  All rights reserved.

Various files include modifications (c) NVIDIA CORPORATION & AFFILIATES.  All rights reserved.

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

NOTE: CUDA Forward Compatibility mode ENABLED.
  Using CUDA 11.6 driver version 510.47.03 with kernel driver version 460.73.01.
  See https://docs.nvidia.com/deploy/cuda-compatibility/ for details.

I0509 02:01:17.740583 1 pinned_memory_manager.cc:240] Pinned memory pool is created at '0x7f7998000000' with size 268435456
I0509 02:01:17.750397 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 0 with size 67108864
I0509 02:01:17.750411 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 1 with size 67108864
I0509 02:01:17.750417 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 2 with size 67108864
I0509 02:01:17.750422 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 3 with size 67108864
I0509 02:01:17.750428 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 4 with size 67108864
I0509 02:01:17.750434 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 5 with size 67108864
I0509 02:01:17.750439 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 6 with size 67108864
I0509 02:01:17.750446 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 7 with size 67108864
I0509 02:01:18.869713 1 model_repository_manager.cc:997] loading: meb:1
I0509 02:01:18.999772 1 hugectr.cc:1597] TRITONBACKEND_Initialize: hugectr
I0509 02:01:18.999796 1 hugectr.cc:1604] Triton TRITONBACKEND API version: 1.8
I0509 02:01:18.999803 1 hugectr.cc:1608] 'hugectr' TRITONBACKEND API version: 1.8
I0509 02:01:18.999810 1 hugectr.cc:1631] The HugeCTR backend Repository location: /usr/local/hugectr/backends/hugectr
I0509 02:01:18.999816 1 hugectr.cc:1640] The HugeCTR backend configuration: {"cmdline":{"ps":"/models/meb/ps.json"}}
I0509 02:01:18.999842 1 hugectr.cc:344] *****Parsing Parameter Server Configuration from /models/meb/ps.json
I0509 02:01:18.999897 1 hugectr.cc:365] Support 64-bit keys = 1
I0509 02:01:18.999912 1 hugectr.cc:376] Volatile database -> type = parallel_hash_map
I0509 02:01:18.999918 1 hugectr.cc:381] Volatile database -> address = <IP_ADDRESS>:7000
I0509 02:01:18.999924 1 hugectr.cc:386] Volatile database -> user name = default
I0509 02:01:18.999932 1 hugectr.cc:390] Volatile database -> password = <empty>
I0509 02:01:18.999938 1 hugectr.cc:397] Volatile database -> algorithm = phm
I0509 02:01:18.999945 1 hugectr.cc:402] Volatile database -> number of partitions = 16
I0509 02:01:18.999951 1 hugectr.cc:408] Volatile database -> max. batch size (GET) = 100000
I0509 02:01:18.999958 1 hugectr.cc:415] Volatile database -> max. batch size (SET) = 100000
I0509 02:01:18.999964 1 hugectr.cc:423] Volatile database -> refresh time after fetch = 0
I0509 02:01:18.999972 1 hugectr.cc:430] Volatile database -> overflow margin = 120000000
I0509 02:01:18.999979 1 hugectr.cc:436] Volatile database -> overflow policy = evict_oldest
I0509 02:01:18.999999 1 hugectr.cc:442] Volatile database -> overflow resolution target = 0.8
I0509 02:01:19.000007 1 hugectr.cc:450] Volatile database -> initial cache rate = 1
I0509 02:01:19.000014 1 hugectr.cc:456] Volatile database -> cache missed embeddings = 0
I0509 02:01:19.000021 1 hugectr.cc:466] Volatile database -> update filters = []
I0509 02:01:19.000060 1 hugectr.cc:583] Model name = meb
I0509 02:01:19.000067 1 hugectr.cc:592] Model 'meb' -> network file = /models/meb/1/meb.json
I0509 02:01:19.000074 1 hugectr.cc:599] Model 'meb' -> max. batch size = 100
I0509 02:01:19.000081 1 hugectr.cc:605] Model 'meb' -> dense model file = /models/meb/1/meb_dense_0.model
I0509 02:01:19.000089 1 hugectr.cc:611] Model 'meb' -> sparse model files = [/models/meb/1/meb0_sparse_0.model]
I0509 02:01:19.000097 1 hugectr.cc:622] Model 'meb' -> use GPU embedding cache = 1                                                                                [406/538]
I0509 02:01:19.000106 1 hugectr.cc:631] Model 'meb' -> hit rate threshold = 0.8
I0509 02:01:19.000115 1 hugectr.cc:639] Model 'meb' -> per model GPU cache = 1
I0509 02:01:19.000132 1 hugectr.cc:655] Model 'meb' -> num. pool worker buffers = 4
I0509 02:01:19.000142 1 hugectr.cc:662] Model 'meb' -> num. pool refresh buffers = 1
I0509 02:01:19.000149 1 hugectr.cc:669] Model 'meb' -> cache refresh rate per iteration = 0.2
I0509 02:01:19.000158 1 hugectr.cc:678] Model 'meb' -> deployed device list = [0, 1, 2, 3, 4, 5, 6, 7]
I0509 02:01:19.000167 1 hugectr.cc:686] Model 'meb' -> default value for each table = [0]
I0509 02:01:19.000179 1 hugectr.cc:706] *****The HugeCTR Backend Parameter Server is creating... *****
I0509 02:01:19.000351 1 hugectr.cc:714] ***** Parameter Server(Int64) is creating... *****
I0509 02:03:04.076790 1 hugectr.cc:725] *****The HugeCTR Backend Backend created the Parameter Server successfully! *****
I0509 02:03:04.076884 1 hugectr.cc:1703] TRITONBACKEND_ModelInitialize: meb (version 1)
I0509 02:03:04.076891 1 hugectr.cc:1716] Repository location: /models/meb
I0509 02:03:04.076899 1 hugectr.cc:1731] backend configuration in mode: {"cmdline":{"ps":"/models/meb/ps.json"}}
I0509 02:03:04.078340 1 hugectr.cc:974] Verifying model configuration: {
    "name": "meb",
    "platform": "",
    "backend": "hugectr",
    "version_policy": {
        "latest": {
            "num_versions": 1
        }
    },
    "max_batch_size": 100,
    "input": [
        {
            "name": "DES",
            "data_type": "TYPE_FP32",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        },
        {
            "name": "CATCOLUMN",
            "data_type": "TYPE_INT64",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        },
        {
            "name": "ROWINDEX",
            "data_type": "TYPE_INT32",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        }
    ],
    "output": [
        {
            "name": "OUTPUT0",
            "data_type": "TYPE_FP32",
            "dims": [
                -1
            ],
            "label_filename": "",
            "is_shape_tensor": false
        }
    ],
    "batch_input": [],
    "batch_output": [],
    "optimization": {
        "priority": "PRIORITY_DEFAULT",
        "input_pinned_memory": {
            "enable": true
        },
        "output_pinned_memory": {
            "enable": true
        },
        "gather_kernel_buffer_threshold": 0,
        "eager_batching": false
    },
    "instance_group": [
        {
            "name": "meb_0",
            "kind": "KIND_GPU",
            "count": 4,
            "gpus": [
                0,
                1,
                2,
                3,
                4,
                5,
                6,
                7
            ],
            "secondary_devices": [],
            "profile": [],
            "passive": false,
            "host_policy": ""
        }
    ],
    "default_model_filename": "",
    "cc_model_filenames": {},
    "metric_tags": {},
    "parameters": {
        "max_nnz": {
            "string_value": "8000"
        },
        "embedding_vector_size": {
            "string_value": "15"
        },
        "gpucacheper": {
            "string_value": "1.0"
        },
        "des_feature_num": {
            "string_value": "0"
        },
        "hit_rate_threshold": {
            "string_value": "0.8"
        },
        "gpucache": {
            "string_value": "true"
        },
        "embeddingkey_long_type": {
            "string_value": "true"
        },
        "slots": {
            "string_value": "15"
        },
        "config": {
