What does t MQTT_MSG_TYPE_PINGRESP mean?

I am getting following thing I don't exaclty know that mqtt broker is working fine or not. but I want to understand the error ..

Every ~120seconds, ESP32 will send PING msg to server for keepalive, server will response with MQTT_MSG_TYPE_PINGRESP

ok I understand while I am testing this with nodeRed
I made nodered program to send a delayed message when it receives something from esp32. but somehow it restarts after 2 restarts its works ok. I am sorry for this long log.
`[MQTT INFO] Connected!
[MQTT INFO] Connected to server <IP_ADDRESS>:1883
[MQTT INFO] Sending MQTT CONNECT message, type: 1, id: 0000
[MQTT INFO] Reading MQTT CONNECT response message
[MQTT INFO] Connected
[MQTT INFO] Connected to MQTT broker, create sending thread before call connected callback
[MQTT INFO] mqtt_sending_task
[MQTT INFO] Queue subscribe, topic"/testESP1", id: 1
[MQTT INFO] Sending...16 bytes
[MQTT INFO] Sending...18 bytes
[MQTT INFO] Queuing publish, length: 18, queue size(0/4096)

[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 24
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 11/11 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[11/11 bytes]
[APP] DATA: Received Ok
f task=mqt a=0x3ffaf238 h=1a2b3c4d t=1a2b3c0a
abort() was called at PC 0x40083779 on core 0
Guru Meditation Error: Core  0 panic'ed (abort)

Backtrace: 0x40009203:0x3ffc4cb0 0x40082ed5:0x3ffc4cd0 0x400833d2:0x3ffc4cf0 0x400864a0:0x3ffc4d10 0x400820d4:0x3ffc4d30 0x4000beca:0x3ffc4d50 0x4011183c:0x3ffc4d70 0x401134a4:0x3ffc4d90 0x401135b1:0x3ffc4de0 0x401136a1:0x3ffc4e00

Rebooting...
ets Jun  8 2016 00:22:57

rst:0xc (SW_CPU_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0x00
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:2
load:0x3fff0008,len:8
load:0x3fff0010,len:4412
ho 0 tail 12 room 4
load:0x40078000,len:11092
load:0x40080000,len:252
entry 0x40080034
I (48) boot: ESP-IDF v2.0-rc1-877-g636d2b3-dirty 2nd stage bootloader
I (48) boot: compile time 19:29:54
I (52) boot: Enabling RNG early entropy source...
I (68) boot: SPI Speed      : 40MHz
I (81) boot: SPI Mode       : DIO
I (93) boot: SPI Flash Size : 4MB
I (106) boot: Partition Table:
I (117) boot: ## Label            Usage          Type ST Offset   Length
I (140) boot:  0 nvs              WiFi data        01 02 00009000 00006000
I (163) boot:  1 phy_init         RF data          01 01 0000f000 00001000
I (186) boot:  2 factory          factory app      00 00 00010000 00100000
I (210) boot: End of partition table
I (222) boot: Disabling RNG early entropy source...
I (240) boot: Loading app partition at offset 00010000
I (946) boot: segment 0: paddr=0x00010018 vaddr=0x00000000 size=0x0ffe8 ( 65512)
I (946) boot: segment 1: paddr=0x00020008 vaddr=0x3f400010 size=0x09c7c ( 40060) map
I (962) boot: segment 2: paddr=0x00029c8c vaddr=0x3ffb0000 size=0x02400 (  9216) load
I (992) boot: segment 3: paddr=0x0002c094 vaddr=0x40080000 size=0x00400 (  1024) load
I (1015) boot: segment 4: paddr=0x0002c49c vaddr=0x40080400 size=0x12ba4 ( 76708) load
I (1078) boot: segment 5: paddr=0x0003f048 vaddr=0x400c0000 size=0x00000 (     0) load
I (1079) boot: segment 6: paddr=0x0003f050 vaddr=0x00000000 size=0x00fb8 (  4024)
I (1100) boot: segment 7: paddr=0x00040010 vaddr=0x400d0018 size=0x4832c (295724) map
I (1126) cpu_start: Pro cpu up.
I (1137) cpu_start: Single core mode
I (1151) heap_alloc_caps: Initializing. RAM available for dynamic allocation:
I (1175) heap_alloc_caps: At 3FFAE2A0 len 00001D60 (7 KiB): DRAM
I (1195) heap_alloc_caps: At 3FFB7628 len 000289D8 (162 KiB): DRAM
I (1216) heap_alloc_caps: At 3FFE0440 len 00003BC0 (14 KiB): D/IRAM
I (1238) heap_alloc_caps: At 3FFE4350 len 0001BCB0 (111 KiB): D/IRAM
I (1259) heap_alloc_caps: At 40092FA4 len 0000D05C (52 KiB): IRAM
check b=0x3ffae2ac size=7496 ok
check b=0x3ffafff4 size=0 ok
check b=0x3ffb7634 size=166336 ok
check b=0x3ffdfff4 size=0 ok
check b=0x3ffe044c size=15272 ok
check b=0x3ffe3ff4 size=0 ok
check b=0x3ffe435c size=113816 ok
check b=0x3ffffff4 size=0 ok
check b=0x40092fb0 size=53316 ok
I (1358) cpu_start: Pro cpu start user code
I (1414) cpu_start: Starting scheduler on PRO CPU.
[APP] Startup..
[APP] Free memory: 290852 bytes
[APP] SDK version: master, Build time: 2017-Jun-30_12:39:16_IST
E (1491) wifi: esp_wifi_set_auto_connect 1270 wifi is not init
[APP] Start, connect to Wifi network: UNICORN ..
I (1497) wifi: wifi firmware version: 8a1ad86
I (1500) wifi: config NVS flash: enabled
I (1503) wifi: config nano formating: disabled
I (1508) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1517) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1579) wifi: Init dynamic tx buffer num: 32
I (1579) wifi: Init dynamic rx buffer num: 32
I (1579) wifi: wifi driver task: 3ffbc794, prio:23, stack:4096
I (1582) wifi: Init static rx buffer num: 10
I (1585) wifi: Init dynamic rx buffer num: 32
I (1590) wifi: Init rx ampdu len mblock:7
I (1593) wifi: Init lldesc rx ampdu entry mblock:4
I (1598) wifi: wifi power manager task: 0x3ffc1c94 prio: 21 stack: 2560
I (1605) wifi: wifi timer task: 3ffc2d3c, prio:22, stack:3584
I (1634) phy: phy_version: 354.0, b2dba61, May 16 2017, 21:41:06, 0, 0
I (1635) wifi: mode : sta (24:0a:c4:01:1b:34)
I (1758) wifi: n:11 0, o:1 0, ap:255 255, sta:11 0, prof:1
I (2746) wifi: state: init -> auth (b0)
I (2748) wifi: state: auth -> assoc (0)
I (2755) wifi: state: assoc -> run (10)
I (2772) wifi: connected with UNICORN, channel 11
I (3453) event: ip: <IP_ADDRESS>, mask: <IP_ADDRESS>, gw: <IP_ADDRESS>
[MQTT INFO] Connecting to server <IP_ADDRESS>:1883,23303
[MQTT INFO] Connected!
[MQTT INFO] Connected to server <IP_ADDRESS>:1883
[MQTT INFO] Sending MQTT CONNECT message, type: 1, id: 0000
[MQTT INFO] Reading MQTT CONNECT response message
[MQTT INFO] Connected
[MQTT INFO] Connected to MQTT broker, create sending thread before call connected callback
[MQTT INFO] mqtt_sending_task
[MQTT INFO] Queue subscribe, topic"/testESP1", id: 1
[MQTT INFO] Sending...16 bytes
[MQTT INFO] Sending...18 bytes
[MQTT INFO] Queuing publish, length: 18, queue size(0/4096)

[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 24
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 11/11 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[11/11 bytes]
[APP] DATA: Received Ok
f task=mqt a=0x3ffaf238 h=1a2b3c4d t=1a2b3c0a
abort() was called at PC 0x40083779 on core 0
Guru Meditation Error: Core  0 panic'ed (abort)

Backtrace: 0x40009203:0x3ffc4cd0 0x40082ed5:0x3ffc4cf0 0x400833d2:0x3ffc4d10 0x400864a0:0x3ffc4d30 0x400820d4:0x3ffc4d50 0x4000beca:0x3ffc4d70 0x4011183c:0x3ffc4d90 0x401134a4:0x3ffc4db0 0x401135b1:0x3ffc4e00 0x401136a1:0x3ffc4e20

Rebooting...
ets Jun  8 2016 00:22:57

rst:0xc (SW_CPU_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0x00
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:2
load:0x3fff0008,len:8
load:0x3fff0010,len:4412
ho 0 tail 12 room 4
load:0x40078000,len:11092
load:0x40080000,len:252
entry 0x40080034
I (48) boot: ESP-IDF v2.0-rc1-877-g636d2b3-dirty 2nd stage bootloader
I (48) boot: compile time 19:29:54
I (52) boot: Enabling RNG early entropy source...
I (68) boot: SPI Speed      : 40MHz
I (81) boot: SPI Mode       : DIO
I (93) boot: SPI Flash Size : 4MB
I (106) boot: Partition Table:
I (117) boot: ## Label            Usage          Type ST Offset   Length
I (140) boot:  0 nvs              WiFi data        01 02 00009000 00006000
I (163) boot:  1 phy_init         RF data          01 01 0000f000 00001000
I (186) boot:  2 factory          factory app      00 00 00010000 00100000
I (210) boot: End of partition table
I (222) boot: Disabling RNG early entropy source...
I (240) boot: Loading app partition at offset 00010000
I (946) boot: segment 0: paddr=0x00010018 vaddr=0x00000000 size=0x0ffe8 ( 65512)
I (946) boot: segment 1: paddr=0x00020008 vaddr=0x3f400010 size=0x09c7c ( 40060) map
I (962) boot: segment 2: paddr=0x00029c8c vaddr=0x3ffb0000 size=0x02400 (  9216) load
I (992) boot: segment 3: paddr=0x0002c094 vaddr=0x40080000 size=0x00400 (  1024) load
I (1015) boot: segment 4: paddr=0x0002c49c vaddr=0x40080400 size=0x12ba4 ( 76708) load
I (1078) boot: segment 5: paddr=0x0003f048 vaddr=0x400c0000 size=0x00000 (     0) load
I (1079) boot: segment 6: paddr=0x0003f050 vaddr=0x00000000 size=0x00fb8 (  4024)
I (1100) boot: segment 7: paddr=0x00040010 vaddr=0x400d0018 size=0x4832c (295724) map
I (1126) cpu_start: Pro cpu up.
I (1137) cpu_start: Single core mode
I (1151) heap_alloc_caps: Initializing. RAM available for dynamic allocation:
I (1175) heap_alloc_caps: At 3FFAE2A0 len 00001D60 (7 KiB): DRAM
I (1195) heap_alloc_caps: At 3FFB7628 len 000289D8 (162 KiB): DRAM
I (1216) heap_alloc_caps: At 3FFE0440 len 00003BC0 (14 KiB): D/IRAM
I (1238) heap_alloc_caps: At 3FFE4350 len 0001BCB0 (111 KiB): D/IRAM
I (1259) heap_alloc_caps: At 40092FA4 len 0000D05C (52 KiB): IRAM
check b=0x3ffae2ac size=7496 ok
check b=0x3ffafff4 size=0 ok
check b=0x3ffb7634 size=166336 ok
check b=0x3ffdfff4 size=0 ok
check b=0x3ffe044c size=15272 ok
check b=0x3ffe3ff4 size=0 ok
check b=0x3ffe435c size=113816 ok
check b=0x3ffffff4 size=0 ok
check b=0x40092fb0 size=53316 ok
I (1358) cpu_start: Pro cpu start user code
I (1414) cpu_start: Starting scheduler on PRO CPU.
[APP] Startup..
[APP] Free memory: 290852 bytes
[APP] SDK version: master, Build time: 2017-Jun-30_12:39:16_IST
E (1491) wifi: esp_wifi_set_auto_connect 1270 wifi is not init
[APP] Start, connect to Wifi network: UNICORN ..
I (1497) wifi: wifi firmware version: 8a1ad86
I (1500) wifi: config NVS flash: enabled
I (1503) wifi: config nano formating: disabled
I (1508) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1517) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1532) wifi: Init dynamic tx buffer num: 32
I (1532) wifi: Init dynamic rx buffer num: 32
I (1535) wifi: wifi driver task: 3ffbc6fc, prio:23, stack:4096
I (1541) wifi: Init static rx buffer num: 10
I (1544) wifi: Init dynamic rx buffer num: 32
I (1549) wifi: Init rx ampdu len mblock:7
I (1552) wifi: Init lldesc rx ampdu entry mblock:4
I (1557) wifi: wifi power manager task: 0x3ffc1c54 prio: 21 stack: 2560
I (1564) wifi: wifi timer task: 3ffc2d24, prio:22, stack:3584
I (1618) phy: phy_version: 354.0, b2dba61, May 16 2017, 21:41:06, 0, 0
I (1619) wifi: mode : sta (24:0a:c4:01:1b:34)
I (1742) wifi: n:11 0, o:1 0, ap:255 255, sta:11 0, prof:1
I (2729) wifi: state: init -> auth (b0)
I (2737) wifi: state: auth -> assoc (0)
I (2747) wifi: state: assoc -> run (10)
I (2768) wifi: connected with UNICORN, channel 11
I (3435) event: ip: <IP_ADDRESS>, mask: <IP_ADDRESS>, gw: <IP_ADDRESS>
[MQTT INFO] Connecting to server <IP_ADDRESS>:1883,23303
[MQTT INFO] Connected!
[MQTT INFO] Connected to server <IP_ADDRESS>:1883
[MQTT INFO] Sending MQTT CONNECT message, type: 1, id: 0000
[MQTT INFO] Reading MQTT CONNECT response message
[MQTT INFO] Connected
[MQTT INFO] Connected to MQTT broker, create sending thread before call connected callback
[MQTT INFO] mqtt_sending_task
[MQTT INFO] Queue subscribe, topic"/testESP1", id: 1
[MQTT INFO] Sending...16 bytes
[MQTT INFO] Sending...18 bytes
[MQTT INFO] Queuing publish, length: 18, queue size(0/4096)

