tf.raw_ops.QuantizedConv2DPerChannel

Computes QuantizedConv2D per channel.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.QuantizedConv2DPerChannel

tf.raw_ops.QuantizedConv2DPerChannel(
    input,
    filter,
    min_input,
    max_input,
    min_filter,
    max_filter,
    strides,
    padding,
    out_type=tf.dtypes.qint32,
    dilations=[1, 1, 1, 1],
    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.
min_input	A Tensor of type float32. The minimum value of the input tensor
max_input	A Tensor of type float32. The maximum value of the input tensor.
min_filter	A Tensor of type float32. The minimum value of the filter tensor.
max_filter	A Tensor of type float32. The maximum value of the filter tensor.
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 quantized type of output tensor that needs to be converted.
dilations	An optional list of ints. Defaults to [1, 1, 1, 1]. list of dilation values.
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.