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--- ori.openvino_backend.py 2024-03-21 12:35:49.552105914 -0700
+++ openvino_backend.py 2024-03-21 13:33:00.382049221 -0700
@@ -33,6 +33,8 @@
from nncf.quantization.algorithms.weight_compression.config import WeightCompressionParameters
from nncf.quantization.algorithms.weight_compression.weight_lowering import compress_weight
+from collections import OrderedDict
+import torch
class OVWeightCompressionAlgoBackend(WeightCompressionAlgoBackend):
def __init__(self, model: ov.Model):
@@ -123,6 +125,8 @@
def transform_model(
self, model: ov.Model, graph: NNCFGraph, weight_compression_parameters: Iterable[WeightCompressionParameters]
) -> ov.Model:
+ debug_wc = OrderedDict()
+
for wc_params in weight_compression_parameters:
compression_config = wc_params.compression_config
if compression_config.mode == CompressWeightsMode.NF4:
@@ -149,6 +153,13 @@
weight = Tensor(get_const_value(const_node))
original_shape = weight.shape
compressed_weight = compress_weight(weight, wc_params.reduction_axes, compression_config)
+ dkey = ".".join(const_node_name.split(".")[2:-1])
+ debug_wc[dkey] = {}
+ debug_wc[dkey]['original_shape'] = original_shape
+ debug_wc[dkey]['q_dtype'] = compression_dtype.type_name
+ debug_wc[dkey]['q_weight'] = compressed_weight.tensor.data
+ debug_wc[dkey]['q_scale'] = compressed_weight.scale.data
+ debug_wc[dkey]['q_zero_point'] = compressed_weight.zero_point.data
compressed_const = opset.constant(
compressed_weight.tensor.data, dtype=compression_dtype, name=const_node_name
@@ -182,6 +193,7 @@
# reset name_to_node_mapping
self.name_to_node_mapping = None
+ torch.save(debug_wc, 'llama-2-chat-7b_r0.8_g128.pth')
return model
@staticmethod
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