[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 24
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 11/11 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[11/11 bytes]
[APP] DATA: Received Ok
[MQTT INFO] Read len 28
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 15/15 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[15/15 bytes]
[APP] DATA: Broker received
I (12748) wifi: pm start, type:0

[MQTT INFO] Sending pingreq
[MQTT INFO] Read len 2
[MQTT INFO] MQTT_MSG_TYPE_PINGRESP
[MQTT INFO] Sending pingreq
[MQTT INFO] Read len 2
[MQTT INFO] MQTT_MSG_TYPE_PINGRESP
`

this was the nodeRed program and but first I used trigger that was first sending a msg wait for 250ms and send another msg now I changed it to send nothing wait for  255ms and send Msg OK received. but I think there is still some problem let me check more after a long interval of staying idle the device resets or something happens just waiting it to happen again.

It restarts or something... 29 times sending pingreq ...
here it is
[MQTT INFO] MQTT_MSG_TYPE_PINGRESP
[MQTT INFO] Sending pingreq       << --- 29 th pingreq
[MQTT INFO] Read len 2
[MQTT INFO] MQTT_MSG_TYPE_PINGRESP
I (1812683) wifi: state: run -> auth (2c0)
I (1812684) wifi: n:11 0, o:11 0, ap:255 255, sta:11 0, prof:1
I (1812684) wifi: pm stop, total sleep time: 0/1799971734

[MQTT INFO] Read len 0
[MQTT INFO] network disconnected
I (1812809) wifi: n:11 0, o:11 0, ap:255 255, sta:11 0, prof:1
I (1812810) wifi: state: auth -> auth (b0)
I (1812815) wifi: state: auth -> assoc (0)
I (1812821) wifi: state: assoc -> run (10)
I (1812834) wifi: connected with UNICORN, channel 11
I (1813454) event: ip: xxxxxx, mask: <IP_ADDRESS>, gw: xxxxxxxxx
[MQTT INFO] Connecting to server xxxxxxxx:1883,23303
[MQTT INFO] Connected!
[MQTT INFO] Connected to server xxxxxxxxxx:1883
[MQTT INFO] Sending MQTT CONNECT message, type: 1, id: 0000
[MQTT INFO] Reading MQTT CONNECT response message
[MQTT INFO] Connected
[MQTT INFO] Connected to MQTT broker, create sending thread before call connected callback
[MQTT INFO] mqtt_sending_task
[MQTT INFO] Queue subscribe, topic"/testESP1", id: 1
[MQTT INFO] Sending...16 bytes
[MQTT INFO] Sending...18 bytes
[MQTT INFO] Queuing publish, length: 18, queue size(0/4096)

[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 36
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 23/23 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[23/23 bytes]
[APP] DATA: Broker: Msg OK received
I (1822822) wifi: pm start, type:0

https://github.com/espressif/esp32-at/issues/12 this does not solve the problem either......
its restarts multiple times .. and then it works fine after 4-5 restarts.
`
[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 36
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 23/23 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[23/23 bytes]
[APP] DATA: Broker: Msg OK received⸮
Z⸮⸮V⸮o⸮:
f task=mqt a=0x3ffaf238 h=1a2b3c4d t=d9d45a0a
abort() was called at PC 0x40083779 on core 0
Guru Meditation Error: Core  0 panic'ed (abort)

Backtrace: 0x40009203:0x3ffc4b20 0x40082ed5:0x3ffc4b40 0x400833d2:0x3ffc4b60 0x400864a0:0x3ffc4b80 0x400820d4:0x3ffc4ba0 0x4000beca:0x3ffc4bc0 0x4011183c:0x3ffc4be0 0x401134a4:0x3ffc4c00 0x401135b1:0x3ffc4c50 0x401136a1:0x3ffc4c70

Rebooting...
ets Jun  8 2016 00:22:57

rst:0xc (SW_CPU_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0x00
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:2
load:0x3fff0008,len:8
load:0x3fff0010,len:4412
ho 0 tail 12 room 4
load:0x40078000,len:11092
load:0x40080000,len:252
entry 0x40080034
I (48) boot: ESP-IDF v2.0-rc1-877-g636d2b3-dirty 2nd stage bootloader
I (48) boot: compile time 19:29:54
I (52) boot: Enabling RNG early entropy source...
I (68) boot: SPI Speed      : 40MHz
I (81) boot: SPI Mode       : DIO
I (93) boot: SPI Flash Size : 4MB
I (106) boot: Partition Table:
I (117) boot: ## Label            Usage          Type ST Offset   Length
I (140) boot:  0 nvs              WiFi data        01 02 00009000 00006000
I (163) boot:  1 phy_init         RF data          01 01 0000f000 00001000
I (186) boot:  2 factory          factory app      00 00 00010000 00100000
I (210) boot: End of partition table
I (222) boot: Disabling RNG early entropy source...
I (240) boot: Loading app partition at offset 00010000
I (946) boot: segment 0: paddr=0x00010018 vaddr=0x00000000 size=0x0ffe8 ( 65512)
I (946) boot: segment 1: paddr=0x00020008 vaddr=0x3f400010 size=0x09c7c ( 40060) map
I (962) boot: segment 2: paddr=0x00029c8c vaddr=0x3ffb0000 size=0x02400 (  9216) load
I (992) boot: segment 3: paddr=0x0002c094 vaddr=0x40080000 size=0x00400 (  1024) load
I (1015) boot: segment 4: paddr=0x0002c49c vaddr=0x40080400 size=0x12ba4 ( 76708) load
I (1078) boot: segment 5: paddr=0x0003f048 vaddr=0x400c0000 size=0x00000 (     0) load
I (1079) boot: segment 6: paddr=0x0003f050 vaddr=0x00000000 size=0x00fb8 (  4024)
I (1100) boot: segment 7: paddr=0x00040010 vaddr=0x400d0018 size=0x4832c (295724) map
I (1126) cpu_start: Pro cpu up.
I (1137) cpu_start: Single core mode
I (1151) heap_alloc_caps: Initializing. RAM available for dynamic allocation:
I (1175) heap_alloc_caps: At 3FFAE2A0 len 00001D60 (7 KiB): DRAM
I (1195) heap_alloc_caps: At 3FFB7628 len 000289D8 (162 KiB): DRAM
I (1216) heap_alloc_caps: At 3FFE0440 len 00003BC0 (14 KiB): D/IRAM
I (1238) heap_alloc_caps: At 3FFE4350 len 0001BCB0 (111 KiB): D/IRAM
I (1259) heap_alloc_caps: At 40092FA4 len 0000D05C (52 KiB): IRAM
check b=0x3ffae2ac size=7496 ok
check b=0x3ffafff4 size=0 ok
check b=0x3ffb7634 size=166336 ok
check b=0x3ffdfff4 size=0 ok
check b=0x3ffe044c size=15272 ok
check b=0x3ffe3ff4 size=0 ok
check b=0x3ffe435c size=113816 ok
check b=0x3ffffff4 size=0 ok
check b=0x40092fb0 size=53316 ok
I (1358) cpu_start: Pro cpu start user code
I (1414) cpu_start: Starting scheduler on PRO CPU.
[APP] Startup..
[APP] Free memory: 290852 bytes
[APP] SDK version: master, Build time: 2017-Jun-30_15:07:44_IST
E (1519) wifi: esp_wifi_set_auto_connect 1270 wifi is not init
[APP] Start, connect to Wifi network: UNICORN ..
I (1521) wifi: wifi firmware version: 8a1ad86
I (1524) wifi: config NVS flash: enabled
I (1527) wifi: config nano formating: disabled
I (1532) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1541) system_api: Base MAC address is not set, read default base MAC address from BLK0 of EFUSE
I (1556) wifi: Init dynamic tx buffer num: 32
I (1556) wifi: Init dynamic rx buffer num: 32
I (1559) wifi: wifi driver task: 3ffbc564, prio:23, stack:4096
I (1565) wifi: Init static rx buffer num: 10
I (1568) wifi: Init dynamic rx buffer num: 32
I (1573) wifi: Init rx ampdu len mblock:7
I (1576) wifi: Init lldesc rx ampdu entry mblock:4
I (1581) wifi: wifi power manager task: 0x3ffc1abc prio: 21 stack: 2560
I (1588) wifi: wifi timer task: 3ffc2b8c, prio:22, stack:3584
I (1614) phy: phy_version: 354.0, b2dba61, May 16 2017, 21:41:06, 0, 0
I (1615) wifi: mode : sta (24:0a:c4:01:1b:34)
I (1738) wifi: n:11 0, o:1 0, ap:255 255, sta:11 0, prof:1
I (2726) wifi: state: init -> auth (b0)
I (2731) wifi: state: auth -> assoc (0)
I (2737) wifi: state: assoc -> run (10)
I (2750) wifi: connected with UNICORN, channel 11
I (3433) event: ip: <IP_ADDRESS>, mask: <IP_ADDRESS>, gw: <IP_ADDRESS>
[MQTT INFO] Connecting to server <IP_ADDRESS>:1883,23303
[MQTT INFO] Connected!
[MQTT INFO] Connected to server <IP_ADDRESS>:1883
[MQTT INFO] Sending MQTT CONNECT message, type: 1, id: 0000
[MQTT INFO] Reading MQTT CONNECT response message
[MQTT INFO] Connected
[MQTT INFO] Connected to MQTT broker, create sending thread before call connected callback
[MQTT INFO] mqtt_sending_task
[MQTT INFO] Queue subscribe, topic"/testESP1", id: 1
[MQTT INFO] Sending...16 bytes
[MQTT INFO] Sending...18 bytes
[MQTT INFO] Queuing publish, length: 18, queue size(0/4096)

[MQTT INFO] mqtt_start_receive_schedule
[MQTT INFO] Read len 5
[MQTT INFO] Read len 36
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 23/23 bytes
[APP] Publish topic: /testESP1
[APP] Publish data[23/23 bytes]
[APP] DATA: Broker: Msg OK received:
⸮m⸮⸮S⸮⸮
I (12737) wifi: pm start, type:0

`

issue 2 is happening always. after 29 times ..

