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, Optional
from fusion_base import Fusion
from onnx import helper
from onnx_model import OnnxModel
logger = getLogger(__name__)
class FusionFastGelu(Fusion):
def __init__(self, model: OnnxModel):
super().__init__(model, "FastGelu", "Tanh")
def fuse(self, tanh_node, input_name_to_nodes: Dict, output_name_to_node: Dict):
if self.fuse_1(tanh_node, input_name_to_nodes, output_name_to_node):
return
if self.fuse_2(tanh_node, input_name_to_nodes, output_name_to_node):
return
if self.fuse_3(tanh_node, input_name_to_nodes, output_name_to_node):
return
def fuse_1(self, tanh_node, input_name_to_nodes, output_name_to_node) -> Optional[bool]:
"""
Fuse Gelu with tanh into one node:
+---------------------------+
| |
| v
[root] --> Pow --> Mul -----> Add --> Mul --> Tanh --> Add --> Mul
| (Y=3) (B=0.0447...) (B=0.7978...) (B=1) ^
| |
+------> Mul(B=0.5)--------------------------------------------+
Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine.
"""
if tanh_node.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[tanh_node.output[0]]
if len(children) != 1 or children[0].op_type != "Add":
return
add_after_tanh = children[0]
if not self.model.has_constant_input(add_after_tanh, 1.0):
return
if add_after_tanh.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[add_after_tanh.output[0]]
if len(children) != 1 or children[0].op_type != "Mul":
return
mul_after_tanh = children[0]
mul_half = self.model.match_parent(mul_after_tanh, "Mul", None, output_name_to_node)
if mul_half is None:
return
i = self.model.find_constant_input(mul_half, 0.5)
if i < 0:
return
root_input = mul_half.input[0 if i == 1 else 1]
# root_node could be None when root_input is graph input
root_node = self.model.get_parent(mul_half, 0 if i == 1 else 1, output_name_to_node)
mul_before_tanh = self.model.match_parent(tanh_node, "Mul", 0, output_name_to_node)
if mul_before_tanh is None:
return
i = self.model.find_constant_input(mul_before_tanh, 0.7978, delta=0.0001)
if i < 0:
return
add_before_tanh = self.model.match_parent(mul_before_tanh, "Add", 0 if i == 1 else 1, output_name_to_node)
if add_before_tanh is None:
return
mul_after_pow = self.model.match_parent(
add_before_tanh,
"Mul",
None,
output_name_to_node,
exclude=[root_node] if root_node else [],
)
if mul_after_pow is None:
return
i = self.model.find_constant_input(mul_after_pow, 0.0447, delta=0.0001)
if i < 0:
return
pow = self.model.match_parent(mul_after_pow, "Pow", 0 if i == 1 else 1, output_name_to_node)
if pow is None:
return
if not self.model.has_constant_input(pow, 3.0):
return
if pow.input[0] != root_input:
return
subgraph_nodes = [
mul_after_tanh,
mul_half,
add_after_tanh,
tanh_node,
mul_before_tanh,
add_before_tanh,
mul_after_pow,
pow,
]
if not self.model.is_safe_to_fuse_nodes(
subgraph_nodes,
[mul_after_tanh.output[0]],
input_name_to_nodes,
output_name_to_node,
):
return
self.nodes_to_remove.extend(subgraph_nodes)
fused_node = helper.make_node(
"FastGelu",
inputs=[root_input],
outputs=mul_after_tanh.output,
name=self.model.create_node_name("FastGelu"),
)
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
return True
def fuse_2(self, tanh_node, input_name_to_nodes: Dict, output_name_to_node: Dict) -> Optional[bool]:
"""
This pattern is from Tensorflow model.
Fuse Gelu with tanh into one node:
+---------------------------+
| |
| v
[root] --> Pow --> Mul -----> Add --> Mul --> Tanh --> Add --> Mul(B=0.5)-->Mul-->
| (Y=3) (B=0.0447...) (B=0.7978...) (B=1) ^
| |
+---------------------------------------------------------------------------+
Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine.
