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高魏洪
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fix: ResourcePoolInsufficientCapacity error
1 parent a07f20b commit 332359d

4 files changed

Lines changed: 186 additions & 8 deletions

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‎__tests__/e2e/scaling/s_149.yaml‎

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edition: 3.0.0
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name: test-scaling-config
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access: quanxi_149
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resources:
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fcDemo:
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component: ${env('fc_component_version', path('../../../'))}
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props:
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region: cn-hangzhou
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functionName: fc3-scaling-pool-149-${env('fc_component_function_name', 'scaling')}
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code: ./code
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handler: index.handler
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timeout: 60
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logConfig: auto
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gpuConfig:
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gpuMemorySize: 49152
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gpuType: fc.gpu.ada.1
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runtime: custom-container
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cpu: 8
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customContainerConfig:
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image: >-
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registry.cn-shanghai.aliyuncs.com/serverless_devs/custom-container-http-examples:springboot
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port: 9000
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instanceConcurrency: 20
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memorySize: 65536
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diskSize: 10240
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provisionConfig:
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defaultTarget: 1
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alwaysAllocateCPU: false
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alwaysAllocateGPU: false
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# scalingConfig:
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# # residentPoolId: fc-pool-5f044a31f87171jkwaraws
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# minInstances: 1
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‎__tests__/e2e/scaling/scalingConfig_provisionConfig.py‎

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#!/usr/bin/env python3
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"""
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Test the conversion between scalingConfig and provisionConfig, as well as the conversion between GPUs of the same type and different types.
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"""
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import subprocess
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import yaml
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s_yaml_file = f"s_149.yaml"
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def deploy_function(scalingConfig, provisionConfig, gpuConfig=None, memorySize=None):
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"""
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部署函数
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根据 scalingConfig 或 provisionConfig 创建函数
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"""
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print(f"scalingConfig: {scalingConfig} provisionConfig: {provisionConfig}")
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# 使用当前文件夹下的s.yaml内容作为基础配置
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with open("s_149.yaml", "r", encoding="utf-8") as f:
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s_yaml = yaml.safe_load(f)
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s_yaml["resources"]["fcDemo"]["props"]["scalingConfig"] = scalingConfig
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s_yaml["resources"]["fcDemo"]["props"]["provisionConfig"] = provisionConfig
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if gpuConfig:
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s_yaml["resources"]["fcDemo"]["props"]["gpuConfig"] = gpuConfig
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if memorySize:
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s_yaml["resources"]["fcDemo"]["props"]["memorySize"] = memorySize
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with open(s_yaml_file, "w", encoding="utf-8") as f:
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yaml.dump(s_yaml, f, default_flow_style=False, allow_unicode=True)
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print(f"使用配置文件部署: {s_yaml_file}")
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# 执行部署命令
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print("正在部署...")
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subprocess.check_call(f"s deploy -y -t {s_yaml_file} --skip-push", shell=True)
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def cleanup_deployment():
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"""
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清理部署
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"""
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print(f"正在清理部署: {s_yaml_file}")
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subprocess.check_call(f"s remove -y -t {s_yaml_file}", shell=True)
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def main():
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"""
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主函数
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修改 scalingConfig 和 provisionConfig，并测试转换
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"""
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subprocess.check_call(f"s deploy -y -t {s_yaml_file} --skip-push", shell=True)
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# GPU remains unchanged
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# 弹性 ----> 弹性
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scalingConfig = {
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"minInstances": 1,
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}
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provisionConfig = {}
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deploy_function(scalingConfig, provisionConfig)
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# 弹性 ----> 常驻
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scalingConfig = {
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"residentPoolId": "fc-pool-5f044a31f87171jkwaraws",
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"maxInstances": 1,
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}
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provisionConfig = {}
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deploy_function(scalingConfig, provisionConfig)
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# 常驻 ----> 常驻
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scalingConfig = {
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# "residentPoolId": "fc-pool-5f044a31f87171jkwaraws",
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"maxInstances": 1,
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}
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provisionConfig = {}
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deploy_function(scalingConfig, provisionConfig)
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# 常驻 ----> 弹性
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scalingConfig = {
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"minInstances": 1,
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}
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provisionConfig = {}
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deploy_function(scalingConfig, provisionConfig)
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cleanup_deployment()
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# GPU remains changed
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# 弹性 ----> 弹性
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scalingConfig = {
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"minInstances": 1,
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}
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gpuConfig = {
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"gpuType": "fc.gpu.tesla.1",
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"gpuMemorySize": 1,
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}
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provisionConfig = {}
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memorySize = 32768
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deploy_function(scalingConfig, provisionConfig, gpuConfig, memorySize)
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# 弹性 ----> 常驻
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scalingConfig = {
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"residentPoolId": "fc-pool-16bedd56db9626uva1it08",
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"maxInstances": 1,
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}
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gpuConfig = {
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"gpuType": "fc.gpu.ada.1",
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"gpuMemorySize": 1,
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}
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provisionConfig = {}
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memorySize = 65536
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deploy_function(scalingConfig, provisionConfig, gpuConfig, memorySize)
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# 常驻 ----> 常驻
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scalingConfig = {
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"residentPoolId": "fc-pool-16bedd56db96260yid15cs",
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"maxInstances": 1,
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}
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gpuConfig = {
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"gpuType": "fc.gpu.ada.2",
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"gpuMemorySize": 1,
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}
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provisionConfig = {}
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memorySize = 32768
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deploy_function(scalingConfig, provisionConfig, gpuConfig, memorySize)
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# 常驻 ----> 弹性
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scalingConfig = {
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"minInstances": 1,
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}
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gpuConfig = {
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"gpuType": "fc.gpu.tesla.1",
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"gpuMemorySize": 1,
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}
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provisionConfig = {}
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memorySize = 32768
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deploy_function(scalingConfig, provisionConfig, gpuConfig, memorySize)
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cleanup_deployment()