[MQTT INFO] Read len 2
[MQTT INFO] MQTT_MSG_TYPE_PINGRESP
I (1812826) wifi: state: run -> auth (2c0)
I (1812827) wifi: n:11 0, o:11 0, ap:255 255, sta:11 0, prof:1
I (1812828) wifi: pm stop, total sleep time: 0/1800089915

[MQTT INFO] Read len 0
[MQTT INFO] network disconnected
I (1812953) wifi: n:11 0, o:11 0, ap:255 255, sta:11 0, prof:1
I (1812954) wifi: state: auth -> auth (b0)
I (1812956) wifi: state: auth -> assoc (0)
I (1812961) wifi: state: assoc -> run (10)
I (1812977) wifi: connected with UNICORN, channel 11
[MQTT INFO] Connecting to server <IP_ADDRESS>:1883,23303
[MQTT ERROR] Connect failed
I (1813983) event: ip: <IP_ADDRESS>, mask: <IP_ADDRESS>, gw: <IP_ADDRESS>
[MQTT INFO] Connecting to server <IP_ADDRESS>:1883,23303
[MQTT INFO] Connected!

hello... any help on this ? i am stuck here.

what is this problem?

still this error is killing my project..
Please help.
`[MQTT INFO] Read len 18
[MQTT INFO] deliver_publish
[MQTT INFO] Data received: 5/5 bytes
[APP] Publish topic: rpi2/temp
[APP] Publish data[5/5 bytes]
[APP] DATA: 43.83s
123.
f task=mqt a=0x3ffc34a4 h=1a2b3c4d t=00103332
abort() was called at PC 0x40083779 on core 0
Guru Meditation Error: Core  0 panic'ed (abort)
Backtrace: 0x40009203:0x3ffc4bf0 0x400e6df1:0x3ffc4c10 0x400833d2:0x3ffc4c30 0x400864a0:0x3ffc4c50 0x400820d4:0x3ffc4c70 0x4000beca:0x3ffc4c90 0x40111840:0x3ffc4cb0 0x401134a8:0x3ffc4cd0 0x401135b5:0x3ffc4d20 0x401136a5:0x3ffc4d40
Rebooting... `


Add scraper for Hungary

Location name

Hungary
Source URL

https://docs.google.com/spreadsheets/d/1e4VEZL1xvsALoOIq9V2SQuICeQrT5MtWfBm32ad7i8Q/edit#gid=311133316
Notes/comments

Entered daily from the official government website, which uses images.

The "megyei" sheet doesn't have all of the states (e.g. it's missing Sopron (iso2:HU-SN)), but it has many of them.  Opening a PR :-)

Opened https://github.com/covidatlas/li/pull/560, @hyperknot can you take a peek?  It gets the data ok, but doesn't seem to cover all the states.

Note from the spreadsheet maintainer:

Thank you for your request. Yes, you can reuse and scrape the data. Because we have now relatively few cases we update the dataset on a weekly base, every Monday. If the new cases would grow again, we put back the daily update. I see your comment on Github regarding Sopron. Sopron is not county and not county capital, what you need for that county is Győr-Moson-Sopron column. All the Hungarian counties we have (19), + the capital Budapest. Unfortunately we don't have detailed, more accurate data for smaller administrative units since the government does not disclose them.


[qtbase] fix feature dbus

Fixes https://github.com/microsoft/vcpkg/issues/35629

I test this PR successfully in x64-windows by vcpkg.json:
{
  "name": "1",
  "version": "1.0",
  "dependencies": [
    {
      "name": "qtbase",
      "default-features": false,
      "features": [
        "dbus"
      ]
    }
  ]
}


Cache seems to be OS version specific (at least on Windows)

I use this cache action to transport files between jobs.
I know it is also possible with artifacts, but imho they are not really suited for the task, as artifacts are things that should persist after the workflow finished and also there is no way to delete to date, so using artifacts is exposing internal workflow state which seems wrong to me.
Instead I use this cache action with ${{ github.run_id }} as cache key as this is an id uniqe to the workflow run, so the cache is used exactly within the workflow and that's it.
I was pretty successful with this tactic so far, as I build a WSL based action and thus all happens only on the windows-latest environment where WSL is available.
I have a build job that builds the action and then several test jobs that test the action, using the built files from the build job.
Now comes the quirk. I added a runtime check that WSL is available in case someone uses my action on windows-2016 environment and also made a test job for this.
Executing the action also fails, but for the wrong reason. It fails for not finding the action.yml file because the cache action had no hit.
If I add a second build action that builds on 2016 and fills a second cache bucket, then use that cache bucket on the windows 2016 test, it works.
Now the question is, why do I not have a cache hit when filling the cache on windows-2019 and restoring it on windows-2016 while the cache key is correct.
You can see the differences in these two runs, but don't get confused from all being green.
There is a continue-on-error: true as the action is expected to fail, it just fails for the wrong reason in one of the runs.
Bad run: https://github.com/Vampire/setup-wsl/runs/936481421?check_suite_focus=true
Here the Build job fills the cache with key 191698355 that is then used in all Test jobs.
In all except for the Test 'windows-2016' environment job this works fine.
In the Test 'windows-2016' environment job though, there is a cache miss for key 191698355,
the Execute action step fails wrongly with Can't find 'action.yml' and the post-part stores an empty cache entry.
Good run: https://github.com/Vampire/setup-wsl/runs/936483860?check_suite_focus=true
Here I added a second build job Build on windows-2016 that does exactly the same things as Build, just on windows-2016 and is then used by the Test 'windows-2016' environment job which properly fails with This Windows environment does not have WSL enabled as expected.
So it seems the build cache is somehow environment-specifc down to the version of the OS.
If this is really the case, this is pretty bad, there are many OS-independent things like JavaScript or Java files.
There is no reason to not reuse them between different platforms, let alone different versions.

@Vampire Yes, this is a known issue.  It's detailed in this issue, but the summary is BSD tar with zstd compression hangs on large files.  If you look at the debugging output in your logs, you'll see we print tar --version and the two Windows versions display different tar versions (GNU and BSD tar). Because BSD tar hangs, we disable zstd compression and fall back to gzip when we detect BSD tar.  However, this means the caches can't be interchanged.
I think we can replace tar --use-compression-program zstd with tar ... | zstd ... and not sacrifice too much performance, but currently we have been focusing on other priorities and likely won't be able to have a fix for a few weeks.  This is open source, however, so we do welcome contributions 😄. The relevant code is over in the actions/toolkit repo.

I see, as actions/cache#301 is still open for a fix, I'll close this one and watch over there, thanks.


Error in engaging events

When I'm trying to engage an event by using the following code:
[[Apptentive sharedConnection] engage:@"got_RSVP" fromViewController:self]; from an viewController and here are the logs printed on console:
2016-09-17 16:54:26.638 [info] Engage Apptentive event: local#app#got_RSVP
Just below this there's another log saying:
2016-09-17 16:54:26.651 [info] Interaction NUMERIC_ID predicate failed evaluation.
2016-09-17 16:54:26.653 [info] Interaction NUMERIC_ID predicate failed evaluation.
And when I look at the dashboard the event count does not increase.
Pls have a look into this issue.

The "failed evaluation" is the normal behavior when either a "Who"(segmentation) requirement isn't being met, or one of the timing settings (like the "wait N days before showing") isn't being met (although admittedly it's a poorly-worded log message).
Unfortunately we currently don't have a way to get more transparency into exactly which isn't being met.
Most commonly you'll see that message because you haven't waited long enough between installing the app and triggering the event. You can speed up the process by temporarily changing your device's (or, in the simulator, your computer's) clock forward a few days.


Support for mssql backup location

TL;DR
The underlying  Google provider allows the DB backup location to be set in settings.backup_configuration
Ref. https://registry.terraform.io/providers/hashicorp/google/4.24.0/docs/resources/sql_database_instance
The mssql submodule  does not allow the backup location to be set
Ref. https://registry.terraform.io/modules/GoogleCloudPlatform/sql-db/google/latest/submodules/mssql
When I use the mssql submodule to create a MS SQL DB, the DB is created with a default mult-region location;

This then causes a warning note in the SQL Cloud console due to an org policy constraint : "This instance's backups settings don't follow your organization policy "Resource Location Restriction".
(This is an edge case and of course I can always manually set the backup config after the DB is created or revert to the underlying Google provider instead of using this mssql module.)
Terraform Resources
No response
Detailed design
No response
Additional information
No response

I see that backup region is supported in the mysql submodule [1] but not in the mssql submodule
[1] https://github.com/terraform-google-modules/terraform-google-sql-db/blob/a83101cc2bf11f9a071ab6119576550019cf4fc8/modules/mysql/main.tf#L64


while playing video greater then 720P video have no audio does anyone now about solution?

YouTubekit is best but while playing video greater then 720P video have no audio does anyone now about solution?

Likely fixed with newest release


Make agent hostPort more docker friendly

For localhost to hit agent processor endpoints in the docker world, we need to use <IP_ADDRESS> as the host for the agent.

Coverage decreased (-0.07%) to 98.296% when pulling ebb34a4d73bfe972932429022ed5db99d4a38d53 on puertos into 7bb89a21d71da172dfee26e5b788e44dd4e2542f on master.

Changes Unknown when pulling 223a5b3b74625e7f932a3bc860d76907e8079b95 on puertos into ** on master**.

Changes Unknown when pulling 223a5b3b74625e7f932a3bc860d76907e8079b95 on puertos into ** on master**.


[Durable Objects] Add a build a rate limiter example for Durable Objects

Will come back to this once you implemented Matt's suggestions.

Will come back to this once you implemented Matt's suggestions.

@Maddy-Cloudflare would love your feedback here.


OAuth integration

It'd be nice to have GitHub's OAuth used for generating access tokens instead of requiring intervention on the user's part.
The Chrome extension documentation has an example that looks like it should be helpful in accomplishing this.

@SnoopJeDi I'll take a look at this over the weekend.

