Do not document prefetch_buffer_size
The value is autotuned by default which should be good enough in most
cases.
@@ -190,9 +190,6 @@ train:
# (optional) The number of threads to use for processing data in parallel (default: 4).
num_threads: 4
- # (optional) The number of batches to prefetch asynchronously. If not set, use an
- # automatically tuned value on TensorFlow 1.8+ and 1 on older versions. (default: null).
- prefetch_buffer_size: null
# (optional) The number of elements from which to sample during shuffling (default: 500000).
# Set 0 or null to disable shuffling, -1 to match the number of training examples.
@@ -231,8 +228,6 @@ infer:
# (optional) The number of threads to use for processing data in parallel (default: 1).
num_threads: 1
- # (optional) The number of batches to prefetch asynchronously (default: 1).
- prefetch_buffer_size: 1
# (optional) For compatible models, the number of hypotheses to output (default: 1).
# This sets the parameter params/num_hypotheses.
@@ -250,8 +245,6 @@ score:
batch_size: 64
# (optional) The number of threads to use for processing data in parallel (default: 1).
num_threads: 1
- # (optional) The number of batches to prefetch asynchronously (default: 1).
- prefetch_buffer_size: 1
# (optional) Also report token-level cross entropy.
with_token_level: false
