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|
ir_version: 7
producer_name: "pytorch"
producer_version: "CURRENT_VERSION"
graph {
node {
input: "input"
input: "weight"
input: "bias"
input: "running_mean"
input: "running_var"
output: "6"
name: "BatchNormalization_0"
op_type: "BatchNormalization"
attribute {
name: "epsilon"
f: 1e-05
type: FLOAT
}
attribute {
name: "momentum"
f: 0.9
type: FLOAT
}
attribute {
name: "training_mode"
i: 0
type: INT
}
}
name: "torch_jit"
initializer {
dims: 2
data_type: 1
name: "weight"
raw_data: "\000\000\200?\000\000\200?"
}
initializer {
dims: 2
data_type: 1
name: "bias"
raw_data: "\000\000\000\000\000\000\000\000"
}
initializer {
dims: 2
data_type: 1
name: "running_mean"
raw_data: "\000\000\000\000\000\000\000\000"
}
initializer {
dims: 2
data_type: 1
name: "running_var"
raw_data: "\000\000\200?\000\000\200?"
}
input {
name: "input"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
dim {
dim_value: 2
}
}
}
}
}
input {
name: "weight"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
}
}
}
}
input {
name: "bias"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
}
}
}
}
input {
name: "running_mean"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
}
}
}
}
input {
name: "running_var"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
}
}
}
}
output {
name: "6"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 2
}
dim {
dim_value: 2
}
}
}
}
}
}
opset_import {
version: 14
}
|