Awesome @jay-khatri! I've let this project stagnate a little, but it could definitely use some polish. Let me know here if you run into any trouble or want somebody to bounce ideas off of.

@SnoopJeDi definitely! I saw two things that I'd like to work on. One was OAuth and the other was refactoring some of structure for readability. Thoughts? Also, for publicity sake, Github doesn't provide personalized suggestions do they (I couldn't find anything other than github.com/explore)"?

Nope, that's the only available suggestion-y feature I'm aware of, and as near as I can tell it does not seem to be personalized, so GitStub is still providing a relevant feature! 😁


Add some useful constants

This PR add constants officially specified by the W3C. It prevents typo when using them.
(Borrowed from https://github.com/symfony/symfony/pull/22273)

Could we do these similar to how psr/http-message-util does, and push the constants into a separate interface? That allows developers to implement the interface in their own classes that generate links, simplifying the usage to self::REL_*.
Thanks!

Note that almost every standard will refer to this list of link relations, which is also kept up-to-date as new ones are registered:
http://www.iana.org/assignments/link-relations/link-relations.xhtml

@evert Good to know!
@dunglas With that known... You may want to look at what we did to automate validating response status reason phrases in zend-diactoros and do similarly here to ensure that they stay valid and in sync.

Closing in favor of #5.


summary-panel renders inconsistently

The summary-panel renders inconsistently, when switching between processes.  To be more specific, the panel renders on initial load, but then may not render at all when switching between processes
Description
The summary-panel (top-right, which includes the commandName, commandLine and parent/child process id's) will occasionally not render when selecting a new process, or after re-selecting a process which had been previously selected and for which the panel previously rendered.
Steps to Reproduce

In NR1, locate a host, and load the Top nerdlet.  Select a process other than the one currently selected at load, re-select the original process. The summary panel does not render.

In NR1, locate a host, and load the Top nerdlet.  Select a process other than the one currently selected at load, then select another.  After several selections, the summary panel no longer renders.  Note, navigating using the child/parent link yields the same result.

Expected Behaviour
The summary-panel should load consistently, for every process
Your Environment

Versions 0.1.5, 0.1.6
Browsers:
Chrome Version 77.0.3865.120 (Official Build) (64-bit) (Mac)
Firefox 69.0.3 (64-bit) (Mac)

@throck I can confirm that I was able to reproduce. I'll look into addressing this in the weeks ahead. Thanks for reporting it.

:tada: This issue has been resolved in version 0.4.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Typo in the description of the /e option.

In the https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/xcopy#parameters table, on the row for the /e option, the Description has an extraneous /t tagged on to the end.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 544925b9-8587-3e0e-9d49-44b77dbd290d
Version Independent ID: e9969211-1085-ca1f-afb5-b619edbbfab3
Content: xcopy
Content Source: WindowsServerDocs/administration/windows-commands/xcopy.md
Service: unspecified
GitHub Login: @coreyp-at-msft
Microsoft Alias: coreyp

Thanks for raising this issue. Did you know you can edit the file to fix the typo directly? Follow the instructions here. We're working on making the command information more useful - we'll add this typo to our list of fixes. Thanks!


Vehicle Location geojson

Before Describe the bug
Thank you for your generosity and time in making this integration  and sharing it with the community.
Describe the bug
Real time vehicle position does not appear to be called anywhere in the code base as is described in the readme.md
Option to add gtfs realtime vehicle location source/url, generates geojson file which can be used for tracking vehicle on map card
Looking at the code I can see methods for

get_rt_vehicle_positions
update_geojson

but I am unable to find any reference of this being called anywhere in the code.
Is this feature currently implemented?
Thank you

I found in  your older code you were calling get_rt_vehicle_positions from within another helper, this appears to have been removed.
I have added the following locally to test:
def get_rt_alerts(self):
if self._vehicle_position_url != "" :
    get_rt_vehicle_positions(self)

.......................
This is now generating the expected ./www/gtfs2/{route}_0.json file with appropriate contents.

I also note documentation as follows
Note: geojson currently only updates each 5 minutes and can not be refreshed by a service call

The last version had a major rework in it and code cleaning, although I did think about veh.loca ... apparently this did not make it to the release. Will add it by eow.
On geojson, this is core functinoality used for reading the geojson file(s) that gtfs2 generates and is limited to 5 mins. which I cannot change (dev. also does not respond to my request). In the meantime I learned how to create/remove entities at a higher frequency so a future implementation will allow faster updates

Collecting veh.positions is fixed with release 0.4.2.


Remove unnecessary files

Issue

These files are not needed under version control, probably.

Overview (Required)

Links

Screenshot

Before
After

Good catch! Thanks. LGTM 👍

sorry, I mistake to push without switching branch...

No problem! Will you revert the commit?

done it, thanks!

Thanks! I'll wait CI and merge.


Update<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>

:arrow_up:

Thanks for upgrading these :boat:


test

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

1 of 1 (100.0%)  changed or added relevant line in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.002%) to 88.17%

Totals

Change from base Build<PHONE_NUMBER>:
0.002%

Covered Lines:
6238

Relevant Lines:
7075

💛  - Coveralls


added signed npm delegation

Summary
Added the npm delegation, versioned bumped and signed, no other changes.
Look for:
Version: 3

Public key (PEM encoded) should be the same as in 1.registry.npmjs.json
File hash for delegated file keys.json should not have changed since previous version.
KeyType should be ecdsa in targets.json

Note the signature of registry.npm.json contains signatures with both new and old key id (key id changed as the key type was updated), I added that because during test last week, the verify command did behave strange when only the new key id was there, it only verified correctly ~1/3 so it seems that the key ids are confused internally in the tool as they refer to the same key.
Release Note
N/A
Documentation
N/A

kommendorkapten@m1m14:~/git/root-signing % git status
On branch add-npm
nothing to commit, working tree clean
kommendorkapten@m1m14:~/git/root-signing % ./verify repository --repository ./repository --staged
STAGED METADATA

Outputting metadata verification at ./repository...

Verifying root.json...
	Contains 0/3 valid signatures from the current staged metadata
	Contains 0/3 valid signatures from the previous root
	root version 9, expires 2024/09/12

Verifying targets.json...
	Contains 0/3 valid signatures from the current staged metadata
	targets version 9, expires 2024/09/12

Verifying registry.npmjs.org.json...
	Success! Signatures valid and threshold achieved
	registry.npmjs.org version 3, expires 2024/09/12


Altitude angles wrapped to wrong range

Altitude angles in this library are wrapped/limited to a range of [-180, +180] degrees. This is incorrect: altitude should have a range of [-90, +90] degrees!

I searched for code that manipulates the altitude position but did not find any instances of it being limited or wrapped to [-180, +180]. This may have been the case when backlash compensation was present but that feature has since been removed. The only problem I could find was in the docstring block for the get_position function of NexStarMount.


Updated the example to remove openshift/fabric8 aspects, so just beco…

…me a simple spring-boot app using OT JavaAgent with Hawkular APM

@jpkroehling Could you review please?
I've simplified each service by removing the openshift/fabric8 aspects, and downloading the agent so doesn't need to be done manually.
Aim is to make this a simple example of using OT JavaAgent (with spring boot) against a real Tracer (e.g. Hawkular APM) - so can be referenced from OT JavaAgent repo's README.
Currently still dependent upon some snapshots, but hopefully good enough to review against the above aim.
Once using non-snapshot versions, may see about getting it moved to the hawkular org.

@jpkrohling Thanks!


Only use packages/ subfolder from parent, and fix issue with dissappearing items

@flivni I'm not able to write into this repo - can you merge this in


Error when use multiple GPUs

Hi team,
I am working on inference with codellama/CodeLlama-7b-Instruct-hf on vllm. I am using 2 T4 GPU for this.
At the first place, I was trying with engine_args.tensor_parallel_size = 1. And it shows OOM. So after that, I tried engine_args.tensor_parallel_size = 2. But new error pop up.
FYI, when I tried with 1 A100, the result looks good as the memory is enough.
Could you help check on this? Thanks!
GPU
(base) [root@ac4da495a32a vllm]# nvidia-smi
Tue Oct 17 10:00:36 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.125.06   Driver Version: 525.125.06   CUDA Version: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |
| N/A   48C    P8    10W /  70W |      2MiB / 15360MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  Tesla T4            Off  | 00000000:00:05.0 Off |                    0 |
| N/A   41C    P8     9W /  70W |      2MiB / 15360MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

version
python==3.8.16

vllm                         0.2.0
transformers                 4.35.0.dev0
torch                        2.0.1
torchvision                  0.15.2

reproduce code
import argparse
import asyncio
from typing import Iterable, Optional, Dict
from vllm import EngineArgs, LLMEngine, RequestOutput, SamplingParams, AsyncLLMEngine, AsyncEngineArgs
from mlserver.logging import logger
import uuid

def get_engine(model_path):
    logger.info("ready to load vllm AsyncLLMEngine")

    engine_args = AsyncEngineArgs(model_path)
    # engine_args.tensor_parallel_size = 1
    engine_args.tensor_parallel_size = 2
    engine_args.dtype = 'float16'
    print(f"engine_args: {engine_args}")
    """
    AsyncEngineArgs(model='facebook/opt-13b', tokenizer='facebook/opt-13b', tokenizer_mode='auto',
                    trust_remote_code=False, download_dir=None, load_format='auto', dtype='auto', seed=0,
                    max_model_len=None, worker_use_ray=False, pipeline_parallel_size=1, tensor_parallel_size=2,
                    block_size=16, swap_space=4, gpu_memory_utilization=0.9, max_num_batched_tokens=None,
                    max_num_seqs=256, disable_log_stats=False, revision=None, quantization=None, engine_use_ray=False,
                    disable_log_requests=False, max_log_len=None)
    """
    engine = AsyncLLMEngine.from_engine_args(engine_args)

    logger.info(f"loaded vllm AsyncLLMEngine with model_path: {model_path}")
    return engine

async def generate_stream_vllm(engine,
                               tokenizer,
                               prompt,
                               temperature,
                               presence_penalty,
                               frequency_penalty,
                               max_tokens,
                               stream_interval: int = 2
                               ):
    assert stream_interval > 0, f'stream_interval assertion failed, expect > 0 but got {stream_interval}'
    logger.info("generate_stream_vllm with vllm AsyncLLMEngine")

    sampling_params = SamplingParams(
        temperature=temperature,
        presence_penalty=presence_penalty,
        # frequency_penalty=frequency_penalty,
        max_tokens=max_tokens,
    )

    logger.info(f"sampling_params: {sampling_params}")

    request_id = uuid.uuid4()

    cur_step = 0
    async for request_output in engine.generate(prompt, sampling_params, request_id):
        cur_step = cur_step + 1

        if request_output.finished or cur_step % stream_interval == 0:
            yield {
                "text": request_output.outputs[0].text,
                "usage": {
                    "prompt_tokens": len(request_output.prompt_token_ids),
                    "completion_tokens": len(request_output.outputs[0].token_ids),
                    "total_tokens": len(request_output.prompt_token_ids) + len(request_output.outputs[0].token_ids),
                },
                "finish_reason": None if not request_output.finished else "stop",
            }

async def generate_vllm(engine,
                        tokenizer,
                        prompt,
                        temperature,
                        presence_penalty,
                        frequency_penalty,
                        max_tokens,
                        ):
    logger.info("generate_vllm with vllm AsyncLLMEngine")
    result = None
    async for result in generate_stream_vllm(engine,
                                             tokenizer,
                                             prompt,
                                             temperature,
                                             presence_penalty,
                                             frequency_penalty,
                                             max_tokens,
                                             50
                                             ):
        pass
    return result

