tf.train.Int64List
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Used in tf.train.Example
protos. Holds a list of Int64s.
Used in the notebooks
An Example
proto is a representation of the following python type:
Dict[str,
Union[List[bytes],
List[int64],
List[float]]]
This proto implements the List[int64]
portion.
from google.protobuf import text_format
example = text_format.Parse('''
features {
feature {key: "my_feature"
value {int64_list {value: [1, 2, 3, 4]} } }
}''',
tf.train.Example())
example.features.feature['my_feature'].int64_list.value
[1, 2, 3, 4]
Use tf.io.parse_example
to extract tensors from a serialized Example
proto:
tf.io.parse_example(
example.SerializeToString(),
features = {'my_feature': tf.io.RaggedFeature(dtype=tf.int64)})
{'my_feature': <tf.Tensor: shape=(4,), dtype=float32,
numpy=array([1, 2, 3, 4], dtype=int64)>}
See the tf.train.Example
guide for usage details.
Attributes |
value
|
repeated int64 value
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.train.Int64List\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/core/example/feature.proto) |\n\nUsed in [`tf.train.Example`](../../tf/train/Example) protos. Holds a list of Int64s.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.train.Int64List`](https://www.tensorflow.org/api_docs/python/tf/train/Int64List)\n\n\u003cbr /\u003e\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [TFRecord and tf.train.Example](https://www.tensorflow.org/tutorials/load_data/tfrecord) - [Feature Engineering using TFX Pipeline and TensorFlow Transform](https://www.tensorflow.org/tfx/tutorials/tfx/penguin_tft) - [Graph regularization for sentiment classification using synthesized graphs](https://www.tensorflow.org/neural_structured_learning/tutorials/graph_keras_lstm_imdb) - [Graph-based Neural Structured Learning in TFX](https://www.tensorflow.org/tfx/tutorials/tfx/neural_structured_learning) |\n\nAn `Example` proto is a representation of the following python type: \n\n Dict[str,\n Union[List[bytes],\n List[int64],\n List[float]]]\n\nThis proto implements the `List[int64]` portion. \n\n from google.protobuf import text_format\n example = text_format.Parse('''\n features {\n feature {key: \"my_feature\"\n value {int64_list {value: [1, 2, 3, 4]} } }\n }''',\n tf.train.Example())\n\n example.features.feature['my_feature'].int64_list.value\n [1, 2, 3, 4]\n\nUse [`tf.io.parse_example`](../../tf/io/parse_example) to extract tensors from a serialized `Example` proto: \n\n tf.io.parse_example(\n example.SerializeToString(),\n features = {'my_feature': tf.io.RaggedFeature(dtype=tf.int64)})\n {'my_feature': \u003ctf.Tensor: shape=(4,), dtype=float32,\n numpy=array([1, 2, 3, 4], dtype=int64)\u003e}\n\nSee the [`tf.train.Example`](https://www.tensorflow.org/tutorials/load_data/tfrecord#tftrainexample)\nguide for usage details.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|---------|------------------------|\n| `value` | `repeated int64 value` |\n\n\u003cbr /\u003e"]]