tf.raw_ops.QuantizedConv2DWithBiasSumAndRelu(
input, filter, bias, min_input, max_input, min_filter, max_filter, summand,
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.
|
bias
|
A Tensor of type float32.
|
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.
|
summand
|
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.
|
