m2m模型翻译
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# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
from logging import getLogger
from typing import Dict
from fusion_base import Fusion
from onnx import helper
from onnx_model import OnnxModel
logger = getLogger(__name__)
class FusionBiasSplitGelu(Fusion):
def __init__(self, model: OnnxModel):
super().__init__(model, "BiasSplitGelu", "Gelu")
def fuse(self, gelu_node, input_name_to_nodes: Dict, output_name_to_node: Dict):
"""
[root] --->Add --------------------> Slice ---------------> Mul -->
| ^ ^
| | |
+----------------------------+---Slice --> Gelu---+
| | ^
| |-----|
| | |
| Mul Mul
| ^ ^
v | |
Shape ---> Gather --> Add --> Div --+
"""
if gelu_node.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[gelu_node.output[0]]
if len(children) != 1 or children[0].op_type != "Mul":
return
mul_after_gelu = children[0]
slice_before_gelu = self.model.match_parent(gelu_node, "Slice", 0, output_name_to_node)
if slice_before_gelu is None:
return
if self.model.find_constant_input(slice_before_gelu, -1, delta=0.001) != 3:
return
add_output = slice_before_gelu.input[0]
start_index_nodes = self.model.match_parent_path(
slice_before_gelu,
["Div", "Add", "Gather", "Shape", "Add"],
[1, 0, 0, 0, 0],
output_name_to_node, # Mul(1) is optional
)
if start_index_nodes is None:
start_index_nodes = self.model.match_parent_path(
slice_before_gelu,
["Mul", "Div", "Add", "Gather", "Shape", "Add"],
[1, 0, 0, 0, 0, 0],
output_name_to_node,
)
if start_index_nodes is None or start_index_nodes[-2].input[0] != add_output:
return
end_index_nodes = self.model.match_parent_path(slice_before_gelu, ["Mul", "Div"], [2, 0], output_name_to_node)
if (
end_index_nodes is None or end_index_nodes[1] not in start_index_nodes
): # the Div is parent of both two Mul nodes
return
slice_before_mul = self.model.match_parent(mul_after_gelu, "Slice", 0, output_name_to_node)
if slice_before_mul is None:
return
if (
slice_before_mul.input[2] != slice_before_gelu.input[1]
): # end index of slice_before_mul is start index of slice_before_gelu
return
subgraph_nodes = start_index_nodes + [
end_index_nodes[0],
mul_after_gelu,
gelu_node,
slice_before_mul,
slice_before_gelu,
]
subgraph_output = mul_after_gelu.output[0]
if not self.model.is_safe_to_fuse_nodes(
subgraph_nodes, [subgraph_output], input_name_to_nodes, output_name_to_node
):
logger.info("Skip fuse BiasSplitGelu since it is not safe to fuse the subgraph.")
return
add_node = start_index_nodes[-1]
bias_index, _value = self.model.get_constant_input(add_node)
if not isinstance(bias_index, int):
return
self.nodes_to_remove.extend(subgraph_nodes)
node_name = self.model.create_node_name("BiasSplitGelu", name_prefix="BiasSplitGelu")
fused_node = helper.make_node(
"BiasSplitGelu",
inputs=[add_node.input[1 - bias_index], add_node.input[bias_index]],
outputs=[subgraph_output],
name=node_name,
)
fused_node.domain = "com.microsoft"
self.nodes_to_add.append(fused_node)
self.node_name_to_graph_name[node_name] = self.this_graph_name