            "string_value": "/models/meb/1/meb.json"
        },
        "cat_feature_num": {
            "string_value": "8000"
        },
        "label_dim": {
            "string_value": "1"
        }
    },
    "model_warmup": []
}
I0509 02:03:04.078466 1 hugectr.cc:1060] The model configuration: {
    "name": "meb",
    "platform": "",
    "backend": "hugectr",
    "version_policy": {
        "latest": {
            "num_versions": 1
        }
    },
    "max_batch_size": 100,
    "input": [
        {
            "name": "DES",
            "data_type": "TYPE_FP32",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        },
        {
            "name": "CATCOLUMN",
            "data_type": "TYPE_INT64",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        },
        {
            "name": "ROWINDEX",
            "data_type": "TYPE_INT32",
            "format": "FORMAT_NONE",
            "dims": [
                -1
            ],
            "is_shape_tensor": false,
            "allow_ragged_batch": false,
            "optional": false
        }
    ],
    "output": [
        {
            "name": "OUTPUT0",
            "data_type": "TYPE_FP32",
            "dims": [
                -1
            ],
            "label_filename": "",
            "is_shape_tensor": false
        }
    ],
    "batch_input": [],
    "batch_output": [],
    "optimization": {
        "priority": "PRIORITY_DEFAULT",
        "input_pinned_memory": {
            "enable": true
        },
        "output_pinned_memory": {
            "enable": true
        },
        "gather_kernel_buffer_threshold": 0,
        "eager_batching": false
    },
    "instance_group": [
        {
            "name": "meb_0",
            "kind": "KIND_GPU",
            "count": 4,
            "gpus": [
                0,
                1,
                2,
                3,
                4,
                5,
                6,
                7
            ],
            "secondary_devices": [],
            "profile": [],
            "passive": false,
            "host_policy": ""
        }
    ],
    "default_model_filename": "",
    "cc_model_filenames": {},
    "metric_tags": {},
    "parameters": {
        "max_nnz": {
            "string_value": "8000"
        },
        "embedding_vector_size": {
            "string_value": "15"
        },
        "gpucacheper": {
            "string_value": "1.0"
        },
        "des_feature_num": {
            "string_value": "0"
        },
        "hit_rate_threshold": {
            "string_value": "0.8"
        },
        "gpucache": {
            "string_value": "true"
        },
        "embeddingkey_long_type": {
            "string_value": "true"
        },
        "slots": {
            "string_value": "15"
        },
        "config": {
            "string_value": "/models/meb/1/meb.json"
        },
        "cat_feature_num": {
            "string_value": "8000"
        },
        "label_dim": {
            "string_value": "1"
        }
    },
    "model_warmup": []
}
I0509 02:03:04.078548 1 hugectr.cc:1105] slots set = 15
I0509 02:03:04.078555 1 hugectr.cc:1111] desene number = 0
I0509 02:03:04.078562 1 hugectr.cc:1117] cat_feature number = 8000
I0509 02:03:04.078569 1 hugectr.cc:1129] embedding size = 15
I0509 02:03:04.078576 1 hugectr.cc:1135] maxnnz = 8000
I0509 02:03:04.078583 1 hugectr.cc:1153] HugeCTR model config path = /models/meb/1/meb.json
I0509 02:03:04.078593 1 hugectr.cc:1176] support gpu cache = 1
I0509 02:03:04.078610 1 hugectr.cc:1199] gpu cache per = 1
I0509 02:03:04.078619 1 hugectr.cc:1216] hit-rate threshold = 0.8
I0509 02:03:04.078626 1 hugectr.cc:1232] Label dim = 1
I0509 02:03:04.078633 1 hugectr.cc:1238] support 64-bit embedding key = 1
I0509 02:03:04.078639 1 hugectr.cc:1252] Model_Inference_Para.max_batchsize: 100
I0509 02:03:04.078645 1 hugectr.cc:1256] max_batch_size in model config.pbtxt is 100
I0509 02:03:04.078654 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 0
I0509 02:03:04.078661 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 1
I0509 02:03:04.078667 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 2
I0509 02:03:04.078673 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 3
I0509 02:03:04.078680 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 4
I0509 02:03:04.078686 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 5
I0509 02:03:04.078693 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 6
I0509 02:03:04.078699 1 hugectr.cc:1326] ******Creating Embedding Cache for model meb in device 7
I0509 02:03:04.078705 1 hugectr.cc:1353] ******Creating Embedding Cache for model meb successfully
I0509 02:03:04.084639 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 0)
I0509 02:03:04.084655 1 hugectr.cc:1495] Triton Model Instance Initialization on device 0
I0509 02:03:04.092570 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:04.092584 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:04.119280 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:04.119445 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:04.119527 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:04.119535 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:06.406007 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:06.406216 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 1)
I0509 02:03:06.406245 1 hugectr.cc:1495] Triton Model Instance Initialization on device 1
I0509 02:03:06.406305 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:06.406313 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:06.423536 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:06.423681 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:06.423781 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:06.423789 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:07.636730 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:07.636912 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 2)
I0509 02:03:07.636927 1 hugectr.cc:1495] Triton Model Instance Initialization on device 2
I0509 02:03:07.636933 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:07.636941 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:07.653589 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:07.653740 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:07.653842 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:07.653850 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:08.864003 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:08.864193 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 3)
I0509 02:03:08.864208 1 hugectr.cc:1495] Triton Model Instance Initialization on device 3
I0509 02:03:08.864215 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:08.864239 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:08.881026 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:08.881182 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:08.881300 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:08.881309 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:10.089367 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:10.089537 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 4)
I0509 02:03:10.089549 1 hugectr.cc:1495] Triton Model Instance Initialization on device 4
