tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient

Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.

tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient(
    gradients: Annotated[Any, _atypes.Float32],
    inputs: Annotated[Any, _atypes.Float32],
    min: Annotated[Any, _atypes.Float32],
    max: Annotated[Any, _atypes.Float32],
    num_bits: int = 8,
    narrow_range: bool = False,
    name=None
)

gradients A Tensor of type float32. Backpropagated gradients above the FakeQuantWithMinMaxVars operation, shape one of: [d], [b, d], [b, h, w, d].
inputs A Tensor of type float32. Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape same as gradients. min, max: Quantization interval, floats of shape [d].
min A Tensor of type float32.
max A Tensor of type float32.
num_bits An optional int. Defaults to 8. The bitwidth of the quantization; between 2 and 16, inclusive.
narrow_range An optional bool. Defaults to False. Whether to quantize into 2^num_bits - 1 distinct values.
name A name for the operation (optional).

A tuple of Tensor objects (backprops_wrt_input, backprop_wrt_min, backprop_wrt_max).
backprops_wrt_input A Tensor of type float32.
backprop_wrt_min A Tensor of type float32.
backprop_wrt_max A Tensor of type float32.