Initialisation du repository de Beta

venv/lib/python3.12/site-packages/onnxruntime/quantization/operators/concat.py

@@ -0,0 +1,62 @@
+import onnx
+
+from ..quant_utils import (  # noqa: F401
+    TENSOR_NAME_QUANT_SUFFIX,
+    QuantizedValue,
+    QuantizedValueType,
+    attribute_to_kwarg,
+    ms_domain,
+)
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase  # noqa: F401
+
+
+class QLinearConcat(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        (
+            q_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [*range(len(node.input))])
+        if not data_found or q_input_names is None:
+            return super().quantize()
+
+        # Create an entry for output quantized value
+        quantized_input_value = self.quantizer.quantized_value_map[node.input[0]]
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+            output_scale_name,
+            output_zp_name,
+            quantized_input_value.value_type,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        qnode_name = node.name + "_quant" if node.name else ""
+
+        qlconcat_inputs = [output_scale_name, output_zp_name]
+        for i in range(len(q_input_names)):
+            qlconcat_inputs.extend([q_input_names[i], scale_names[i], zero_point_names[i]])
+        qlconcat_node = onnx.helper.make_node(
+            "QLinearConcat", qlconcat_inputs, [quantized_output_value.q_name], qnode_name, **kwargs
+        )
+
+        self.quantizer.new_nodes += nodes
+        self.quantizer.new_nodes += [qlconcat_node]