tf.raw_ops.QuantizedDepthwiseConv2DWithBias

Computes quantized depthwise Conv2D with Bias.

tf.raw_ops.QuantizedDepthwiseConv2DWithBias(
    input,
    filter,
    bias,
    min_input,
    max_input,
    min_filter,
    max_filter,
    strides,
    padding,
    out_type=tf.dtypes.qint32,
    dilations=[1, 1, 1, 1],
    name=None
)

input A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. The original input tensor.
filter A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. The original filter tensor.
bias A Tensor of type float32. The original bias tensor.
min_input A Tensor of type float32. The float value that the minimum quantized input value represents.
max_input A Tensor of type float32. The float value that the maximum quantized input value represents.
min_filter A Tensor of type float32. The float value that the minimum quantized filter value represents.
max_filter A Tensor of type float32. The float value that the maximum quantized filter value represents.
strides A list of ints. List of stride values.
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. The type of the output.
dilations An optional list of ints. Defaults to [1, 1, 1, 1]. List of dilation values.
name A name for the operation (optional).

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.