I0509 02:03:10.089556 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:10.089563 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:10.106748 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:10.106901 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:10.107012 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:10.107020 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:11.315555 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:11.315748 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 5)
I0509 02:03:11.315763 1 hugectr.cc:1495] Triton Model Instance Initialization on device 5
I0509 02:03:11.315770 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:11.315776 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:11.333771 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:11.333941 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:11.334056 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:11.334065 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:12.548906 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:12.549089 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 6)
I0509 02:03:12.549103 1 hugectr.cc:1495] Triton Model Instance Initialization on device 6
I0509 02:03:12.549110 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:12.549116 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:12.566637 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:12.566807 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:12.566930 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:12.566939 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:13.789554 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:13.789746 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_0 (device 7)
I0509 02:03:13.789761 1 hugectr.cc:1495] Triton Model Instance Initialization on device 7
I0509 02:03:13.789768 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:13.789775 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:13.807076 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:13.807262 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:13.807390 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:13.807399 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:15.054373 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:15.054532 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 0)
I0509 02:03:15.054545 1 hugectr.cc:1495] Triton Model Instance Initialization on device 0
I0509 02:03:15.054551 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:15.054558 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:15.059515 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:15.059646 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:15.059775 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:15.059784 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:15.435527 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:15.435710 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 1)
I0509 02:03:15.435724 1 hugectr.cc:1495] Triton Model Instance Initialization on device 1
I0509 02:03:15.435733 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:15.435742 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:15.440908 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:15.441018 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:15.441116 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:15.441124 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:15.809277 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:15.809436 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 2)
I0509 02:03:15.809449 1 hugectr.cc:1495] Triton Model Instance Initialization on device 2
I0509 02:03:15.809455 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:15.809462 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:15.814312 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:15.814412 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:15.814511 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:15.814519 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:16.182679 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:16.182843 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 3)
I0509 02:03:16.182857 1 hugectr.cc:1495] Triton Model Instance Initialization on device 3
I0509 02:03:16.182863 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:16.182870 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:16.188940 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:16.189040 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:16.189140 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:16.189148 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:16.567086 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:16.567323 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 4)
I0509 02:03:16.567338 1 hugectr.cc:1495] Triton Model Instance Initialization on device 4
I0509 02:03:16.567344 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:16.567350 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:16.572950 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:16.573061 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:16.573169 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:16.573177 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:16.954819 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:16.954976 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 5)
I0509 02:03:16.954989 1 hugectr.cc:1495] Triton Model Instance Initialization on device 5
I0509 02:03:16.954996 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:16.955001 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:16.960033 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:16.960144 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:16.960262 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:16.960270 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:17.335444 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:17.335611 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 6)
I0509 02:03:17.335624 1 hugectr.cc:1495] Triton Model Instance Initialization on device 6
I0509 02:03:17.335631 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:17.335637 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:17.340769 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:17.340877 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:17.340976 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:17.340983 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
I0509 02:03:17.725151 1 hugectr.cc:1565] ******Loading HugeCTR model successfully
I0509 02:03:17.725387 1 hugectr.cc:1851] TRITONBACKEND_ModelInstanceInitialize: meb_0_1 (device 7)
I0509 02:03:17.725400 1 hugectr.cc:1495] Triton Model Instance Initialization on device 7
I0509 02:03:17.725407 1 hugectr.cc:1505] Dense Feature buffer allocation:
I0509 02:03:17.725412 1 hugectr.cc:1512] Categorical Feature buffer allocation:
I0509 02:03:17.730393 1 hugectr.cc:1530] Categorical Row Index buffer allocation:
I0509 02:03:17.730501 1 hugectr.cc:1540] Predict result buffer allocation:
I0509 02:03:17.730597 1 hugectr.cc:1864] ******Loading HugeCTR Model******
I0509 02:03:17.730606 1 hugectr.cc:1558] The model origin json configuration file path is: /models/meb/1/meb.json
[qgpuvb813-cvision:1    :0:381] Caught signal 7 (Bus error: nonexistent physical address)
==== backtrace (tid:    381) ====
 0 0x00000000000143c0 __funlockfile()  ???:0
 1 0x000000000018ba51 __nss_database_lookup()  ???:0
 2 0x0000000000068d6c ncclGroupEnd()  ???:0
 3 0x000000000005de2d ncclGroupEnd()  ???:0
 4 0x0000000000008609 start_thread()  ???:0
 5 0x000000000011f163 clone()  ???:0
=================================

