本文整理汇总了Python中tensorflow.core.example.feature_pb2.Int64List方法的典型用法代码示例。如果您正苦于以下问题：Python feature_pb2.Int64List方法的具体用法？Python feature_pb2.Int64List怎么用？Python feature_pb2.Int64List使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tensorflow.core.example.feature_pb2的用法示例。
在下文中一共展示了feature_pb2.Int64List方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _write_test_data
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def _write_test_data():
schema = feature_spec_to_schema({"f0": tf.VarLenFeature(dtype=tf.int64),
"f1": tf.VarLenFeature(dtype=tf.int64),
"f2": tf.VarLenFeature(dtype=tf.int64)})
batches = [
[1, 4, None],
[2, None, None],
[3, 5, None],
[None, None, None],
]
example_proto = [example_pb2.Example(features=feature_pb2.Features(feature={
"f" + str(i): feature_pb2.Feature(int64_list=feature_pb2.Int64List(value=[f]))
for i, f in enumerate(batch) if f is not None
})) for batch in batches]
return DataUtil.write_test_data(example_proto, schema) 示例2: create_tf_record
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def create_tf_record(self):
path = os.path.join(self.get_temp_dir(), 'tfrecord')
writer = tf.python_io.TFRecordWriter(path)
image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
with self.test_session():
encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
example = example_pb2.Example(features=feature_pb2.Features(feature={
'image/encoded': feature_pb2.Feature(
bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
'image/format': feature_pb2.Feature(
bytes_list=feature_pb2.BytesList(value=['jpeg'.encode('utf-8')])),
'image/object/bbox/xmin': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[0.0])),
'image/object/bbox/xmax': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[1.0])),
'image/object/bbox/ymin': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[0.0])),
'image/object/bbox/ymax': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[1.0])),
'image/object/class/label': feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[2])),
}))
writer.write(example.SerializeToString())
writer.close()
return path 示例3: _encoded_int64_feature
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def _encoded_int64_feature(ndarray):
return feature_pb2.Feature(int64_list=feature_pb2.Int64List(
value=ndarray.flatten().tolist())) 示例4: _EncodedInt64Feature
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def _EncodedInt64Feature(self, ndarray):
return feature_pb2.Feature(int64_list=feature_pb2.Int64List(
value=ndarray.flatten().tolist())) 示例5: setUp
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def setUp(self):
super(ParseBase, self).setUp()
examples = [
example_pb2.Example(features=feature_pb2.Features(feature={
'a':
feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[1])),
'b':
feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[2, 3, 4])),
})),
example_pb2.Example(features=feature_pb2.Features(feature={
'a':
feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[5])),
'b':
feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[6, 7, 8])),
})),
]
self.serialized = core.LabeledTensor(
constant_op.constant([ex.SerializeToString() for ex in examples]),
['batch'])
self.features = {
'a': io_ops.FixedLenFeature([], dtypes.int64),
'b': io_ops.FixedLenFeature([('x', 3)], dtypes.int64)
} 示例6: _Int64Feature
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def _Int64Feature(self, value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=value)) 示例7: _Int64FeatureFromList
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def _Int64FeatureFromList(self, ndarray):
return feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=ndarray.flatten().tolist())) 示例8: create_tf_record
# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import Int64List [as 别名]
def create_tf_record(self):
path = os.path.join(self.get_temp_dir(), 'tfrecord')
writer = tf.python_io.TFRecordWriter(path)
image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
flat_mask = (4 * 5) * [1.0]
with self.test_session():
encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
example = example_pb2.Example(features=feature_pb2.Features(feature={
'image/encoded': feature_pb2.Feature(
bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
'image/format': feature_pb2.Feature(
bytes_list=feature_pb2.BytesList(value=['jpeg'.encode('utf-8')])),
'image/height': feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[4])),
'image/width': feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[5])),
'image/object/bbox/xmin': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[0.0])),
'image/object/bbox/xmax': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[1.0])),
'image/object/bbox/ymin': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[0.0])),
'image/object/bbox/ymax': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=[1.0])),
'image/object/class/label': feature_pb2.Feature(
int64_list=feature_pb2.Int64List(value=[2])),
'image/object/mask': feature_pb2.Feature(
float_list=feature_pb2.FloatList(value=flat_mask)),
}))
writer.write(example.SerializeToString())
writer.close()
return path