def non_streaming_main():
    # model_path = "codellama/CodeLlama-13b-Instruct-hf"
    model_path = "codellama/CodeLlama-7b-Instruct-hf"
    params = {
        "prompt": "A robot may not injure a human being",
        "temperature": 0.0,
        "repetition_penalty": 1.0,
        "max_new_tokens": 30,
    }

    engine = get_engine(model_path)
    print(asyncio.run(generate_vllm(engine,
                                    None,
                                    prompt=params["prompt"],
                                    temperature=params["temperature"],
                                    presence_penalty=params["repetition_penalty"],
                                    frequency_penalty=None,
                                    max_tokens=params["max_new_tokens"],
                                    )))

if __name__ == '__main__':
    non_streaming_main()

engine_args.tensor_parallel_size = 1
(base) [root@ac4da495a32a vllm]# python vllm_wrapper_async.py
engine_args: AsyncEngineArgs(model='codellama/CodeLlama-7b-Instruct-hf', tokenizer='codellama/CodeLlama-7b-Instruct-hf', tokenizer_mode='auto', trust_remote_code=False, download_dir=None, load_format='auto', dtype='float16', seed=0, max_model_len=None, worker_use_ray=False, pipeline_parallel_size=1, tensor_parallel_size=1, block_size=16, swap_space=4, gpu_memory_utilization=0.9, max_num_batched_tokens=None, max_num_seqs=256, disable_log_stats=False, revision=None, quantization=None, engine_use_ray=False, disable_log_requests=False, max_log_len=None)
Downloading (…)lve/main/config.json: 100%|██████████████████████████████████████████████| 646/646 [00:00<00:00, 68.4kB/s]
WARNING 10-17 09:53:40 config.py:341] Casting torch.bfloat16 to torch.float16.
INFO 10-17 09:53:40 llm_engine.py:72] Initializing an LLM engine with config: model='codellama/CodeLlama-7b-Instruct-hf', tokenizer='codellama/CodeLlama-7b-Instruct-hf', tokenizer_mode=auto, revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=16384, download_dir=None, load_format=auto, tensor_parallel_size=1, quantization=None, seed=0)
INFO 10-17 09:53:40 tokenizer.py:30] For some LLaMA V1 models, initializing the fast tokenizer may take a long time. To reduce the initialization time, consider using 'hf-internal-testing/llama-tokenizer' instead of the original tokenizer.
Downloading (…)okenizer_config.json: 100%|██████████████████████████████████████████████| 749/749 [00:00<00:00, 94.7kB/s]
Downloading tokenizer.model: 100%|████████████████████████████████████████████████████| 500k/500k [00:00<00:00, 2.33MB/s]
Downloading (…)/main/tokenizer.json: 100%|██████████████████████████████████████████| 1.84M/1.84M [00:00<00:00, 24.1MB/s]
Downloading (…)cial_tokens_map.json: 100%|███████████████████████████████████████████████| 411/411 [00:00<00:00, 218kB/s]
[W socket.cpp:426] [c10d] The server socket cannot be initialized on [::]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
[W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [localhost]:34617 (errno: 97 - Address family not supported by protocol).
Downloading (…)of-00002.safetensors: 100%|██████████████████████████████████████████| 3.50G/3.50G [01:03<00:00, 55.0MB/s]
Downloading (…)of-00002.safetensors: 100%|██████████████████████████████████████████| 9.98G/9.98G [03:00<00:00, 55.4MB/s]
Traceback (most recent call last):
  File "vllm_wrapper_async.py", line 115, in <module>
    non_streaming_main()
  File "vllm_wrapper_async.py", line 103, in non_streaming_main
    engine = get_engine(model_path)
  File "vllm_wrapper_async.py", line 25, in get_engine
    engine = AsyncLLMEngine.from_engine_args(engine_args)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 486, in from_engine_args
    engine = cls(engine_args.worker_use_ray,
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 270, in __init__
    self.engine = self._init_engine(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 306, in _init_engine
    return engine_class(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 111, in __init__
    self._init_cache()
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 191, in _init_cache
    num_blocks = self._run_workers(
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 692, in _run_workers
    output = executor(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/worker/worker.py", line 109, in profile_num_available_blocks
    self.model(
  File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/models/llama.py", line 297, in forward
    hidden_states = self.model(input_ids, positions, kv_caches,
  File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/models/llama.py", line 257, in forward
    hidden_states = layer(
  File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/models/llama.py", line 216, in forward
    hidden_states = self.mlp(hidden_states)
  File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/models/llama.py", line 81, in forward
    gate_up, _ = self.gate_up_proj(x)
  File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/parallel_utils/tensor_parallel/layers.py", line 238, in forward
    output_parallel = self.apply_weights(input_parallel, bias)
  File "/opt/conda/lib/python3.8/site-packages/vllm/model_executor/parallel_utils/tensor_parallel/layers.py", line 222, in apply_weights
    return F.linear(x, self.weight, bias)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 688.00 MiB (GPU 0; 14.58 GiB total capacity; 13.06 GiB already allocated; 678.38 MiB free; 13.09 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

engine_args.tensor_parallel_size = 2
(base) [root@ac4da495a32a vllm]# python vllm_wrapper_async.py
engine_args: AsyncEngineArgs(model='codellama/CodeLlama-7b-Instruct-hf', tokenizer='codellama/CodeLlama-7b-Instruct-hf', tokenizer_mode='auto', trust_remote_code=False, download_dir=None, load_format='auto', dtype='float16', seed=0, max_model_len=None, worker_use_ray=False, pipeline_parallel_size=1, tensor_parallel_size=2, block_size=16, swap_space=4, gpu_memory_utilization=0.9, max_num_batched_tokens=None, max_num_seqs=256, disable_log_stats=False, revision=None, quantization=None, engine_use_ray=False, disable_log_requests=False, max_log_len=None)
WARNING 10-17 09:57:35 config.py:341] Casting torch.bfloat16 to torch.float16.
2023-10-17 09:57:37,236	WARNING services.py:1889 -- WARNING: The object store is using /tmp instead of /dev/shm because /dev/shm has only 46964736 bytes available. This will harm performance! You may be able to free up space by deleting files in /dev/shm. If you are inside a Docker container, you can increase /dev/shm size by passing '--shm-size=7.67gb' to 'docker run' (or add it to the run_options list in a Ray cluster config). Make sure to set this to more than 30% of available RAM.
2023-10-17 09:57:37,378	INFO worker.py:1642 -- Started a local Ray instance.
INFO 10-17 09:57:38 llm_engine.py:72] Initializing an LLM engine with config: model='codellama/CodeLlama-7b-Instruct-hf', tokenizer='codellama/CodeLlama-7b-Instruct-hf', tokenizer_mode=auto, revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=16384, download_dir=None, load_format=auto, tensor_parallel_size=2, quantization=None, seed=0)
INFO 10-17 09:57:38 tokenizer.py:30] For some LLaMA V1 models, initializing the fast tokenizer may take a long time. To reduce the initialization time, consider using 'hf-internal-testing/llama-tokenizer' instead of the original tokenizer.
(RayWorker pid=6679) [W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [::ffff:<IP_ADDRESS>]:36763 (errno: 97 - Address family not supported by protocol).
(RayWorker pid=6678) [W socket.cpp:426] [c10d] The server socket cannot be initialized on [::]:36763 (errno: 97 - Address family not supported by protocol).
(RayWorker pid=6679) *** SIGBUS received at time=1697536689 on cpu 7 ***
(RayWorker pid=6679) PC: @     0x7f600974f18a  (unknown)  __memset_avx2_unaligned_erms
(RayWorker pid=6679)     @     0x7f60096e9df0       1536  (unknown)
(RayWorker pid=6679)     @ 0x54392d6c63636e2f  (unknown)  (unknown)
(RayWorker pid=6679) [2023-10-17 09:58:09,995 E 6679 6879] logging.cc:361: *** SIGBUS received at time=1697536689 on cpu 7 ***
(RayWorker pid=6679) [2023-10-17 09:58:09,996 E 6679 6879] logging.cc:361: PC: @     0x7f600974f18a  (unknown)  __memset_avx2_unaligned_erms
(RayWorker pid=6679) [2023-10-17 09:58:09,999 E 6679 6879] logging.cc:361:     @     0x7f60096e9df0       1536  (unknown)
(RayWorker pid=6679) [2023-10-17 09:58:10,003 E 6679 6879] logging.cc:361:     @ 0x54392d6c63636e2f  (unknown)  (unknown)
(RayWorker pid=6679) Fatal Python error: Bus error
(RayWorker pid=6679)
(RayWorker pid=6678) [W socket.cpp:601] [c10d] The client socket cannot be initialized to connect to [::ffff:<IP_ADDRESS>]:36763 (errno: 97 - Address family not supported by protocol). [repeated 3x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/ray-logging.html#log-deduplication for more options.)
2023-10-17 09:58:10,214	WARNING worker.py:2058 -- A worker died or was killed while executing a task by an unexpected system error. To troubleshoot the problem, check the logs for the dead worker. RayTask ID: ffffffffffffffff5612a023179f9dd66427c42101000000 Worker ID: 751fef21f9b691422fcf0a276b2e0cd19b3c3eb807a3dcf7eb0f240a Node ID: 52ba7341d9a6a03d304c25c56050eb18dbde025686633d9b3a2afdf2 Worker IP address: <IP_ADDRESS> Worker port: 35173 Worker PID: 6679 Worker exit type: SYSTEM_ERROR Worker exit detail: Worker unexpectedly exits with a connection error code 2. End of file. There are some potential root causes. (1) The process is killed by SIGKILL by OOM killer due to high memory usage. (2) ray stop --force is called. (3) The worker is crashed unexpectedly due to SIGSEGV or other unexpected errors.
Traceback (most recent call last):
  File "vllm_wrapper_async.py", line 115, in <module>
    non_streaming_main()
  File "vllm_wrapper_async.py", line 103, in non_streaming_main
    engine = get_engine(model_path)
  File "vllm_wrapper_async.py", line 25, in get_engine
    engine = AsyncLLMEngine.from_engine_args(engine_args)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 486, in from_engine_args
    engine = cls(engine_args.worker_use_ray,
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 270, in __init__
    self.engine = self._init_engine(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/async_llm_engine.py", line 306, in _init_engine
    return engine_class(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 111, in __init__
    self._init_cache()
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 191, in _init_cache
    num_blocks = self._run_workers(
  File "/opt/conda/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 696, in _run_workers
    all_outputs = ray.get(all_outputs)
  File "/opt/conda/lib/python3.8/site-packages/ray/_private/auto_init_hook.py", line 24, in auto_init_wrapper
    return fn(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 103, in wrapper
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/ray/_private/worker.py", line 2549, in get
    raise value
ray.exceptions.RayActorError: The actor died unexpectedly before finishing this task.
	class_name: RayWorker
	actor_id: 5612a023179f9dd66427c42101000000
	pid: 6679
	namespace: 4b5e0964-74c2-4739-bd27-961c79067b12
	ip: <IP_ADDRESS>
The actor is dead because its worker process has died. Worker exit type: SYSTEM_ERROR Worker exit detail: Worker unexpectedly exits with a connection error code 2. End of file. There are some potential root causes. (1) The process is killed by SIGKILL by OOM killer due to high memory usage. (2) ray stop --force is called. (3) The worker is crashed unexpectedly due to SIGSEGV or other unexpected errors.
(RayWorker pid=6678) *** SIGBUS received at time=1697536689 on cpu 4 ***
(RayWorker pid=6678) PC: @     0x7f3c580e518a  (unknown)  __memset_avx2_unaligned_erms
(RayWorker pid=6678)     @     0x7f3c5807fdf0       1536  (unknown)
(RayWorker pid=6678)     @ 0x43422d6c63636e2f  (unknown)  (unknown)
(RayWorker pid=6678) [2023-10-17 09:58:09,995 E 6678 6878] logging.cc:361: *** SIGBUS received at time=1697536689 on cpu 4 ***
(RayWorker pid=6678) [2023-10-17 09:58:09,996 E 6678 6878] logging.cc:361: PC: @     0x7f3c580e518a  (unknown)  __memset_avx2_unaligned_erms
(RayWorker pid=6678) [2023-10-17 09:58:09,999 E 6678 6878] logging.cc:361:     @     0x7f3c5807fdf0       1536  (unknown)
(RayWorker pid=6678) [2023-10-17 09:58:10,003 E 6678 6878] logging.cc:361:     @ 0x43422d6c63636e2f  (unknown)  (unknown)
(RayWorker pid=6678) Fatal Python error: Bus error
(RayWorker pid=6678)

