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# ABSTRACT: Start here for an overview of the library
# PODNAME: AI::TensorFlow::Libtensorflow::Manual::Quickstart

__END__

=pod

=encoding UTF-8

=head1 NAME

AI::TensorFlow::Libtensorflow::Manual::Quickstart - Start here for an overview of the library

=head1 DESCRIPTION

This provides a tour of C<libtensorflow> to help get started with using the
library.

=head1 CONVENTIONS

The library uses UpperCamelCase naming convention for method names in order to
match the underlying C library (for compatibility with future API changes) and
to make translating code from C easier as this is a low-level API.

As such, constructors for objects that correspond to C<libtensorflow> data
structures are typically called C<New>. For example, a new
L<AI::TensorFlow::Libtensorflow::Status> object can be created as follows

  use AI::TensorFlow::Libtensorflow::Status;
  my $status = AI::TensorFlow::Libtensorflow::Status->New;

  ok defined $status, 'Created new Status';

These C<libtensorflow> data structures use L<destructors|perlobj/Destructors> where necessary.

=head1 OBJECT TYPES

=over 4

=item L<AI::TensorFlow::Libtensorflow::Status>

Used for error-handling. Many methods take this as the final argument which is
then checked after the method call to ensure that it completed successfully.

=item L<AI::TensorFlow::Libtensorflow::Tensor>, L<AI::TensorFlow::Libtensorflow::DataType>

A C<TFTensor> is a multi-dimensional data structure that stores the data for inputs and outputs.
Each element has the same data type
which is defined by L<AI::TensorFlow::Libtensorflow::DataType>
thus a C<TFTensor> is considered to be "homogeneous data structure".
See L<Introduction to Tensors|https://www.tensorflow.org/guide/tensor> for more.

=item L<AI::TensorFlow::Libtensorflow::OperationDescription>, L<AI::TensorFlow::Libtensorflow::Operation>

An operation is a function that has inputs and outputs. It has a user-defined
name (such as C<MyAdder>) and library-defined type (such as C<AddN>).
L<AI::TensorFlow::Libtensorflow::OperationDescription> is used to build an
operation that will be added to a graph of other operations where those other
operations can set the operation's inputs and get the operation's outputs.
These inputs and outputs have types and dimension specifications, so that the
operations only accept and emit certain C<TFTensor>s.

=item L<AI::TensorFlow::Libtensorflow::Graph>

A set of operations with inputs and outputs linked together. This computation
can be serialized along with parameters as part of
a L<SavedModel|https://www.tensorflow.org/guide/saved_model>.