 0.03, 0.035, 0.0325], dtype=dtype),
      dtype=dtype)
  
  market = instruments.InterestRateMarket(reference_curve=reference_curve,
                                          discount_curve=None)
  
  price = self.evaluate(edfuture.price(valuation_date, market))
  
  #### References:
  [1]: Leif B.G. Andersen and Vladimir V. Piterbarg. Interest Rate Modeling,
      Volume I: Foundations and Vanilla Models. Chapter 5. 2010.
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docstr: Returns the price of the contract on the valuation date.
  
  Args:
    valuation_date: A scalar `DateTensor` specifying the date on which
      valuation is being desired.
    market: A namedtuple of type `InterestRateMarket` which contains the
      necessary information for pricing the FRA instrument.
    model: Reserved for future use.
  
  Returns:
    A Rank 1 `Tensor` of real type containing the modeled price of each
    futures contract based on the input market data.
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code: def price(self, valuation_date, market, model=None):
      """Returns the price of the contract on the valuation date.
  
      Args:
        valuation_date: A scalar `DateTensor` specifying the date on which
          valuation is being desired.
        market: A namedtuple of type `InterestRateMarket` which contains the
          necessary information for pricing the FRA instrument.
        model: Reserved for future use.
  
      Returns:
        A Rank 1 `Tensor` of real type containing the modeled price of each
        futures contract based on the input market data.
      """
  
      del model, valuation_date
  
      reference_curve = market.reference_curve
  
      fwd_rate = reference_curve.get_forward_rate(
          self._accrual_start_date,
          self._accrual_end_date,
          self._daycount_fraction,
      )
  
      return 100.0 * self._contract_notional * (1.0 - fwd_rate)
  
imports: import tensorflow.compat.v2
  from tf_quant_finance import datetime
  from tf_quant_finance.experimental.instruments import rates_common
label_desc: Use image node_id 2 for calling the EurodollarFutures obj's underlying member method code with example usage: obj.price(valuation_date, market, model) and returns: unknown