diff options
Diffstat (limited to 'ethosu/vela/weight_compressor.py')
| -rw-r--r-- | ethosu/vela/weight_compressor.py | 13 |
1 files changed, 10 insertions, 3 deletions
diff --git a/ethosu/vela/weight_compressor.py b/ethosu/vela/weight_compressor.py index b291dce..bb7cd67 100644 --- a/ethosu/vela/weight_compressor.py +++ b/ethosu/vela/weight_compressor.py @@ -426,13 +426,13 @@ def calc_scales_and_pack_biases(tens, arch, ofm_depth_step, rescale_for_faf=Fals first_consumer_op = tens.consumer_list[0] ifm_dtype = first_consumer_op.inputs[0].dtype - ifm_scale = first_consumer_op.inputs[0].quantization.scale_f32 + ifm_scale = first_consumer_op.get_input_quantization().scale_f32 ofm_scale = first_consumer_op.get_output_quantization().scale_f32 weight_scales = first_consumer_op.inputs[1].quantization.scale_f32 # biases can have multiple consumers for rnn cells. if so, then check that they are all the same for op in tens.consumer_list[1:]: - assert ifm_scale == op.inputs[0].quantization.scale_f32 + assert ifm_scale == op.get_input_quantization().scale_f32 assert ofm_scale == op.get_output_quantization().scale_f32 assert weight_scales == op.inputs[1].quantization.scale_f32 @@ -445,7 +445,14 @@ def calc_scales_and_pack_biases(tens, arch, ofm_depth_step, rescale_for_faf=Fals # TensorFlow Lite casts the scales slightly differently for uint8 and int8 if not rescale_for_faf: if ifm_dtype == DataType.uint8: - scales = [np.double(ifm_scale * weight_scale) / np.double(ofm_scale) for weight_scale in weight_scales] + # for some cases of the Mean operator, the scale must be calculated differently to match reference + if first_consumer_op.low_precision_scaling: + scales = [ + np.double(np.single(ifm_scale) / (np.single(weight_scale) * np.single(ofm_scale))) + for weight_scale in weight_scales + ] + else: + scales = [np.double(ifm_scale * weight_scale) / np.double(ofm_scale) for weight_scale in weight_scales] elif ifm_dtype == DataType.int8 or ifm_dtype == DataType.int16: scales = [ (np.double(ifm_scale) * np.double(weight_scale)) / np.double(ofm_scale) |