Facing same issue when trying with llama 7b on single and two v100s instances

me too，the bug occur when set --tensor-parallel-size=4.

the same issue

解法：docker run --shm-size=10.24gb -d your_image_name 即可（chatgpt4 说的，实测可以，附上chatgpt4 解释 这个警告信息是来自于 Ray（一种用于分布式计算的库），它在告诉你对象存储正在使用 /tmp 目录而不是 /dev/shm 目录。这通常是由于 /dev/shm 的可用空间不足导致的。/dev/shm 是一个临时文件存储区，也被称为共享内存，通常用于高性能计算场景，因为它比普通的磁盘存储有更快的访问速度。
默认情况下，Docker 容器的 /dev/shm 分区大小可能相对较小，这可能限制了性能，尤其是在需要大量内存的应用程序中。为了解决这个问题，你可以在启动 Docker 容器时，设置更大的共享内存大小。
根据警告信息提供的建议，你可以通过以下步骤来增加 Docker 容器的 /dev/shm 大小：）

Using --ipc=host fixed the issue for me. See vLLM docs here: https://docs.vllm.ai/en/latest/serving/deploying_with_docker.html

您好，我是叶燊泳，已收到你的邮件。

FYI for anyone using podman-compose, the ipc instruction is still unsupported for whatever obscure reason, and no error is given for unknown fields in your docker-compose.yml, so watch out for this.


[FLINK-23025][upsert-kafka] Fix upsert-kafka produce duplicates when …

…enable object reuse

What is the purpose of the change
Fix upsert-kafka produce duplicates when enable object reuse.
Verifying this change

Add tests in BufferedUpsertSinkFunctionTest to verify the results  if enable object reuse.

Does this pull request potentially affect one of the following parts:

Dependencies (does it add or upgrade a dependency): (yes / no)
The public API, i.e., is any changed class annotated with @Public(Evolving): (yes / no)
The serializers: (yes / no / don't know)
The runtime per-record code paths (performance sensitive): (yes / no / don't know)
Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn/Mesos, ZooKeeper: (yes / no / don't know)
The S3 file system connector: (yes / no / don't know)

Documentation

Does this pull request introduce a new feature? (yes / no)
If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented)

@fsk119  could you also open a check-pick PR for master branch ?

cc #16257


I can not redirect Downloads directory

I wanted to redirect the download directory, so I modified the script and changed two things:

log screenshot:

I can't upload the log file, can you send me the email address? i send you an email.
However, I actually found that the download directory was redirected:

I don't know if there will be problems in the future

this is my log file:
Redirect-UserFoldersToAnotherDrive-133059482003324986.txt


Minor fixes

Coverage decreased (-0.2%) to 93.418% when pulling 867060d812b226c899d73da1befb008f5c3f6730 on Juanlu001:minor-fixes into 994f55016fb345e16c9f63887f441efc4e572752 on satellogic:master.


Spriggans

Spriggans should probably not spawn in tier 1 biomes.

They don't! We found a misconfiguration that was making them smell your fear from an extra 40 blocks away. This configuration has been corrected in WAIG. Reduced their "follow distance" modifier to 0.


Tiny box on desktop appears when I launch HomeConMenu

Hello, there is a small box on my desktop (image 1) that appears when I launch HomeConMenu, and disappears when I quit the app. Nothing happens when I click on it. When I click on my desktop, the tiny box flies upward as if it were a normal app window. Furthermore, when I move an ordinary app window (e.g., Safari) around, it bumps into the tiny box as if it were an app window (image 2). When I quit HomeConMenu, the box disappears.
I am currently running macOS 15.1.1 and HomeConMenu 4.0.4 (217). — Curious if anyone has insight into what might be going on.

Thank you for reporting.
But I can not find the small window on my Mac.
Is anyone else experiencing the same thing?

Hi, when I restarted my computer, I did not see it, even though the app was open. So, it seems that the answer to your first question may be no. But it reappeared. It appears in the vertical centre of the screen about three quarters of the way up (see screenshot 1). Force-quitting the app then restarting it removes then recalls the box (see recording).
I also tried installing it on my laptop and while the tiny black box was not there, whenever I enter Exposé, 'HomeConMenu' appears as a text string, and upon closer inspection of the screenshot, it appears that there's a circular artefact above the right edge of the text (see screenshot 2).

https://github.com/user-attachments/assets/769d5f30-eb3d-450b-9cd8-a23b96cfca36

Thank you, for your great report.
I think the bug you found is due to the architecture of my application.
I suppose this issue is not resolved unless chainging the architecture.
Please wait... sorry.
If you are interested in coding an app using the HomeKit API, please read my speculation below.
This small window is a view that is forcibly displayed by the Catalyst framework. My code tries to close it automatically, but there is a possibility that the view cannot always be closed.
I think this problem can be solved by moving the architecture from UIKit to SwiftUI. However, it will require some coding. Please wait for a while.

It's no problem, really — it's easy to ignore it as it only appears on the desktop. I just thought you should know. Hopefully, Apple eventually revises their requirements for developing with the HomeKit API.


[Addition]: A small hummingbird farm in China XiaMenShi

Hotspot b58 Addresses
11298twfr2HecaApSAvFbchUxfccho2ejUazvRGiBpzFMmAHdcqq
112R6PZMiMh9TkWqrT2U8u1Si4h7wbujqLNdFzqauN2znqJs7pri
112pmvbp4hC4N8Cm4PMp5nY1w4oo5AiX4hVr6JRv9Wx4xwiua1uK
112YgR1pM51NCABBZfgTjiLKbLzkUC1KNt46sQWQ6Vx1oC9uhCSR
112YhQimP3tnA7bjLhgurd3JmmJsqekQbUMvjmtvnTkHip8QfdGJ
11zwxaMa8ihAdxhENbf8DwqQW2z1LEwB98moNHgyq1MLA8VgmHZ
Discord Handle
No response
Reason(s)
Self witnessing
They are near the other big hummingbird farm and share the same wallet address.
Consistently witnessing only those 3 hotspots.

Sorry, we are not a hummingbird farm, mainly because we only bought this machine here, and it is all a real deployment network, we should not be blocked! How can these machines be blocked out when they are placed in everyone's office?


Link to customer not working.

Click on a customer on admin home page (under heading 'Customers'), goes to admin/customers.php but page is blank.
from error file:
PHP Fatal error:  Call to undefined function jscon_encode() in /home/somewebsite/public_html/2point4/admin/customers.php on line 279
(fixing that typo results in another error: PHP Fatal error:  Call to undefined function json_enccode() in /home/somewebsite/public_html/2point4/admin/customers.php on line 296)

Thanks the report!
Same issue is found in line 300


GridGain implementation in vector stores and chat memory

Gridgain integration into latest version of langflow
Added integration tests and improved tests related files
Added icon to Gridgain component

Hi! I'm the autofix.ci troubleshooter bot.
It looks like you correctly set up a CI job that uses the autofix.ci GitHub Action, but the autofix.ci GitHub App has not been installed for this repository. This means that autofix.ci unfortunately does not have the permissions to fix this pull request. If you are the repository owner, please install the app and then restart the CI workflow! 😃


Could not select Proxmox Virtio SCSI Disk when installing FreeBSD

Describe the bug
I could not select destination disk when installing FreeBSD. I'm using Proxmox Virtio SCSI Disk.
To Reproduce
Steps to reproduce the behavior:

Go to 'Utilities'
Double click on 'Install FreeBSD'
Click 'Continue', then click 'Continue' again
On 'Select Destination Disk' page, I see the disk but could not select it

Expected behavior
I could select the disk, then continue the installation.
Screenshots

Version (please complete the following information):

Live ISO or installed system to disk: Live ISO
FreeBSD version (System --> About this Computer): 12.2
helloSystem build (cat /.url): 0.5.0 (https://github.com/helloSystem/ISO/commit/b6811af)
Running in a virtual machine: yes

Computer (please complete the following information):

Device: Proxmox Virtual Environment 6.3.6

Additional context
In the source code (https://github.com/helloSystem/Utilities/commit/cc233a6cf7961463b26d9d117a4cc014f8a8ae35#diff-759ab4208a690e8eac9942b41d38bb463a9fbf8a62b87a5c2ce03a89344ecd85R742-R743), if geomname startswith "da", selection is disabled. If I delete those 2 lines, I can select the disk, then continue installation.

Ok, you need drivers for Virtio to work. You should set your virtual disk up as SATA or NVMe instead of SCSI

if geomname startswith "da", selection is disabled. If I delete those 2 lines, I can select the disk, then continue installation.

This was added due to https://github.com/helloSystem/ISO/issues/200. If we can solve that issue, then those two lines can be removed again.

Hi @probonopd, #200 was fixed in the latest experimental iso, but I think you forgot to remove those 2 lines. I confirm the latest iso works using Proxmox Virtio SCSI disk. After removal of those 2 lines of course.

Thank you. The next experimental ISO should have it fixed.
https://github.com/helloSystem/Utilities/commit/ae46b5417203cd7ad6bb8e79893801ca4f2633a1
Please comment here if the issue persists.


Invalid narrows make a request to the server every 5s for every new message

https://github.com/zulip/zulip/blob/f4d2d199e249f9c6437a952c201cb0d163eb9069/static/js/message_events.js#L40-L89
If the narrow is invalid, it gets back a 400; this retries every 5s indefinitely.  Additionally, since this runs on every message that comes in, the client will make an increasing number of requests over time, as long as the client has the invalid narrow opened.
We should not retry 400's, and we should have an upper limit on retries, and ideally backoff, for other requests.

This code is unmodified since 4f4e982ed1f4a15dfe7f5a16539b05db347adacb. It's possible the best thing to do is delete it.

Here's the similar code path in message_fetch.js:
            if (xhr.status === 400) {
                // Bad request: We probably specified a narrow operator
                // for a nonexistent stream or something.  We shouldn't
                // retry or display a connection error.
                //
                // FIXME: Warn the user when this has happened?
                message_scroll.hide_indicators();
                const data = {
                    messages: [],
                };
                process_result(data, opts);
                return;
            }

            // We might want to be more clever here
            $("#connection-error").addClass("show");
            setTimeout(() => {
                load_messages(opts);
            }, consts.error_retry_time);

@alexmv Would you be up for picking up this release goal?


