| CheckpointOp is a wrapper over a SaveFloatTensorOp
| that basically allows flexible naming
| over iterations.
|
| The file pattern in db_name should be
| a format string that can be passed into
| sprintf with an int argument specifying
| the current iteration. An example:
| “/path/to/my/checkpoint/checkpoint_at_%d.pb”
|
| The Checkpoint operator is similar
| to the Save operator, but allows one
| to save to db every few iterations, with
| a db name that is appended with the iteration
| count. It takes [1, infinity) number
| of inputs and has no output. The first
| input has to be a TensorCPU of type int
| and has size 1 (i.e. the iteration counter).
| This is determined whether we need to
| do checkpointing.
|
| Checks if the db described by the arguments
| exists.
|
| Github Links:
|
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/load_save_op.cc
|
| The Load operator loads a set of serialized
| blobs from a db or multiple dbs. It takes
| $[0, \infty)$ number of inputs and $[0,
| \infty)$ number of outputs, using the
| db keys to match the db entries with the
| outputs.
|
| If at least one input is passed, then
| it is assumed that that input blobs are
| a set of DBReaders to load from. Otherwise
| the db or dbs argument is used to
| load blobs from one single db or multiple
| dbs respectively. db_type argument
| is used to specify the type of the input
| db/dbs.
|
| Github Links:
|
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/load_save_op.cc
|
| Saves a set of blobs to a db.
|
| It takes $[1, \infty)$
| number of inputs and has no
| output. The contents of the inputs are
| written into the db using the settings
| specified by the arguments.
|
| Github Links:
|
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/load_save_op.cc
|