‎src/resources/fc/error-code.ts‎

Lines changed: 8 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -10,6 +10,7 @@ export enum FC_API_ERROR_CODE {
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AliasAlreadyExists = 'AliasAlreadyExists', // 别名已存在
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ProvisionConfigExist = 'ProvisionConfigExist', // 预配置存在
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ResidentScalingConfigExists = 'ResidentScalingConfigExists', // 常驻资源池预配置存在
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ResourcePoolInsufficientCapacity = 'ResourcePoolInsufficientCapacity', // 资源池无容量
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}
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export const isSlsNotExistException = (project: string, logstore: string, ex) => {
@@ -57,12 +58,13 @@ export const isFunctionScalingConfigError = (
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{ localGPUType = '', remoteGPUType = '', functionName = 'F' },
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) => {
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if (
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(isInvalidArgument(ex) &&
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ex.message.includes('GPU type should not be changed with resident scaling config')) ||
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ex.message.includes(
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`function gpu type '${localGPUType}' doesn't match resident pool gpu type '${remoteGPUType}'`,
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) ||
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ex.message.includes(`idle provision config exists for function '${functionName}'`)
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isInvalidArgument(ex) &&
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(ex.message.includes('GPU type should not be changed with resident scaling config') ||
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ex.message.includes(
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`function gpu type '${localGPUType}' doesn't match resident pool gpu type '${remoteGPUType}'`,
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) ||
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ex.message.includes(`idle provision config exists for function '${functionName}'`) ||
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ex.code === FC_API_ERROR_CODE.ResourcePoolInsufficientCapacity)
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) {
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return true;
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}

‎src/resources/fc/index.ts‎

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Original file line numberDiff line numberDiff line change
@@ -311,6 +311,8 @@ export default class FC extends FC_Client {
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throw ex;
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}
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retryInterval = 5;
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} else if (retry > FC_DEPLOY_RETRY_COUNT) {
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throw ex;
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} else if (
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isFunctionScalingConfigError(ex, {
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localGPUType,
@@ -330,8 +332,6 @@ export default class FC extends FC_Client {
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isFunctionStateWaitTimedOut(ex)
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) {
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throw ex;
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} else if (retry > FC_DEPLOY_RETRY_COUNT) {
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throw ex;
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}
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retry += 1;
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if (isAppCenter()) {

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