RüDiger Busche, Saisai Shao, Sam Abrahams, @sanosay, Sean Papay, @seaotterman,
@selay01, Shaurya Sharma, Sriram Narayanamoorthy, Stefano Probst, @taknevski,
@tbonza, @teldridge11, Tim Anglade, Tomas Reimers, Tomer Gafner, Valentin
Iovene, Vamsi Sripathi, Viktor Malyi, Vit Stepanovs, Vivek Rane, Vlad Firoiu,
@wangg12, @will, Xiaoyu Tao, Yaroslav Bulatov, Yi Liu, Yuan (Terry) Tang,

    n_ask_attempts: (Integer) Number of times to query for valid input before
      raising an error and quitting.

  Returns:
    [String] The value of var_name after querying for input.

  Raises:
    UserInputError: if a query has been attempted n_ask_attempts times without
      success, assume that the user has made a scripting error, and will

//
// Below here we do the gradient algorithm. It works as follows:
//
// First we filter the tape to just the subset of operations we want to
// differentiate. In the process of doing so we count how many times each Tensor
// is used as an input to an op (so we know when we're done computing gradients
// for that Tensor). We also count, for each tape entry, how many of its output

# See https://docs.bazel.build/versions/main/windows.html
build:windows --features=compiler_param_file
build:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion
build:windows --copt=/d2ReducedOptimizeHugeFunctions