tf.raw_ops.QuantizedConv2DAndRelu
tf.raw_ops.QuantizedConv2DAndRelu(
input, filter, min_input, max_input, min_filter, max_filter, strides, padding,
out_type=tf.dtypes.qint32, dilations=[1, 1, 1, 1], padding_list=[], name=None
)
| Args |
|---|
input | A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. |
filter | A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. |
min_input | A Tensor of type float32. |
max_input | A Tensor of type float32. |
min_filter | A Tensor of type float32. |
max_filter | A Tensor of type float32. |
strides | A list of ints. |
padding | A string from: "SAME", "VALID". |
out_type | An optional tf.DType from: tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16. Defaults to tf.qint32. |
dilations | An optional list of ints. Defaults to [1, 1, 1, 1]. |
padding_list | An optional list of ints. Defaults to []. |
name | A name for the operation (optional). |
| Returns |
|---|
A tuple of Tensor objects (output, min_output, max_output). |
output | A Tensor of type out_type. |
min_output | A Tensor of type float32. |
max_output | A Tensor of type float32. |