Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.
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 .
|