[Nuphar] Parse node doc_string for quantize info (#8746)

onnxruntime/core/providers/nuphar/scripts/model_quantizer.py

@@ -52,6 +52,53 @@ class QuantizeConfig:
                      ('QuantizationType', 'Signed' if self.sign_bit_ else 'Unsigned'),
                      ('ReservedBit', self.reserved_bits_)])
 
+def parse_custom_attributes(in_node):
+    if in_node.doc_string:
+        # some models have node description as qcfg, e.g.
+        # {"custom_attributes":{
+        #     "FutureContextLength":10,
+        #     "IntermediateBit":32,
+        #     "PerRowQuantization":true,
+        #     "QuantizeBitOfVector":8,
+        #     "VectorQuantizationType":"AsymmetricUnsigned",
+        #     "QuantizeBitOfMatrix":8,
+        #     "ReservedBitOfVector":1,
+        #     "MatrixQuantizationType":"AsymmetricSigned",
+        #     "ReservedBitOfMatrix":0}}
+        qcfg_str = in_node.doc_string
+        # make sure it's the string we can parse
+        if 'custom_attributes' in qcfg_str:
+            # some fixes to make it a valid JSON string, when model keys are not string
+            if qcfg_str[1] == 'c':
+                qcfg_str = qcfg_str.replace('{', '{"')
+                qcfg_str = qcfg_str.replace(',', ',"')
+                qcfg_str = qcfg_str.replace(':', '":')
+                qcfg_str = qcfg_str.replace('{"}', '{}')
+            qcfg = json.loads(qcfg_str)['custom_attributes']
+            if qcfg:
+                return qcfg
+    return None
+
+def parse_node_description(in_node):
+    if not in_node.doc_string:
+        return None
+    custom_qcfg = parse_custom_attributes(in_node)
+    if custom_qcfg:
+        assert custom_qcfg['IntermediateBit'] == 32
+        assert custom_qcfg['PerRowQuantization']
+        assert custom_qcfg['QuantizeBitOfVector'] == custom_qcfg['QuantizeBitOfMatrix']
+        qbits = custom_qcfg['QuantizeBitOfVector']
+        assert ("Asymmetric" in custom_qcfg['VectorQuantizationType']) == ("Asymmetric" in custom_qcfg['MatrixQuantizationType'])
+        symmetric = 0 if "Asymmetric" in custom_qcfg['VectorQuantizationType'] else 1
+        x_signed = 0 if "Unsigned" in custom_qcfg['VectorQuantizationType'] else 1
+        w_signed = 0 if "Unsigned" in custom_qcfg['MatrixQuantizationType'] else 1
+        x_reserved_bits = custom_qcfg['ReservedBitOfVector']
+        w_reserved_bits = custom_qcfg['ReservedBitOfMatrix']
+        return {'W' : dict(QuantizeConfig(signed=w_signed, reserved_bits=w_reserved_bits, type_bits=qbits)),
+                'X' : dict(QuantizeConfig(signed=x_signed, reserved_bits=x_reserved_bits, type_bits=qbits)),
+                'Symmetric' : symmetric}
+    return None
+
 def quantize_matmul_2d_with_weight(in_node, in_graph, nf, converted_weights, quantized_inputs, qcfg_dict, update_qcfg_dict, default_qcfg, onnx_opset_ver):
     assert in_node.op_type == 'MatMul'
 
@@ -68,7 +115,7 @@ def quantize_matmul_2d_with_weight(in_node, in_graph, nf, converted_weights, qua
     if in_node.output[0] in qcfg_dict:
         node_qcfg = qcfg_dict[in_node.output[0]]
     else:
-        node_qcfg = None
+        node_qcfg = parse_node_description(in_node)
         if not node_qcfg:
             if not update_qcfg_dict and qcfg_dict:
                 # when qcfg_dict is readonly, raise warning if qcfg is not found for this node