tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient

Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.

View aliases

Main aliases

`tf.fake_quant_with_min_max_vars_per_channel_gradient`

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.fake_quant_with_min_max_vars_per_channel_gradient, tf.compat.v1.quantization.fake_quant_with_min_max_vars_per_channel_gradient, `tf.compat.v2.quantization.fake_quant_with_min_max_vars_per_channel_gradient`

tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient(
    gradients, inputs, min, max, num_bits=8, narrow_range=False, name=None
)

Args
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).

Returns
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.