tensorflow中Tensor的数据类型 tf.DType

Class DType

定义在： tensorflow/python/framework/dtypes.py.

中文版：https://www.w3cschool.cn/tensorflow_python/tensorflow_python-d6x22e0f.html

英文指南: Building Graphs > Tensor types

要查看 tf.Tensor 的数据类型，请使用 Tensor.dtype 属性。

用 python 对象创建 tf.Tensor 时，可以选择指定数据类型。
如果不指定数据类型，TensorFlow 会将 Python 整数转型为 tf.int32，并将 python 浮点数转型为 tf.float32。
此外，TensorFlow 使用 Numpy 在转换至数组时使用的相同规则。

Represents the type of the elements in a Tensor.

The following DType objects are defined:

• tf.float16: 16-bit half-precision floating-point.
• tf.float32: 32-bit single-precision floating-point.
• tf.float64: 64-bit double-precision floating-point.
• tf.bfloat16: 16-bit truncated floating-point.
• tf.complex64: 64-bit single-precision complex.
• tf.complex128: 128-bit double-precision complex.
• tf.int8: 8-bit signed integer.
• tf.uint8: 8-bit unsigned integer.
• tf.uint16: 16-bit unsigned integer.
• tf.uint32: 32-bit unsigned integer.
• tf.uint64: 64-bit unsigned integer.
• tf.int16: 16-bit signed integer.
• tf.int32: 32-bit signed integer.
• tf.int64: 64-bit signed integer.
• tf.bool: Boolean.
• tf.string: String.
• tf.qint8: Quantized 8-bit signed integer.
• tf.quint8: Quantized 8-bit unsigned integer.
• tf.qint16: Quantized 16-bit signed integer.
• tf.quint16: Quantized 16-bit unsigned integer.
• tf.qint32: Quantized 32-bit signed integer.
• tf.resource: Handle to a mutable resource.
• tf.variant: Values of arbitrary types.

In addition, variants of these types with the _ref suffix are defined for reference-typed tensors.

此外, 还为引用类型的张量定义了具有 _ref 后缀的这些类型的变体。 

The tf.as_dtype() function converts numpy types and string type names to a DTypeobject.

该 tf.as_dtype() 函数将 numpy 类型和字符串类型名称转换为DType对象。