Zend Captcha

The current implementation of this related to Recaptcha v1 which is no longer supported/available since 2018 (not sure about legacy users).
Can we pull in another project https://github.com/cgsmith/zf1-recaptcha-2 to add new support for this and also make it all php8 compatable.
Not sure if that is licence compatible.

@tsmgeek I'm not a license expert, but if you are able to port it here, I'm happy to merge :)

@tsmgeek if both are GPL3, then you are definitely able to re-use it as you like. Just mention authors.

@tsmgeek are you planning to add this any time soon, pls? If yes, I'll mark it for 1.24.0 release, thanks.

Ile get around to it soon but not sure ile get it done for that release

@tsmgeek I'll probably release 1.24 soon, as we have bunch of commits already merged.


Added a MongoDB database

Hopefully this doesn't over-complicate things too much!
For your own (already working) app you need to do the following:
heroku addons:create mongolab
heroku config

Note the MONGOLAB_URI in the config and add it to your .env file.

Ahhh, this works so well! Thank you so much for slaving through this!


Remove support for initializing and building extensions in a language besides tinygo

This is a placeholder issue which will be elaborated over the next couple days with justification to remove rust and solely support tinygo for new extensions.
"getenvoy extension push --extension-file" supports any wasm, which could have been built in rust or another language.
It is understood that rust served a purpose in developing the wasm extension feature. While we are grateful for that experience, we cannot pretend this choice hasn't come at a heavy price that costs us every day. Future revisions to this issue will enumerate the costs as well as any technical gaps we have and how they would be resolved.

The purpose of the getenvoy extension toolkit is to have a standard way to develop wasm extensions for Envoy, for many languages. While Rust costs much we should never remove it.

Will flesh out the description later, but first phase is I made a tag and tagged every change where rust was the cause or dominated the effort. There are still some issues yet to be solved and they are labeled also. https://github.com/tetratelabs/getenvoy/issues?q=label%3Arust+

Also it is understood that https://github.com/tetratelabs/envoy-wasm-rust-sdk and its dependency on a personal fork as described in #183... that the only consumer of these repos are this project. It is understood that they were over a year in the making and this can be an emotional thing to consider stopping work like that. If people feel strongly about that, they could still work on them even if this project doesn't depend on it directly anymore.

It became clear to me folks may have misunderstood the end state.

this project no longer depends on non-upstream rust sdk in any way
this project stops embedding rust builds (via extension init, run, test)
instead we introduce a pre-canned example in rust using the normal sdk and prove we can run it

@lizan before I rewrite description etc, do you feel any differently with how I've restated the change?

obviated by #200


Export the resolveLocale functions for use in the getRequestConfig no routing locale resolution

Is your feature request related to a problem? Please describe.
I am working on an internal app that does not require having the locale in the URL. Therefore I opted for the without i18n routing variant of the next-intl use. According to the documentation the locale resolution should happen in the i18n/request.ts using the getRequestConfig function.
All I want to do here is to do the same locale resolution as what the routing variant does, only skip the first route resolution. I want to check the NEXT_LOCALE cookie, read the accept-language header if it is not present and fallback to the default locale when nothing else matched. But all that logic already exists in resolveLocale. It seems unreasonable that I have to reimplement a piece of logic the library already has just to pass it back to it.
Describe the solution you'd like
Honestly the best solution would be something similar to what was proposed in #1369, where I could simply omit the detectFromUrl piece from the locale resolution chain and let the library do its work.
If for any reason you would not want to make it too complex, just exporting the getAcceptLanguageLocale and getLocaleFromCookie helper functions for use in the getRequestConfig function might be enough.
Describe alternatives you've considered
An alternative is already described in the docs:

// Provide a static locale, fetch a user setting,
// read from cookies(), headers(), etc.

Yes, it is doable, but as I wrote above, it seems awkward to have to reimplement some logic that is already there.
Thank you for considering this issue.

Hi, thanks for all the reasons to not add the export, I respect it. Let's see what the Next.js middleware improvements will be.
So I have copied the logic and implemented the logic myself and yes, it is doable and it is not as much code. But there are some drawbacks:

I had to explicitly declare negotiator and @formatjs/intl-localematcher as my project dependencies. So there is a good chance I will end up with multiple versions of those libraries after a while.
I had to explicitly hardcode the NEXT_LOCALE cookie name in the code. I know you have to do it too, because Next does not expose the cookie name either. But I don't like it.


Add objective chat codes

Codecov Report

Merging #3 into master will not change coverage.
The diff coverage is 100%.

@@          Coverage Diff          @@
##           master     #3   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files           1      1
  Lines          70     83   +13
=====================================
+ Hits           70     83   +13

Impacted Files
Coverage Δ

src/index.js
100% <100%> (ø)
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Continue to review full report at Codecov.

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10 retries?

My put example is failing with "Send request failed: The HTTP redirect request failed".
Does it really make sense to retry 10 times in this case?
Does it ever make sense to retry (10 times)?

that one shouldn't retry at all. we have a flag in the errors for what is retryable and what is not. That one needs to be fixed.
Sent from my iPhone

On Mar 3, 2017, at 5:28 AM, Olaf van der Spek<EMAIL_ADDRESS>wrote:
My put example is failing with "Send request failed: The HTTP redirect request failed".
Does it really make sense to retry 10 times in this case?
Does it ever make sense to retry (10 times)?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub, or mute the thread.

What could be causing this error?

It's hard to tell without logs, but it looks like you are using the us standard region on a bucket that isn't in us-standard (e.g. us-east-1) For example, if the bucket is in us-west-2, you need to configure your client for that region. We should, handle 304 correctly, but apparently we aren't, it is getting retried, because the SDK is thinking that it is a network timeout. I'll add a story to our backlog to fix that. In the meantime, you can avoid the issue by configuring your client with the region of your bucket.

Related question @JonathanHenson... what exactly does the current retry logic try to handle?  My understanding is that it definitely handles straight up HTTP request failures.  If there is successful HTTP communication but a service returns an error code, are you saying there are certain error codes that the SDK will automatically retry?  For example with S3, if I got an InternalError response (http://docs.aws.amazon.com/AmazonS3/latest/API/ErrorResponses.html), would the SDK automatically retry this for me or is my job as the caller to put a wrapper around the SDK to handle this?
I have intermittently seen InternalError responses from S3; I'm trying to figure out if I should code in some retry logic myself or if I should just bump up / customize the SDK's existing retry customization layer.
If the SDK does retry certain error codes automatically, does it key off of the HTTP status code or the error code in the table in the above link?  If there's a spot in the code you could point me to that does that logic, that would be helpful.
Thanks.

It's keyed off the error codes/exception headers sent by AWS.
You can find a common list of errors in:
https://github.com/aws/aws-sdk-cpp/blob/master/aws-cpp-sdk-core/source/client/CoreErrors.cpp
And S3 specific errors can be found in:
https://github.com/aws/aws-sdk-cpp/blob/master/aws-cpp-sdk-s3/source/S3Errors.cpp
Note that the last boolean parameter determines whether this error is retry-able or not.
This does not answer your original question, but if you can provide logs, we could help you further.

This still happens and is a bug.
The error (ERROR_WINHTTP_REDIRECT_FAILED) comes from WinHttp.
If you turn logging on, extract the Url being used and post the Url manually, you get a 301 response with the following content:
<?xml version="1.0" encoding="UTF-8"?>
<Error>
    PermanentRedirect
    <Message>The bucket you are attempting to access must be addressed using the specified endpoint. Please send all future requests to this endpoint.</Message>
    <Endpoint>my-bucket.s3-us-west-2.amazonaws.com</Endpoint>
    <Bucket>my-bucket</Bucket>
    <RequestId>BC57F9FA4D7C7DE5</RequestId>
    <HostId>zJ36wH04X6KDt8LxVp3TDsF67olvRyOrqUuLwDww/ZXbNQte5e44pHyPdeDZXZvq6ivwmxkWlIA=</HostId>
</Error>

However, the S3 server does not return a "Location" header, so presumably, this is why WinHttp fails.
For FollowRedirectsPolicy of DEFAULT and ALWAYS, WinHttp is instructed to follow redirects... which are guaranteed to fail with the ERROR_WINHTTP_REDIRECT_FAILED since there is no Location header for WinHttp to follow.
Furthermore, it is almost always incorrect to allow WinHttp to follow redirects as it is allowed to and does convert POST into GET after a redirect.
One can get a slightly better result by setting FollowRedirectsPolicy to NEVER.  However, the most useful information, the Endpoint information is thrown away.
I will raise separate issues on both these points.


use granite poi bundle (from 6.2) to get proper import version info

Coverage remained the same at 31.626% when pulling 0a0b4a48fdb295bda9ba4babc291b4107033d2c0 on justinedelson:issue/use-granite-poi into 9feb6ebdb086779ebbe3cc2af5d16476b635ec1f on Adobe-Consulting-Services:master.

Coverage remained the same at 31.626% when pulling 0a0b4a48fdb295bda9ba4babc291b4107033d2c0 on justinedelson:issue/use-granite-poi into 9feb6ebdb086779ebbe3cc2af5d16476b635ec1f on Adobe-Consulting-Services:master.

Coverage remained the same at 31.626% when pulling 0a0b4a48fdb295bda9ba4babc291b4107033d2c0 on justinedelson:issue/use-granite-poi into 9feb6ebdb086779ebbe3cc2af5d16476b635ec1f on Adobe-Consulting-Services:master.

Coverage remained the same at 31.626% when pulling 0a0b4a48fdb295bda9ba4babc291b4107033d2c0 on justinedelson:issue/use-granite-poi into 9feb6ebdb086779ebbe3cc2af5d16476b635ec1f on Adobe-Consulting-Services:master.

Coverage remained the same at 31.626% when pulling 0a0b4a48fdb295bda9ba4babc291b4107033d2c0 on justinedelson:issue/use-granite-poi into 9feb6ebdb086779ebbe3cc2af5d16476b635ec1f on Adobe-Consulting-Services:master.


Cakephp 3.0 Asset Compress

Hi,
Are you working on cakephp 3.0 asset compress plugin, as i am not able to use it in my cakephp 3.0 application.
Can you please suggest me on this.
Thanks,
JP

Yes. The 3.0 branch works with cake3. I've got a few deployed sites using it.


Select to Bracket for HTML tags

VSCode Version: 1.24.1

In Visual Studio this same feature works nice for HTML tags as well. That is - it selects text from opening tag to closing tag. Can we have the same in VS Code? Right now it selects either opening or closing tag, depending where the cursor is.
Steps to Reproduce:

Put cursor inside HTML opening or closing tag
Execute Select to Bracket command
Only opening or closing tag will be selected

Use the Emmet: Balance(outward) command.


refactoring code with truth value test

which is more pythonic, concise, readable and efficient
Thank you for creating a pull request!
Please note that Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.
Please double-check the following.

Read our contribution guide.

Does your code conform to our coding guidelines?
Did you write sufficient test code?
Did you write sufficient documentation?

Also, take a look at our compatibility policy.

