本文整理匯總了Python中tensorflow.python.ops.parsing_ops.parse_single_example方法的典型用法代碼示例。如果您正苦於以下問題：Python parsing_ops.parse_single_example方法的具體用法？Python parsing_ops.parse_single_example怎麽用？Python parsing_ops.parse_single_example使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.ops.parsing_ops的用法示例。
在下文中一共展示了parsing_ops.parse_single_example方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: decode
# 需要導入模塊: from tensorflow.python.ops import parsing_ops [as 別名]
# 或者: from tensorflow.python.ops.parsing_ops import parse_single_example [as 別名]
def decode(self, serialized_example, items=None):
"""Decodes the given serialized TF-example.
Args:
serialized_example: a serialized TF-example tensor.
items: the list of items to decode. These must be a subset of the item
keys in self._items_to_handlers. If `items` is left as None, then all
of the items in self._items_to_handlers are decoded.
Returns:
the decoded items, a list of tensor.
"""
example = parsing_ops.parse_single_example(serialized_example,
self._keys_to_features)
# Reshape non-sparse elements just once:
for k in self._keys_to_features:
v = self._keys_to_features[k]
if isinstance(v, parsing_ops.FixedLenFeature):
example[k] = array_ops.reshape(example[k], v.shape)
if not items:
items = self._items_to_handlers.keys()
outputs = []
for item in items:
handler = self._items_to_handlers[item]
keys_to_tensors = {key: example[key] for key in handler.keys}
outputs.append(handler.tensors_to_item(keys_to_tensors))
return outputs 示例2: parse_single_example
# 需要導入模塊: from tensorflow.python.ops import parsing_ops [as 別名]
# 或者: from tensorflow.python.ops.parsing_ops import parse_single_example [as 別名]
def parse_single_example(serialized, features, name=None, example_names=None):
"""Parses a single `Example` proto.
See tf.parse_single_example.
Args:
serialized: A scalar string Tensor or LabeledTensor, a single serialized
Example.
features: A `dict` mapping feature keys to `labeled_tensor.FixedLenFeature`
values.
name: A name for this operation (optional).
example_names: (Optional) A scalar string Tensor, the associated name.
Returns:
A `dict` mapping feature keys to `LabeledTensor` values.
Raises:
ValueError: if any feature is invalid.
"""
serialized = core.convert_to_labeled_tensor(serialized)
unlabeled_features = _labeled_to_unlabeled_features(features)
unlabeled_parsed = parsing_ops.parse_single_example(
serialized.tensor, unlabeled_features, name, example_names)
parsed = {}
for name, parsed_feature in unlabeled_parsed.items():
parsed[name] = core.LabeledTensor(parsed_feature, features[name].axes)
return parsed 示例3: decode
# 需要導入模塊: from tensorflow.python.ops import parsing_ops [as 別名]
# 或者: from tensorflow.python.ops.parsing_ops import parse_single_example [as 別名]
def decode(self, serialized_example, items=None):
"""Decodes the given serialized TF-example.
Args:
serialized_example: a serialized TF-example tensor.
items: the list of items to decode. These must be a subset of the item
keys in self._items_to_handlers. If `items` is left as None, then all
of the items in self._items_to_handlers are decoded.
Returns:
the decoded items, a list of tensor.
"""
example = parsing_ops.parse_single_example(serialized_example,
self._keys_to_features)
# Reshape non-sparse elements just once, adding the reshape ops in
# deterministic order.
for k in sorted(self._keys_to_features):
v = self._keys_to_features[k]
if isinstance(v, parsing_ops.FixedLenFeature):
example[k] = array_ops.reshape(example[k], v.shape)
if not items:
items = self._items_to_handlers.keys()
outputs = []
for item in items:
handler = self._items_to_handlers[item]
keys_to_tensors = {key: example[key] for key in handler.keys}
outputs.append(handler.tensors_to_item(keys_to_tensors))
return outputs 示例4: decode
# 需要導入模塊: from tensorflow.python.ops import parsing_ops [as 別名]
# 或者: from tensorflow.python.ops.parsing_ops import parse_single_example [as 別名]
def decode(self, serialized_example, items=None):
"""Decodes the given serialized TF-example.
Args:
serialized_example: a serialized TF-example tensor.
items: the list of items to decode. These must be a subset of the item
keys in self._items_to_handlers. If `items` is left as None, then all
of the items in self._items_to_handlers are decoded.
Returns:
the decoded items, a list of tensor.
"""
example = parsing_ops.parse_single_example(
serialized_example,
self._keys_to_features)
# Reshape non-sparse elements just once:
for k in self._keys_to_features:
v = self._keys_to_features[k]
if isinstance(v, parsing_ops.FixedLenFeature):
example[k] = array_ops.reshape(example[k], v.shape)
if not items:
items = self._items_to_handlers.keys()
outputs = []
for item in items:
handler = self._items_to_handlers[item]
keys_to_tensors = {key: example[key] for key in handler.keys}
outputs.append(handler.tensors_to_item(keys_to_tensors))
return outputs