diff options
Diffstat (limited to 'ethosu/vela/weight_compressor.py')
| -rw-r--r-- | ethosu/vela/weight_compressor.py | 16 |
1 files changed, 10 insertions, 6 deletions
diff --git a/ethosu/vela/weight_compressor.py b/ethosu/vela/weight_compressor.py index 4ba3dee3..7e33e93b 100644 --- a/ethosu/vela/weight_compressor.py +++ b/ethosu/vela/weight_compressor.py @@ -203,7 +203,7 @@ def core_deinterleave(hwio, core, ncores): return ohwi[core : ohwi.shape[0] : ncores] -def _prepare_scale_and_bias(arch, tens, rescale_for_faf): +def _prepare_scale_and_bias(arch, tens, rescale_for_faf, explicit_scaling): assert tens.purpose in [TensorPurpose.FeatureMap, TensorPurpose.FSBias] assert tens.format == TensorFormat.NHWC # the connected operator should expect a bias input unless it is a FullyConnected @@ -260,11 +260,15 @@ def _prepare_scale_and_bias(arch, tens, rescale_for_faf): else: raise UnsupportedFeatureError(f"Compression of {ifm_dtype} is not implemented; Tensor: '{tens.name}'") - # quantise all of the weight scales into (scale_factor, shift) - if ifm_dtype == DataType.int16: - quantised_scales = [reduced_quantise_scale(scale) for scale in scales] + if explicit_scaling: + assert len(explicit_scaling.shift) == len(explicit_scaling.multiplier) + quantised_scales = [(int(m), int(s)) for s, m in zip(explicit_scaling.shift, explicit_scaling.multiplier)] else: - quantised_scales = [quantise_scale(scale) for scale in scales] + # quantise all of the weight scales into (scale_factor, shift) + if ifm_dtype == DataType.int16: + quantised_scales = [reduced_quantise_scale(scale) for scale in scales] + else: + quantised_scales = [quantise_scale(scale) for scale in scales] # If only 1 quantised scale is used, repeat that value for the length of the biases if len(quantised_scales) == 1: @@ -355,7 +359,7 @@ def encode_weight_and_scale_tensor( # Bias & scale if do_scales: - quantised_scales, biases = _prepare_scale_and_bias(arch, scale_tens, rescale_for_faf) + quantised_scales, biases = _prepare_scale_and_bias(arch, scale_tens, rescale_for_faf, op.explicit_scaling) scale_tens.element_size_bytes = 10 # Slice the weight stream up depth-ways into bricks and compress |