Thanks for your contribution, but unfortunately we only merge PRs for these purposes now:

Notice: As announced, Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.

https://github.com/chainer/chainer

Thanks for your contribution, but unfortunately we only merge PRs for these purposes now:

Notice: As announced, Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.

https://github.com/chainer/chainer

Thank you!


upgraded to latest version

I'm getting a msbuild related error after upgrading to visual studio 2017:
Invalid static method invocation syntax: "[MSBuild]::IsRunningFromVisualStudio()". Method '[MSBuild]::IsRunningFromVisualStudio' not found. Static method invocation should be of the form: $([FullTypeName]::Method()), e.g. $([System.IO.Path]::Combine('a', 'b'))
Please see this thread: https://github.com/Microsoft/msbuild/issues/2775
In the thread the proposed fix is to Upgrade to Microsoft.Build to v15.5.
How is msbuild upgraded to latest version?

Ran into the same issue. Had to switch from nuget.org to https://dotnet.myget.org/feed/msbuild/package/nuget/Microsoft.Build/15.5.179 and release an emergency upgrade for our product (Xenko).
However, I would like to understand how are we supposed to handle MSBuild dependencies if it is not "forward compatible" when reading newer Visual Studio targets?

What should we assume in terms of upgrade, backward and forward compatibility for API and for Visual Studio MSBuild targets (that used new API in this case)?
Is it bad practice to embed/copy MSBuild assemblies?
Should we instead write an assembly resolver which would replicate some of the logic for locating the real MSBuild path?

Bump: Having the same forward-compat issues again: if our app is compiled against MSBuild 15.5.180, it can't load a project with latest VS. We have to upgrade it to MSBuild 15.6.82.
We get the following error: Error: The "FindDependenciesOfExternallyResolvedReferences" parameter is not supported by the "ResolveAssemblyReference" task. Verify the parameter exists on the task, and it is a settable public instance property.
We need guideline on how we are supposed to embed MSBuild to load/compile projects.

@xen2 Can you take a look at https://github.com/rainersigwald/visualstudio-docs/blob/msbuild-api/docs/msbuild/updating-an-existing-application.md? I'd love any feedback you have about it before I push it to docs.microsoft.com

@rainersigwald Thanks, exactly what I was looking for!
(we were doing something similar manually, happy to switch to an official supported solution to solve this issue)

@rainersigwald Update: seems to work fine, doc was helpful!


sidequest: init at 0.3.1

Motivation for this change
Adds SideQuest, an application store / sideloading tool for the Oculus Quest and some other VR headsets.
Things done

[ ] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[x] Assured whether relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

Also verified that loading Beat Saber songs works with my Quest (which uses a separate tool, QuestSaberPatch, that is downloaded on runtime). Have not tested other sideloading capabilities with this expression, but if uploading a new Beat Saber APK works, I see no reason why those features shouldn't.

@GrahamcOfBorg build sidequest


remove useless vendored test files

we don't run these anywhere, right?
i know the godep tool doesn't vendor test files https://github.com/tools/godep#how-to-use-godep-with-a-new-project
so i'm assuming they were added manually at some point.
[test]

godep does vendor them, we didn't add them explicitly.

[merge]

awesome, my most useful contribution to opensource. 😆


SeekableReader not available from readers over InputStream

Imported from ION-243,IONJAVA-102

Why was this closed?  There's good use cases for this, and at least some scenarios where we can support seeking.

Hello,
I'm trying to learn more about what is this issue here. I'm looking for a way to seek into a specific item inside an Ion file. In the text form, I can seek to the position and start reading there, it works fine, but I can't figure out how to do the same using the binary format. Is this issue related to some feature like this? Or is there already some way to seek and read a specific entry using the binary format?
Thanks.

@wilkerlucio Can you share more information about what you're trying to do? Are you trying to skip forward in a stream until you find the value you're looking for, or do you need to be able to seek back to a value you've seen previously? Can you share the code that you mentioned works with text Ion but not binary Ion?

Sure, I have a system in which I like to index records stored in file data formats. The idea is that when I try to look something up (for example, I want a record with ID 123, from this ID, I can have an index that tells me the record 123 is stored at offset 452315 of a given file). With the offset at hand, I like to open the file, skip to that offset and read the record that starts at that point. This works fine with text format. Here is a snippet demonstrating it:

package com.nubank.dhi.serving_layer.encoding;

import com.amazon.ion.IonReader;
import com.amazon.ion.IonType;
import com.amazon.ion.IonWriter;
import com.amazon.ion.system.IonReaderBuilder;
import com.amazon.ion.system.IonTextWriterBuilder;

import java.io.*;

public class IonSkipReadDemo {
    IonReaderBuilder readerBuilder = IonReaderBuilder.standard();
    IonTextWriterBuilder textWriterBuilder = IonTextWriterBuilder.standard();

    public static void main(String[] args) {
        try {
            IonSkipReadDemo demo = new IonSkipReadDemo();

            demo.writeFile();

            demo.readSkipping(53); // 53 is the byte offset of the record with "world 4"
        } catch (Throwable e) {
            System.out.println(e.getMessage());
        }
    }

    void writeFile() throws IOException {
        try (OutputStream out = new FileOutputStream("file-java.txt");
             IonWriter textWriter = textWriterBuilder.build(out)) {
            for (long i = 1; i < 1000; i++) {
                writeHelloWorld(textWriter, "world " + i);
            }
        }
    }

    void readSkipping(long offset) throws IOException {
        InputStream in = new FileInputStream("file-java.txt");

        in.skip(offset);

        try (IonReader reader = readerBuilder.build(in)) {
            readHelloWorld(reader);
        }
    }

    void writeHelloWorld(IonWriter writer, String value) throws IOException {
        writer.stepIn(IonType.STRUCT);  // step into a struct
        writer.setFieldName("hello");   // set the field name for the next value to be written
        writer.writeString(value);    // write the next value
        writer.stepOut();               // step out of the struct
    }

    void readHelloWorld(IonReader reader) {
        reader.next();                                // position the reader at the first value, a struct
        reader.stepIn();                              // step into the struct
        reader.next();                                // position the reader at the first value in the struct
        String fieldName = reader.getFieldName();     // retrieve the current value's field name
        String value = reader.stringValue();          // retrieve the current value's String value
        reader.stepOut();                             // step out of the struct
        System.out.println(fieldName + " " + value);  // prints "hello world"
    }
}

But I can't figure out how to do the same with the binary because it must read the header at the beginning, and I'm also not sure how it would handle the local symbol tables in this case (although, for my case, I can just used shared tables, if that helps).
Is there a way to make the same with the binary format?

Sure, I have a system in which I like to index records stored in file data formats. The idea is that when I try to look something up (for example, I want a record with ID 123, from this ID, I can have an index that tells me the record 123 is stored at offset 452315 of a given file). With the offset at hand, I like to open the file, skip to that offset and read the record that starts at that point. This works fine with text format. Here is a snippet demonstrating it:

package com.amazon-ion-encode-demo;

import com.amazon.ion.IonReader;
import com.amazon.ion.IonType;
import com.amazon.ion.IonWriter;
import com.amazon.ion.system.IonReaderBuilder;
import com.amazon.ion.system.IonTextWriterBuilder;

import java.io.*;

public class IonSkipReadDemo {
    IonReaderBuilder readerBuilder = IonReaderBuilder.standard();
    IonTextWriterBuilder textWriterBuilder = IonTextWriterBuilder.standard();

    public static void main(String[] args) {
        try {
            IonSkipReadDemo demo = new IonSkipReadDemo();

            demo.writeFile();

            demo.readSkipping(53); // 53 is the byte offset of the record with "world 4"
        } catch (Throwable e) {
            System.out.println(e.getMessage());
        }
    }

    void writeFile() throws IOException {
        try (OutputStream out = new FileOutputStream("file-java.txt");
             IonWriter textWriter = textWriterBuilder.build(out)) {
            for (long i = 1; i < 1000; i++) {
                writeHelloWorld(textWriter, "world " + i);
            }
        }
    }

    void readSkipping(long offset) throws IOException {
        InputStream in = new FileInputStream("file-java.txt");

        in.skip(offset);

        try (IonReader reader = readerBuilder.build(in)) {
            readHelloWorld(reader);
        }
    }

    void writeHelloWorld(IonWriter writer, String value) throws IOException {
        writer.stepIn(IonType.STRUCT);  // step into a struct
        writer.setFieldName("hello");   // set the field name for the next value to be written
        writer.writeString(value);    // write the next value
        writer.stepOut();               // step out of the struct
    }

    void readHelloWorld(IonReader reader) {
        reader.next();                                // position the reader at the first value, a struct
        reader.stepIn();                              // step into the struct
        reader.next();                                // position the reader at the first value in the struct
        String fieldName = reader.getFieldName();     // retrieve the current value's field name
        String value = reader.stringValue();          // retrieve the current value's String value
        reader.stepOut();                             // step out of the struct
        System.out.println(fieldName + " " + value);  // prints "hello world"
    }
}

But I can't figure out how to do the same with the binary because it must read the header at the beginning, and I'm also not sure how it would handle the local symbol tables in this case (although, for my case, I can just used shared tables, if that helps).
Is there a way to make the same with the binary format?

Thank you for the illustration. I understand what you're trying to do.
This works with text because (in general) text Ion does not require a symbol table. If you seek a text Ion InputStream to a byte position where a value begins, the text IonReader will be able to read the value because it is not missing any context. (Note: for Ion 1.0 data only. If new revisions are released, then the reader will need to know what version of the Ion format to read, typically identified by the Ion version marker. The marker $ion_1_0 is implied if missing.)
For binary Ion, you correctly identified part of the problem. Seeking past a symbol table throws away context that the binary IonReader may need in order to process the values that follow. Additionally, the binary Ion version marker (0xE0 0x01 0x00 0xEA for Ion 1.0) is always required in order for the reader to consider the data valid. Using shared symbol tables won't fix the problem because your shared symbol table imports are declared in a shared symbol table.
Therefore, rather than calling InputStream.skip directly, seeking within an Ion stream needs to be done in a way that allows the IonReader to consume any symbol tables or Ion version markers that may occur between top-level values. The SeekableReader facet was created to help with use-cases like yours, where you want to pre-process the data to build up an index of values that you can quickly seek back to later. However, currently, the SeekableReader is only supported when you provide your IonReader with a byte[], not an InputStream, hence the existence of this issue.
You can still quickly seek past binary Ion values, however; the Ion 1.0 specification optimizes for this case by requiring all values to be prefixed with their length. Skipping a value simply requires the reader to parse the value's length from its header, then seek ahead by that length. The IonReader will parse any symbol tables and version markers that may occur between the values it skips, so it will always have the context it needs to read the values the follow.
To achieve something similar to what you're attempting above using the functionality available in the library today, I recommend recording value index rather than byte position during your indexing pass. Then, create your IonReader from the start of the InputStream, and call IonReader.next() enough times to position the reader at the desired value index.
For example:
    void readSkipping(long valueIndex) throws IOException {
        try (IonReader reader = readerBuilder.build(new FileInputStream("file-java.10n"))) {
            for (int i = 0; i < valueIndex; i++) {
                reader.next();
            }
            readHelloWorld(reader);
        }
    }

This assumes you only have one index to revisit; if you have more than one, visiting them all in order using the same IonReader will be more efficient.

Hello @tgregg, thanks for the detailed response.
Yes, jumping is valid, but it's only performant up to a point. In my use case, I need low latency, and I have huge files (gbs of data in a single file), and also, the file system is a networked one. In this scenario, if I have a record close to the end of a gb sized file, and I have to keep jumping with a networked file system, it won't perform well enough for my requirements.
I'm looking forward to the SeekableReader supporting InputStream. I think that will just be what I need to make this work :)