def __init__(self, filenames):
"""Create a `LMDBDataset`.
`LMDBDataset` allows a user to read data from a mdb file as
(key value) pairs sequentially.
For example:
```python
tf.compat.v1.enable_eager_execution()
dataset = tf.contrib.lmdb.LMDBDataset("/foo/bar.mdb")
# Prints the (key, value) pairs inside a lmdb file.
for key, value in dataset:
print(key, value)
```
Args:
filenames: A `tf.string` tensor containing one or more filenames.
"""
self._filenames = ops.convert_to_tensor(
filenames, dtype=dtypes.string, name="filenames")
if compat.forward_compatible(2019, 8, 3):
variant_tensor = gen_experimental_dataset_ops.lmdb_dataset(
self._filenames, **self._flat_structure)
else:
variant_tensor = gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames, **self._flat_structure)
super(LMDBDataset, self).__init__(variant_tensor)
def __init__(self, filenames):
"""Create a `LMDBDataset`.
`LMDBDataset` allows a user to read data from a mdb file as
(key value) pairs sequentially.
For example:
```python
dataset = tf.contrib.lmdb.LMDBDataset("/foo/bar.mdb")
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()
# Prints the (key, value) pairs inside a lmdb file.
while True:
try:
print(sess.run(next_element))
except tf.errors.OutOfRangeError:
break
```
Args:
filenames: A `tf.string` tensor containing one or more filenames.
"""
self._filenames = ops.convert_to_tensor(filenames,
dtype=dtypes.string,
name="filenames")
variant_tensor = gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames, **dataset_ops.flat_structure(self))
super(LMDBDataset, self).__init__(variant_tensor)
def __init__(self, filenames):
"""Create a `LMDBDataset`.
`LMDBDataset` allows a user to read data from a mdb file as
(key value) pairs sequentially.
For example:
```python
tf.enable_eager_execution()
dataset = tf.contrib.lmdb.LMDBDataset("/foo/bar.mdb")
# Prints the (key, value) pairs inside a lmdb file.
for key, value in dataset:
print(key, value)
```
Args:
filenames: A `tf.string` tensor containing one or more filenames.
"""
self._filenames = ops.convert_to_tensor(
filenames, dtype=dtypes.string, name="filenames")
variant_tensor = gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames, **dataset_ops.flat_structure(self))
super(LMDBDataset, self).__init__(variant_tensor)
def _as_variant_tensor(self):
return gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames,
output_types=nest.flatten(self.output_types),
output_shapes=nest.flatten(self.output_shapes))
def _as_variant_tensor(self):
return gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames, **dataset_ops.flat_structure(self))
def _as_variant_tensor(self):
return gen_experimental_dataset_ops.experimental_lmdb_dataset(
self._filenames,
output_types=nest.flatten(self.output_types),
output_shapes=nest.flatten(self.output_shapes))