def forward(self, input_bit_width: Tensor) -> Tensor:
bit_width_to_remove = self.bit_width_to_remove_impl()
output_bit_width = torch.abs(input_bit_width - bit_width_to_remove)
output_bit_width = tensor_clamp_ste(output_bit_width,
self.min_overall_bit_width(),
self.max_overall_bit_width())
return output_bit_width
def forward(self, input_bit_width: Tensor, zero_hw_sentinel: Tensor) -> Tensor:
bit_width_to_remove = self.bit_width_to_remove_impl(zero_hw_sentinel)
output_bit_width = torch.abs(input_bit_width - bit_width_to_remove)
output_bit_width = tensor_clamp_ste(output_bit_width,
self.min_overall_bit_width + zero_hw_sentinel,
self.max_overall_bit_width + zero_hw_sentinel) #todo STE on max only
return output_bit_width
def forward(self, x: torch.Tensor, min_val: torch.Tensor,
max_val: torch.Tensor):
return tensor_clamp_ste(x, min_val, max_val)
