def read(self, queue, name=None):
"""Returns the next record (key, value) pair produced by a reader.
Will dequeue a work unit from queue if necessary (e.g. when the
Reader needs to start reading from a new file since it has
finished with the previous file).
Args:
queue: A Queue or a mutable string Tensor representing a handle
to a Queue, with string work items.
name: A name for the operation (optional).
Returns:
A tuple of Tensors (key, value).
key: A string scalar Tensor.
value: A string scalar Tensor.
"""
if isinstance(queue, ops.Tensor):
queue_ref = queue
else:
queue_ref = queue.queue_ref
if self._reader_ref.dtype == dtypes.resource:
return gen_io_ops._reader_read_v2(self._reader_ref,
queue_ref,
name=name)
else:
# For compatibility with pre-resource queues, create a ref(string) tensor
# which can be looked up as the same queue by a resource manager.
old_queue_op = gen_data_flow_ops._fake_queue(queue_ref)
return gen_io_ops._reader_read(self._reader_ref,
old_queue_op,
name=name)
def read(self, queue, name=None):
"""Returns the next record (key, value pair) produced by a reader.
Will dequeue a work unit from queue if necessary (e.g. when the
Reader needs to start reading from a new file since it has
finished with the previous file).
Args:
queue: A Queue or a mutable string Tensor representing a handle
to a Queue, with string work items.
name: A name for the operation (optional).
Returns:
A tuple of Tensors (key, value).
key: A string scalar Tensor.
value: A string scalar Tensor.
"""
if isinstance(queue, ops.Tensor):
queue_ref = queue
else:
queue_ref = queue.queue_ref
if self._reader_ref.dtype == dtypes.resource:
return gen_io_ops._reader_read_v2(self._reader_ref, queue_ref, name=name)
else:
# For compatibility with pre-resource queues, create a ref(string) tensor
# which can be looked up as the same queue by a resource manager.
old_queue_op = gen_data_flow_ops._fake_queue(queue_ref)
return gen_io_ops._reader_read(self._reader_ref, old_queue_op, name=name)
def read_up_to(
self,
queue,
num_records, # pylint: disable=invalid-name
name=None):
"""Returns up to num_records (key, value) pairs produced by a reader.
Will dequeue a work unit from queue if necessary (e.g., when the
Reader needs to start reading from a new file since it has
finished with the previous file).
It may return less than num_records even before the last batch.
Args:
queue: A Queue or a mutable string Tensor representing a handle
to a Queue, with string work items.
num_records: Number of records to read.
name: A name for the operation (optional).
Returns:
A tuple of Tensors (keys, values).
keys: A 1-D string Tensor.
values: A 1-D string Tensor.
"""
if isinstance(queue, ops.Tensor):
queue_ref = queue
else:
queue_ref = queue.queue_ref
if self._reader_ref.dtype == dtypes.resource:
return gen_io_ops._reader_read_up_to_v2(self._reader_ref,
queue_ref,
num_records,
name=name)
else:
# For compatibility with pre-resource queues, create a ref(string) tensor
# which can be looked up as the same queue by a resource manager.
old_queue_op = gen_data_flow_ops._fake_queue(queue_ref)
return gen_io_ops._reader_read_up_to(self._reader_ref,
old_queue_op,
num_records,
name=name)
def read_up_to(self, queue, num_records, # pylint: disable=invalid-name
name=None):
"""Returns up to num_records (key, value pairs) produced by a reader.
Will dequeue a work unit from queue if necessary (e.g., when the
Reader needs to start reading from a new file since it has
finished with the previous file).
It may return less than num_records even before the last batch.
Args:
queue: A Queue or a mutable string Tensor representing a handle
to a Queue, with string work items.
num_records: Number of records to read.
name: A name for the operation (optional).
Returns:
A tuple of Tensors (keys, values).
keys: A 1-D string Tensor.
values: A 1-D string Tensor.
"""
if isinstance(queue, ops.Tensor):
queue_ref = queue
else:
queue_ref = queue.queue_ref
if self._reader_ref.dtype == dtypes.resource:
return gen_io_ops._reader_read_up_to_v2(self._reader_ref,
queue_ref,
num_records,
name=name)
else:
# For compatibility with pre-resource queues, create a ref(string) tensor
# which can be looked up as the same queue by a resource manager.
old_queue_op = gen_data_flow_ops._fake_queue(queue_ref)
return gen_io_ops._reader_read_up_to_v2(self._reader_ref,
old_queue_op,
num_records,
name=name)
