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+ - »
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+ - brevitas.core.bit_width package
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brevitas.core.bit_width package
+
+
Submodules
+
+
+
brevitas.core.bit_width.const module
+
+-
+class
brevitas.core.bit_width.const.BitWidthConst(bit_width)
+Bases: torch.nn.modules.module.Module
+ScriptModule that returns a constant bit-width wrapped in a float torch.tensor.
+
+- Parameters
+bit_width (int) – bit-width value.
+
+Examples
+>>> bit_width = BitWidthConst(8)
+>>> bit_width()
+tensor(8.)
+
+
+
Note
+
The bit-width is not part of the Module’s state, meaning that it won’t be saved as part of
+a checkpoint.
+
+
Note
+
Maps to bit_width_impl_type == BitWidthImplType.CONST == ‘CONST’ == ‘const’ in higher-level APIs.
+
+-
+
forward()
+Defines the computation performed at every call.
+Should be overridden by all subclasses.
+
+
Note
+
Although the recipe for forward pass needs to be defined within
+this function, one should call the Module instance afterwards
+instead of this since the former takes care of running the
+registered hooks while the latter silently ignores them.
+
+- Return type
+Tensor
+
+
+
+
+-
+
training: bool
+
+
+
+
+
+-
+class
brevitas.core.bit_width.const.MsbClampBitWidth(bit_width_to_remove_impl, min_overall_bit_width, max_overall_bit_width)
+Bases: torch.nn.modules.module.Module
+
+-
+
forward(input_bit_width)
+Defines the computation performed at every call.
+Should be overridden by all subclasses.
+
+
Note
+
Although the recipe for forward pass needs to be defined within
+this function, one should call the Module instance afterwards
+instead of this since the former takes care of running the
+registered hooks while the latter silently ignores them.
+
+- Return type
+Tensor
+
+
+
+
+-
+
training: bool
+
+
+
+
+
+
+
brevitas.core.bit_width.parameter module
+
+-
+class
brevitas.core.bit_width.parameter.BitWidthParameter(bit_width, min_bit_width=2, restrict_bit_width_impl=IntRestrictValue( (float_to_int_impl): RoundSte() ), override_pretrained_bit_width=False)
+Bases: torch.nn.modules.module.Module
+ScriptModule that returns a learnable bit-width wrapped in a float torch.Tensor.
+
+- Parameters
+
+bit_width (int) – value to initialize the output learned bit-width.
min_bit_width (int) – lower bound for the output learned bit-width. Default: 2.
restrict_bit_width_impl (Module) – restrict the learned bit-width to a subset of values. Default: IntRestrictValue(RoundSte()).
override_pretrained_bit_width (bool) – ignore pretrained bit-width loaded from a state dict. Default: False.
+- Returns
+bit-width wrapped in a float torch.tensor and backend by a learnable torch.nn.Parameter.
+- Return type
+Tensor
+- Raises
+RuntimeError – if bit_width < min_bit_width.
+
+Examples
+>>> bit_width_parameter = BitWidthParameter(8)
+>>> bit_width_parameter()
+tensor(8., grad_fn=<RoundSteFnBackward>)
+
+
+
Note
+
Set env variable BREVITAS_IGNORE_MISSING_KEYS=1 to avoid errors when retraining
+from a floating point state dict.
+
+
Note
+
Maps to bit_width_impl_type == BitWidthImplType.PARAMETER == ‘PARAMETER’ == ‘parameter’ in higher-level APIs.
+
+-
+
forward()
+Defines the computation performed at every call.
+Should be overridden by all subclasses.
+
+
Note
+
Although the recipe for forward pass needs to be defined within
+this function, one should call the Module instance afterwards
+instead of this since the former takes care of running the
+registered hooks while the latter silently ignores them.
+
+- Return type
+Tensor
+
+
+
+
+-
+
training: bool
+
+
+
+
+
+-
+class
brevitas.core.bit_width.parameter.RemoveBitwidthParameter(bit_width_to_remove, override_pretrained_bit_width=False, non_zero_epsilon=1e-06, remove_zero_bit_width=0.1)
+Bases: torch.nn.modules.module.Module
+
+-
+
forward()
+Defines the computation performed at every call.
+Should be overridden by all subclasses.
+
+
Note
+
Although the recipe for forward pass needs to be defined within
+this function, one should call the Module instance afterwards
+instead of this since the former takes care of running the
+registered hooks while the latter silently ignores them.
+
+- Return type
+Tensor
+
+
+
+
+-
+
training: bool
+
+
+
+
+
+
+
Module contents
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