It seems that the following options were added when running the docker container from merline-inference:22.04
--shm-size=1g --ulimit memlock=-1


hp.14-df0023: init

Description of changes
Add new hardware configuration for the HP Notebook 14-df0023, my main machine.
Hardware spec: https://support.hp.com/us-en/document/c06166782
Things done

[x] Tested the changes in your own NixOS Configuration
[x] Tested the changes end-to-end by using your fork of nixos-hardware and
importing it via <nixos-hardware> or Flake input

bors merge


Slow shutter sound

I'm having an weird issue with the shutter sound when taking a picture. Sometimes the shutter make like a pause at middle and then finish the sound, sometimes the pause is shorter, but it never is as fast as the native camera shutter sound. Thanks in advance.

@sherm4n90 sounds like something is a blocking the thread. A debug tip is to pause the application in the middle of the capturing and inspect the threads.

@MMasterson Thks, I will take a look and let you know.

Thank you :)
Thanks & Best Regards,
Le Tai
Mobile Software Engineer
Mobile: +84 90 360 91 21
Email<EMAIL_ADDRESS>Skype: sirlevantai

On Mar 23, 2016, at 12:59 AM, germ4n<EMAIL_ADDRESS>wrote:
@MMasterson https://github.com/MMasterson Thks, I will take a look and let you know.
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@MMasterson Solved! was the [recorder stopRunning] in the viewWillDisappear method. Thanks


Video Recording Problems on Flutter CameraX Package

Steps to reproduce
1- We start the video recording with the startVideoRecording() method.
2- After shooting what we want to shoot during the video, we end the video recording with the stopVideoRecording() method.
Expected results
Video recording without any problems
Actual results
A few seconds after you start shooting a video in the camera_android_camerax package, the video preview becomes distorted and changes to horizontal. The quality drops a lot. Video is not recorded after using the recording stopvideorecording method. When we try to access it via the file path, we get an error saying "There is no such file, there is no video type file in the relevant path."
Tests performed:

The same problem occurs when we run the example sample included in the flutter camera_android_camerax package.

