def make_batch_feature(self,
filenames,
num_epochs,
batch_size,
reader_num_threads=1,
parser_num_threads=1,
shuffle=False,
shuffle_seed=None,
drop_final_batch=False):
self.filenames = filenames
self.num_epochs = num_epochs
self.batch_size = batch_size
return readers.make_batched_features_dataset(
file_pattern=self.filenames,
batch_size=self.batch_size,
features={
"file": parsing_ops.FixedLenFeature([], dtypes.int64),
"record": parsing_ops.FixedLenFeature([], dtypes.int64),
"keywords": parsing_ops.VarLenFeature(dtypes.string)
},
reader=core_readers.TFRecordDataset,
num_epochs=self.num_epochs,
shuffle=shuffle,
shuffle_seed=shuffle_seed,
reader_num_threads=reader_num_threads,
parser_num_threads=parser_num_threads,
drop_final_batch=drop_final_batch)
def _read_batch_features(self,
filenames,
num_epochs,
batch_size,
reader_num_threads=1,
parser_num_threads=1,
shuffle=False,
shuffle_seed=None):
self.filenames = filenames
self.num_epochs = num_epochs
self.batch_size = batch_size
return readers.make_batched_features_dataset(
file_pattern=self.filenames,
batch_size=self.batch_size,
features={
"file": parsing_ops.FixedLenFeature([], dtypes.int64),
"record": parsing_ops.FixedLenFeature([], dtypes.int64),
"keywords": parsing_ops.VarLenFeature(dtypes.string)
},
reader=core_readers.TFRecordDataset,
num_epochs=self.num_epochs,
shuffle=shuffle,
shuffle_seed=shuffle_seed,
reader_num_threads=reader_num_threads,
parser_num_threads=parser_num_threads).make_one_shot_iterator(
).get_next()
def _predict_input_fn():
dataset = readers.make_batched_features_dataset(
examples_file, batch_size, feature_spec, num_epochs=1)
def features_fn(features):
features.pop('label')
return features
return dataset.map(features_fn)
def make_batch_feature(self,
filenames,
num_epochs,
batch_size,
label_key=None,
reader_num_threads=1,
parser_num_threads=1,
shuffle=False,
shuffle_seed=None,
drop_final_batch=False):
self.filenames = filenames
self.num_epochs = num_epochs
self.batch_size = batch_size
return readers.make_batched_features_dataset(
file_pattern=self.filenames,
batch_size=self.batch_size,
features={
"file": parsing_ops.FixedLenFeature([], dtypes.int64),
"record": parsing_ops.FixedLenFeature([], dtypes.int64),
"keywords": parsing_ops.VarLenFeature(dtypes.string),
"label": parsing_ops.FixedLenFeature([], dtypes.string),
},
label_key=label_key,
reader=core_readers.TFRecordDataset,
num_epochs=self.num_epochs,
shuffle=shuffle,
shuffle_seed=shuffle_seed,
reader_num_threads=reader_num_threads,
parser_num_threads=parser_num_threads,
drop_final_batch=drop_final_batch)
def _eval_input_fn():
dataset = readers.make_batched_features_dataset(examples_file,
batch_size,
feature_spec,
num_epochs=1)
return dataset.map(lambda features:
(features, features.pop('label')))
def _eval_input_fn():
dataset = readers.make_batched_features_dataset(
examples_file, batch_size, feature_spec, num_epochs=1)
return dataset.map(lambda features: (features, features.pop('label')))