Initialisation du repository de Beta

venv/lib/python3.12/site-packages/onnxruntime/transformers/fusion_biasgelu.py

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+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from logging import getLogger
+
+from fusion_base import Fusion
+from fusion_utils import NumpyHelper
+from onnx import helper
+from onnx_model import OnnxModel
+
+logger = getLogger(__name__)
+
+
+class FusionBiasGelu(Fusion):
+    def __init__(self, model: OnnxModel, is_fastgelu):
+        if is_fastgelu:
+            super().__init__(model, "FastGelu", "FastGelu", "add bias")
+        else:
+            super().__init__(model, "BiasGelu", "Gelu")
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        gelu_op_type = node.op_type
+        fuse_op_type = "BiasGelu" if gelu_op_type == "Gelu" else "FastGelu"
+
+        if len(node.input) != 1:
+            return
+
+        nodes = self.model.match_parent_path(node, ["Add", "MatMul"], [0, None])
+        if nodes is None:
+            return
+        (add, matmul) = nodes
+
+        bias_weight = None
+        # bias should be one dimension
+        bias_index = -1
+        for i, input in enumerate(add.input):
+            initializer = self.model.get_initializer(input)
+            if initializer is None:
+                continue
+            bias_index = i
+            bias_weight = NumpyHelper.to_array(initializer)
+            break
+        if bias_weight is None:
+            return
+        if len(bias_weight.shape) != 1:
+            return
+
+        subgraph_nodes = [node, add]
+        if not self.model.is_safe_to_fuse_nodes(
+            subgraph_nodes, [node.output[0]], input_name_to_nodes, output_name_to_node
+        ):
+            return
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+
+        fused_node = helper.make_node(
+            fuse_op_type,
+            inputs=[matmul.output[0], add.input[bias_index]],
+            outputs=node.output,
+            name=self.model.create_node_name(fuse_op_type, gelu_op_type + "_AddBias_"),
+        )
+        fused_node.domain = "com.microsoft"
+        self.nodes_to_add.append(fused_node)
+        self.node_name_to_graph_name[fused_node.name] = self.this_graph_name