Code sample
Code sample

// RUN THIS METHOD FOR START AND STOP VIDEO RECORD
void _videoRecordingChanger() async {
    if(isVideoRecording) {
      _stopVideoRecording();
    } else {
      _startVideoRecording();
    }
  }

void _startVideoRecording() async {

    if(!Platform.isAndroid){
      await _cameraController?.prepareForVideoRecording();
    }
    await _cameraController?.startVideoRecording();
    setState(() {
      isVideoRecording = true;
    });

  }

void _stopVideoRecording() async {

    XFile videoFile = await _cameraController!.stopVideoRecording();
    setState(() {
      isVideoRecording = false;
    });

    var realFilePath = '/VIDEO_${DateTime.now().millisecondsSinceEpoch}_${generateNumber()}.mp4';

    await videoFile.saveTo(realFilePath);

  }

Screenshots or Video

Screenshots / Video demonstration
[Upload media here]

Logs
Logs
[Paste your logs here]

Flutter Doctor output
Doctor output
[✓] Flutter (Channel stable, 3.13.2, on macOS 13.5.1 22G90 darwin-arm64, locale tr-TR)
    • Flutter version 3.13.2 on channel stable at /Users/simeray/development/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision ff5b5b5fa6 (4 months ago), 2023-08-24 08:12:28 -0500
    • Engine revision b20183e040
    • Dart version 3.1.0
    • DevTools version 2.25.0

[✓] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
    • Android SDK at /Users/simeray/Library/Android/sdk
    • Platform android-34, build-tools 34.0.0
    • ANDROID_HOME = /Users/simeray/Library/Android/sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jbr/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 17.0.6+0-17.0.6b829.9-10027231)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 15.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Build 15C65
    • CocoaPods version 1.12.1

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 2022.3)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 17.0.6+0-17.0.6b829.9-10027231)

[✓] VS Code (version 1.85.0)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.78.0

[✓] Connected device (2 available)
    • macOS (desktop) • macos  • darwin-arm64   • macOS 13.5.1 22G90 darwin-arm64
    • Chrome (web)    • chrome • web-javascript • Google Chrome 120.0.6099.109
    ! Error: Browsing on the local area network for Sinem iPhone’u. Ensure the device is unlocked and attached with a cable or associated with the same local area network as this Mac.
      The device must be opted into Developer Mode to connect wirelessly. (code -27)

[✓] Network resources
    • All expected network resources are available.

• No issues found!

Closing this as a duplicate of https://github.com/flutter/flutter/issues/137366.
Kindly subscribe to the original issue for updates.
Thank you


How to INCLUDE the package files in TFS

What if I actually WANT to include the package files in my TFS folders?  I realize I can just add the packages folder to TFS, but will it automatically include new and updated packages?

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

ID: d965aea9-a6cc-06da-a347-6e8c89458c98
Version Independent ID: 6775f211-f4b6-6d0c-6f2e-6664b3e9721e
Content: NuGet Packages and Source Control
Content Source: docs/consume-packages/Packages-and-Source-Control.md
Product: nuget
GitHub Login: @karann-msft
Microsoft Alias: karann

just like any source control, any changes you make locally and checkin will be included in your TFS repo. If you restore the latest packages locally and then perform a checkin, then yes it will be included.

Closing the issue as resolved.


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Update machine-learning-recommendation-api-sample-application.md

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Fallbacks to exclude default locale

Fixes https://github.com/svenfuchs/i18n/issues/338 ?
I believe using the default locale as a default fallback is not a sane default behaviour.
"Silently" displaying an default locale version of a string when a page is being rendered in another can have a negative impact (especially if this is not fixable like in the cases where emails are being sent).
For us to disable that behaviour, we had to pass in an explicit nil, but I believe it should be the default behaviour:
I18n::Locale::Fallbacks.new([nil])
or
Rails.application.config.i18n.fallbacks = [nil]

This only work because of a undocumented compact down in the internals of the class.
I am not saying that I would always prefer to have a "translation missing" error instead of displaying the default locale, but not having the default allows the rest of the i18n stack to handle exceptions as normal, send it to the exception handler where I can transform that missing translation to the specificities of my application.
Eg.: in my current case we have an exception handler that logs on missing translation, send a developer actionable item then manually fall back to I18n.t(key, options.merge(locale: :en), all within the I18n.exception_handler#call

I have a sneaking suspicion this might also fix #413. That would be nice :)

v1.1.0 has broken broken our application, due to this change. We built all relying on its default behavior, and changing it is a major compatibility issue that I see no reason to add, but if it should be added, at the very least it should be done properly: name the version 2.0 instead of 1.1, and release a previous version triggering warnings when the default behavior is being used...
But well... we always can stick to 1.0.1 (which we will do).

