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# Defaults for eval.py.
#
#
# You must also include a binding for MODEL.
#
# Required to be set:
#
# - MIXTURE_OR_TASK_NAME: The SeqIO Task/Mixture to evaluate on
# - CHECKPOINT_PATH: The model checkpoint to evaluate
# - EVAL_OUTPUT_DIR: The dir to write results to.
#
#
# Commonly overridden options:
#
# - DatasetConfig.split
# - DatasetConfig.batch_size
# - DatasetConfig.use_cached
# - RestoreCheckpointConfig.mode
# - PjitPartitioner.num_partitions
from __gin__ import dynamic_registration
import __main__ as eval_script
import seqio
from t5x import partitioning
from t5x import utils
# Must be overridden
MIXTURE_OR_TASK_NAME = %gin.REQUIRED
CHECKPOINT_PATH = %gin.REQUIRED
EVAL_OUTPUT_DIR = %gin.REQUIRED
TASK_FEATURE_LENGTHS = None # auto-computes the maximum features length to use.
# DEPRECATED: Import the this module in your gin file.
MIXTURE_OR_TASK_MODULE = None
eval_script.evaluate:
model = %MODEL # imported from separate gin file
dataset_cfg = @utils.DatasetConfig()
partitioner = @partitioning.PjitPartitioner()
restore_checkpoint_cfg = @utils.RestoreCheckpointConfig()
output_dir = %EVAL_OUTPUT_DIR
inference_evaluator_cls = @seqio.Evaluator
partitioning.PjitPartitioner:
num_partitions = 1
logical_axis_rules = @partitioning.standard_logical_axis_rules()
seqio.Evaluator:
logger_cls = [@seqio.PyLoggingLogger, @seqio.TensorBoardLogger, @seqio.JSONLogger]
num_examples = None # Use all examples in the dataset.
use_memory_cache = True
utils.DatasetConfig:
mixture_or_task_name = %MIXTURE_OR_TASK_NAME
task_feature_lengths = %TASK_FEATURE_LENGTHS
split = 'test'
batch_size = 32
shuffle = False
seed = 42
use_cached = False
pack = False
use_custom_packing_ops = False
module = %MIXTURE_OR_TASK_MODULE
utils.RestoreCheckpointConfig:
path = %CHECKPOINT_PATH
mode = 'specific'
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