tf.raw_ops.QuantizedConv2DWithBiasAndRelu
tf.raw_ops.QuantizedConv2DWithBiasAndRelu(
input,
filter,
bias,
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. |
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. |
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. |