Please provide steps to reproduce this issue so that I can investigate.
On 9 Aug 2018, 03:38 +1000, Fernando Calatayud<EMAIL_ADDRESS>wrote:

v1.1.0 has broken broken our application, due to this change. We built all relying on its default behavior, and changing it is a major compatibility issue that I see no reason to add, but if it should be added, at the very least it should be done properly: name the version 2.0 instead of 1.1, and release a previous version triggering warnings when the default behavior is being used...
But well... we always can stick to 1.0.1 (which we will do).
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@Fernan2 if you relied on this behavior all you have to do now is declare it explicitly if I'm right, something like:
# config/application.rb
module XXXXX
  class Application < Rails::Application
    ...
    config.i18n.fallbacks = [:en]
  end
end

Ok, it seems that I had a weird configuration that has been the cause of all... after @jarthod 's comment, I've gone to my application.rb and I've found that I had
    config.i18n.default_locale = :es
    config.i18n.fallbacks = [:es]

But (fortunately!) I also noticed that I had a different configuration in development.rb and production.rb:
config.i18n.fallbacks = true

That worked fine on 1.0.1, but not on 1.1.0... with the problem that I had overriden development and production but no test, so tests were all passing.
Now I've removed my environment overrides and it works fine... thanks a lot!

I've had exactly the same problem, and after I found the code change in i18n I checked my application.rb and saw that this syntax can't work, I removed the fallback = true line all is back to normal. I'm not sure where this line came from but I guess it was in some tutorial or documentation.

As my application comes from Rails 1.2, I guess that this was the proper configuration many years ago...

Haha, mine is from Rails 3 so maybe not that old ;)

I had:
I18n::Backend::Simple.send(:include, I18n::Backend::Fallbacks)
I18n.enforce_available_locales = false

And things like:
I18n.l product.updated_at, :format => :long, :locale => "un-supported"

Worked great! Used default locale's :long.
Then I upgraded to said version, and I cannot get this behavior back.
I18n::Backend::Simple.send :include, I18n::Backend::Fallbacks
I18n.enforce_available_locales = false
I18n.fallbacks = [I18n.default_locale]

Gives:
Traceback (most recent call last):
       14: from ./bin/rails:4:in `<main>'
       13: from ./bin/rails:4:in `require'
       12: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/railties-<IP_ADDRESS>/lib/rails/commands.rb:18:in `<top (required)>'
       11: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/railties-<IP_ADDRESS>/lib/rails/commands/commands_tasks.rb:49:in `run_command!'
       10: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/railties-<IP_ADDRESS>/lib/rails/commands/commands_tasks.rb:78:in `console'
        9: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/railties-<IP_ADDRESS>/lib/rails/commands/console_helper.rb:9:in `start'
        8: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/railties-<IP_ADDRESS>/lib/rails/commands/console.rb:65:in `start'
        7: from (irb):1
        6: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n.rb:274:in `localize'
        5: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n/backend/base.rb:83:in `localize'
        4: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n.rb:181:in `translate'
        3: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n.rb:181:in `catch'
        2: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n.rb:185:in `block in translate'
        1: from /Users/sshaw/.rvm/gems/ruby-2.5.2/gems/i18n-1.1.0/lib/i18n/backend/fallbacks.rb:45:in `translate'
TypeError (no implicit conversion of String into Integer)

I18n.enforce_available_locales = false
I18n.fallbacks = [I18n.default_locale]

Along with other seemingly correct config permutations give:
I18n::MissingTranslationData (translation missing: XX.time.formats.long)

Back to 1.0.1! 🔒

@sshaw Could you please open a new issue so that we can track this separately from this merged PR?

Actually I just found the option to DIY! One moment...


map not loading in modal

i want to add map to get location from the user using modal. but map not loading. please tell me solution fast please.

Have any details, like what map library you're using?
Any links to a website that exhibits this behavior?

using google map api "http://maps.googleapis.com/maps/api/js?libraries=places" and using div #map-canvas to bind map view.

My guess is that you have to fire a map.resize() event every time you open a modal

can you give some sample coding?

The map is maybe not able to calculate the height when the modal is display: none. Just call map.resize() after the modal is shown.

no success dude. i did whatever i have to do. but no success.  :(

You just need to do what is described here.
http://stackoverflow.com/questions/10197128/google-maps-api-v3-not-rendering-competely-on-tabbed-page-using-twitters-bootst
On Sun, Mar 13, 2016 at 10:30 PM, Mohamed Nasrullah <
<EMAIL_ADDRESS>wrote:

no success dude. i did whatever i have to do. but no success. :(
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https://github.com/Dogfalo/materialize/issues/2854#issuecomment-196150730
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Dude i found the issue that when is map loading in modal. Actually if the page contains map and if we open a modal with map div in it means, the map in modal is not displaying untill we resize the window. If we resize the window means map is displaying in modal. How to fix this???


Demo 13 and other code containing a jump table produces a Segmentation Fault when being lifted and recompiled.

Recompiled code that uses a jump table has stopped working after the recent changes on how calls into and out of mcsema-lifted code are handled.
This can be easily reproduced by running Demo 13, which simply results in a segmentation fault. GDB shows that eip is 0 at the time of the segfault.

