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advance: null
approach: post_training_static_quant
calib_iteration: 7
framework: pytorch
op:
? !!python/tuple
- quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.0.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.0.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.0.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.0.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.0.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.0.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.0.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.0.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.0.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.0.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.1.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.1.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.1.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.1.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.1.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.2.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.2.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.2.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.2.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.2.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.3.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.3.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.3.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.3.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.3.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.4.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.4.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.4.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.4.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.4.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.5.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.5.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.5.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.5.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.5.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.6.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.6.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.6.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.6.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.6.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.7.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.7.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.7.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.7.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.7.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.8.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.8.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.8.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.8.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.8.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.9.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.9.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.9.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.9.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.9.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.10.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.10.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.10.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.10.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.10.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.attention.self.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.11.attention.self.query
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.attention.self.key
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.attention.self.value
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.attention.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.11.attention.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.intermediate.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.11.intermediate.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.encoder.layer.11.output.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.encoder.layer.11.output.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- bert.pooler.quant
- QuantStub
: activation:
dtype: uint8
scheme: asym
granularity: per_tensor
algorithm: minmax
? !!python/tuple
- bert.pooler.dense
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl
? !!python/tuple
- classifier
- Linear
: weight:
dtype: int8
scheme: sym
granularity: per_channel
algorithm: minmax
bit: 7.0
activation:
dtype: uint8
scheme: sym
granularity: per_tensor
algorithm: kl