"""
if tanh_node.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[tanh_node.output[0]]
if len(children) != 1 or children[0].op_type != "Add":
return
add_after_tanh = children[0]
if not self.model.has_constant_input(add_after_tanh, 1.0):
return
if add_after_tanh.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[add_after_tanh.output[0]]
if len(children) != 1 or children[0].op_type != "Mul":
return
mul_half = children[0]
i = self.model.find_constant_input(mul_half, 0.5)
if i < 0:
return
if mul_half.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[mul_half.output[0]]
if len(children) != 1 or children[0].op_type != "Mul":
return
mul_after_mul_half = children[0]
root_node = self.model.get_parent(
mul_after_mul_half,
0 if mul_after_mul_half.input[1] == mul_half.output[0] else 1,
output_name_to_node,
)
if root_node is None:
return
mul_before_tanh = self.model.match_parent(tanh_node, "Mul", 0, output_name_to_node)
if mul_before_tanh is None:
return
i = self.model.find_constant_input(mul_before_tanh, 0.7978, delta=0.0001)
if i < 0:
return
add_before_tanh = self.model.match_parent(mul_before_tanh, "Add", 0 if i == 1 else 1, output_name_to_node)
if add_before_tanh is None:
return
mul_after_pow = self.model.match_parent(add_before_tanh, "Mul", None, output_name_to_node, exclude=[root_node])
if mul_after_pow is None:
return
i = self.model.find_constant_input(mul_after_pow, 0.0447, delta=0.0001)
if i < 0:
return
pow = self.model.match_parent(mul_after_pow, "Pow", 0 if i == 1 else 1, output_name_to_node)
if pow is None:
return
if not self.model.has_constant_input(pow, 3.0):
return
if pow.input[0] != root_node.output[0]:
return
subgraph_nodes = [
mul_after_mul_half,
mul_half,
add_after_tanh,
tanh_node,
mul_before_tanh,
add_before_tanh,
mul_after_pow,
pow,
]
if not self.model.is_safe_to_fuse_nodes(
subgraph_nodes,
[mul_after_mul_half.output[0]],
input_name_to_nodes,
output_name_to_node,
):
return
self.nodes_to_remove.extend(subgraph_nodes)
fused_node = helper.make_node(
"FastGelu",
inputs=[root_node.output[0]],
outputs=mul_after_mul_half.output,
name=self.model.create_node_name("FastGelu"),
)
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
return True
def fuse_3(self, tanh_node, input_name_to_nodes: Dict, output_name_to_node: Dict) -> Optional[bool]:
"""
OpenAI's gelu implementation, also used in Megatron:
Gelu(x) = x * 0.5 * (1.0 + torch.tanh(0.79788456 * x * (1.0 + 0.044715 * x * x)))
Fuse subgraph into a FastGelu node:
+------------ Mul (B=0.79788456) -------------------+
| |
+-------------------------------+ |
| | |
| v v
[root] --> Mul (B=0.044715) --> Mul --> Add(B=1) --> Mul --> Tanh --> Add(B=1) --> Mul-->
| ^
| |
+-----------> Mul (B=0.5) --------------------------------------------------------+
"""
if tanh_node.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[tanh_node.output[0]]
if len(children) != 1 or children[0].op_type != "Add":
return
add_after_tanh = children[0]
if not self.model.has_constant_input(add_after_tanh, 1.0):
return
if add_after_tanh.output[0] not in input_name_to_nodes:
return
children = input_name_to_nodes[add_after_tanh.output[0]]
if len(children) != 1 or children[0].op_type != "Mul":
return
mul_last = children[0]
mul_half = self.model.match_parent(mul_last, "Mul", None, output_name_to_node)
if mul_half is None:
return
i = self.model.find_constant_input(mul_half, 0.5)
if i < 0:
return
root_input = mul_half.input[0 if i == 1 else 1]
mul_before_tanh = self.model.match_parent(tanh_node, "Mul", 0, output_name_to_node)
if mul_before_tanh is None:
return
add_1 = self.model.match_parent(mul_before_tanh, "Add", None, output_name_to_node)
if add_1 is None:
return
j = self.model.find_constant_input(add_1, 1.0)
if j < 0:
return
mul_7978 = self.model.match_parent(mul_before_tanh, "Mul", None, output_name_to_node)
if mul_7978 is None:
return
k = self.model.find_constant_input(mul_7978, 0.7978, delta=0.0001)
if k < 0:
return
if mul_7978.input[0 if k == 1 else 1] != root_input:
return
mul_before_add_1 = self.model.match_parent(add_1, "Mul", 0 if j == 1 else 1, output_name_to_node)
if mul_before_add_1 is None:
return
if mul_before_add_1.input[0] == root_input:
another = 1
elif mul_before_add_1.input[1] == root_input:
another = 0
else:
return
mul_0447 = self.model.match_parent(mul_before_add_1, "Mul", another, output_name_to_node)
if mul_0447 is None:
return
m = self.model.find_constant_input(mul_0447, 0.0447, delta=0.0001)
if m < 0:
return
if mul_0447.input[0 if m == 1 else 1] != root_input:
return
subgraph_nodes = [
mul_0447,
mul_before_add_1,
add_1,
mul_before_tanh,
tanh_node,
add_after_tanh,
mul_7978,
mul_half,
mul_last,
]
if not self.model.is_safe_to_fuse_nodes(
subgraph_nodes,
[mul_last.output[0]],
input_name_to_nodes,
output_name_to_node,
):
return
self.nodes_to_remove.extend(subgraph_nodes)
fused_node = helper.make_node(
"FastGelu",
inputs=[root_input],
outputs=mul_last.output,
name=self.model.create_node_name("FastGelu"),
)
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
return True