This should be fixed -- please reopen if its not. The switches example runs on x86 and amd64 linux in the new integration tests.


nk3: SPSDKConnectionError during nitropy nk3 update (with udev rules in place!)

I'm on an up-to-date Debian testing on Linux x86_64 with kernel
Linux host01 6.11.10-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.11.10-1 (2024-11-23) x86_64 GNU/Linux

nitropy should be up-to-date as well:
[~]$ nitropy version
Command line tool to interact with Nitrokey devices 0.7.0
0.7.0

I have package libnitrokey3 installed (the i prefix in the aptitude output), the udev rules are in place, and should be active through reboot:
[~]$ aptitude search libnitrokey
i A libnitrokey-common              - architecture independent files for libnitr
p   libnitrokey-dev                 - library to communicate with Nitrokey stick
i   libnitrokey3                    - library to communicate with Nitrokey stick
[~]$ ls -al /usr/lib/udev/rules.d/41-nitrokey.rules
-rw-r--r-- 1 root root 2852 Apr 27  2022 /usr/lib/udev/rules.d/41-nitrokey.rules
[~]$ grep 42dd /usr/lib/udev/rules.d/41-nitrokey.rules
KERNEL=="hidraw*", SUBSYSTEM=="hidraw", ATTRS{idVendor}=="20a0", ATTRS{idProduct}=="42dd", TAG+="uaccess"

Finally, I have Nitrokey 3A NFC:
[~]$ nitropy nk3 list
Command line tool to interact with Nitrokey devices 0.7.0
:: 'NK3' keys
/dev/hidraw8: Nitrokey 3 8XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXF

Here is what happens in the journal when I plug the device:
[ 1157.164379] host01 kernel: usb 3-3: new full-speed USB device number 15 using xhci_hcd
[ 1157.316164] host01 kernel: usb 3-3: New USB device found, idVendor=20a0, idProduct=42b2, bcdDevice= 1.06
[ 1157.322100] host01 kernel: usb 3-3: New USB device strings: Mfr=1, Product=2, SerialNumber=0
[ 1157.322341] host01 kernel: usb 3-3: Product: Nitrokey 3
[ 1157.322509] host01 kernel: usb 3-3: Manufacturer: Nitrokey
[ 1157.322672] host01 kernel: hid-generic 0003:20A0:42B2.0012: hiddev3,hidraw8: USB HID v1.11 Device [Nitrokey Nitrokey 3] on usb-0000:00:14.0-3/input1
[ 1157.322972] host01 kernel: cdc_acm 3-3:1.2: ttyACM0: USB ACM device
[ 1157.327525] host01 systemd[1698]: Reached target smartcard.target - Smart Card.
[ 1157.327550] host01 systemd[1]: Reached target smartcard.target - Smart Card.
[ 1165.008208] host01 kernel: usb usb2-port2: attempt power cycle
[ 1173.500152] host01 kernel: usb usb2-port2: unable to enumerate USB device

(Not sure whether the messages related to usb2-port2 are relevant here.)
After a nitropy nk3 reboot --bootloader plus a button press I get in the journal:
[ 1203.840171] host01 kernel: usb 3-3: USB disconnect, device number 15
[ 1204.220363] host01 kernel: usb 3-3: new high-speed USB device number 16 using xhci_hcd
[ 1204.368172] host01 kernel: usb 3-3: New USB device found, idVendor=20a0, idProduct=42dd, bcdDevice= 3.00
[ 1204.373524] host01 kernel: usb 3-3: New USB device strings: Mfr=1, Product=2, SerialNumber=0
[ 1204.373905] host01 kernel: usb 3-3: Product: USB COMPOSITE DEVICE
[ 1204.374167] host01 kernel: usb 3-3: Manufacturer: NXP SEMICONDUCTOR INC.
[ 1204.374376] host01 kernel: hid-generic 0003:20A0:42DD.0013: hiddev3,hidraw8: USB HID v1.00 Device [NXP SEMICONDUCTOR INC. USB COMPOSITE DEVICE] on usb-0000:00:14.0-3/input0
[ 1204.380434] host01 systemd[1698]: Stopped target smartcard.target - Smart Card.
[ 1204.381064] host01 systemd[1]: Stopped target smartcard.target - Smart Card.

The ACLs on /dev/hidraw8 look sane:
[~]$ getfacl /dev/hidraw8
getfacl: Removing leading '/' from absolute path names
# file: dev/hidraw8
# owner: root
# group: root
user::rw-
user:farblos:rw-
group::---
mask::rw-
other::---

Now I replug the NK3 and try:
[~]$ nitropy nk3 update
Command line tool to interact with Nitrokey devices 0.7.0
Do you want to download the firmware version v1.8.0? [Y/n]:
Download v1.8.0: 100%|█████████████████████| 1.08M/1.08M [00:00<00:00, 1.85MB/s]
Current firmware version:  v1.6.0
Updated firmware version:  v1.8.0

Please do not remove the Nitrokey 3 or insert any other Nitrokey 3 devices during the update. Doing so may damage the Nitrokey 3.
Do you want to perform the firmware update now? [y/N]: y

Please press the touch button to reboot the device into bootloader mode ...

