tf.raw_ops.QuantizedConv2D

Computes a 2D convolution given quantized 4D input and filter tensors.

tf.raw_ops.QuantizedConv2D(
    input,
    filter,
    min_input,
    max_input,
    min_filter,
    max_filter,
    strides,
    padding,
    out_type=tf.dtypes.qint32,
    dilations=[1, 1, 1, 1],
    name=None
)

The inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.

inputA Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16.
filterA Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16. filter's input_depth dimension must match input's depth dimensions.
min_inputA Tensor of type float32. The float value that the lowest quantized input value represents.
max_inputA Tensor of type float32. The float value that the highest quantized input value represents.
min_filterA Tensor of type float32. The float value that the lowest quantized filter value represents.
max_filterA Tensor of type float32. The float value that the highest quantized filter value represents.
stridesA list of ints. The stride of the sliding window for each dimension of the input tensor.
paddingA string from: "SAME", "VALID". The type of padding algorithm to use.
out_typeAn optional tf.DType from: tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16. Defaults to tf.qint32.
dilationsAn optional list of ints. Defaults to [1, 1, 1, 1]. 1-D tensor of length 4. The dilation factor for each dimension of input. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format, see above for details. Dilations in the batch and depth dimensions must be 1.
nameA name for the operation (optional).

A tuple of Tensor objects (output, min_output, max_output).
outputA Tensor of type out_type.
min_outputA Tensor of type float32.
max_outputA Tensor of type float32.