tf.raw_ops.QuantizedDepthwiseConv2DWithBiasAndRelu

Computes quantized depthwise Conv2D with Bias and Relu.

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tf.compat.v1.raw_ops.QuantizedDepthwiseConv2DWithBiasAndRelu

tf.raw_ops.QuantizedDepthwiseConv2DWithBiasAndRelu(
    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. 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.
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.