Critical error:
An unhandled exception occurred
        Exception encountered: SPSDKConnectionError()

--------------------------------------------------------------------------------
Critical error occurred, exiting now
Unexpected? Is this a bug? Would you like to get support/help?
- You can report issues at: https://support.nitrokey.com/
- Writing an e-mail to<EMAIL_ADDRESS>is also possible
- Please attach the log: '/tmp/nitropy.log.er8mz_96' with any support/help request!
- Please check if you have udev rules installed: https://docs.nitrokey.com/nitrokeys/nitrokey3/firmware-update#troubleshooting-linux

For above button press the journal reports:
[ 1311.564133] host01 kernel: usb 3-3: USB disconnect, device number 17
[ 1311.876390] host01 kernel: usb 3-3: new high-speed USB device number 18 using xhci_hcd
[ 1312.024160] host01 kernel: usb 3-3: New USB device found, idVendor=20a0, idProduct=42dd, bcdDevice= 3.00
[ 1312.029334] host01 kernel: usb 3-3: New USB device strings: Mfr=1, Product=2, SerialNumber=0
[ 1312.029991] host01 kernel: usb 3-3: Product: USB COMPOSITE DEVICE
[ 1312.030400] host01 kernel: usb 3-3: Manufacturer: NXP SEMICONDUCTOR INC.
[ 1312.030748] host01 kernel: hid-generic 0003:20A0:42DD.0015: hiddev3,hidraw9: USB HID v1.00 Device [NXP SEMICONDUCTOR INC. USB COMPOSITE DEVICE] on usb-0000:00:14.0-3/input0
[ 1312.036321] host01 systemd[1698]: Stopped target smartcard.target - Smart Card.
[ 1312.036722] host01 systemd[1]: Stopped target smartcard.target - Smart Card.

Again, the ACLs on the device look OK:
[~]$ getfacl /dev/hidraw9
getfacl: Removing leading '/' from absolute path names
# file: dev/hidraw9
# owner: root
# group: root
user::rw-
user:farblos:rw-
group::---
mask::rw-
other::---

I have copied away the log file quoted above.  Here is what seems one relevant part to me (it is repeated in multiple variations):
14212     DEBUG nitrokey.nk3.updates Trying to connect to bootloader (try 1 of 3)
14212     DEBUG pynitrokey.cli.trussed Searching NK3 bootloader device (try 1 of 30)
14275      INFO nitrokey.trussed._bootloader.lpc55_upload.mboot.mcuboot Connect: identifier='usb', device= (0x20A0, 0x42DD)path=b'3-3:1.0'
14275     DEBUG nitrokey.trussed._bootloader.lpc55_upload.utils.interfaces.device.usb_device Opening the Interface:  (0x20A0, 0x42DD)path=b'3-3:1.0'
14277    WARNING pynitrokey.cli An unhandled exception occurred
Traceback (most recent call last):
  File "/home/farblos/.local/share/pipx/venvs/pynitrokey/lib/python3.12/site-packages/nitrokey/trussed/_bootloader/lpc55_upload/utils/interfaces/device/usb_device.py", line 78, in open
    self._device.open_path(self.path)
  File "hid.pyx", line 158, in hid.device.open_path
OSError: open failed

Since the error messages were not really helpful I tried an strace, where it became clear (?) that it is actually a file hid.pyx that is missing here (newlines in strace added by me):
4549  openat(AT_FDCWD, "/home/farblos/.local/share/pipx/venvs/pynitrokey/lib/python3.12/site-packages/nitrokey/trussed/_bootloader/lpc55_upload/utils/interfaces/device/usb_device.py", O_RDONLY|O_CLOEXEC) = 10
4549  fstat(10, {st_mode=S_IFREG|0644, st_size=5994, ...}) = 0
4549  ioctl(10, TCGETS, 0x7ffef2144e40) = -1 ENOTTY (Inappropriate ioctl for device)
4549  lseek(10, 0, SEEK_CUR)            = 0
4549  read(10, "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#\n# Copyright 2023 NXP\n#\n# SPDX-License-Identifier: BSD-3-Clause\n\n\"\"\"Low level Hid device.\"\"\"\nimport logging\nimport warnings\nfrom typing import TYPE_CHECKING, List, Optional\n\nfrom ....exceptions import SPSDKCon"..., 4096) = 4096
4549  read(10, "rror(\"Device is not opened for writing\")\n        try:\n            bytes_written = self._device.write(data)\n        except Exception as e:\n            raise SPSDKConnectionError(str(e)) from e\n        if bytes_written < 0 or bytes_written < len(data):\n     "..., 8192) = 1898
4549  read(10, "", 8192)                = 0
4549  close(10)                         = 0
4549  newfstatat(AT_FDCWD, "/home/farblos/.local/share/pipx/venvs/pynitrokey/lib/python3.12/site-packages/nitrokey/trussed/_bootloader/lpc55_upload/utils/interfaces/device/usb_device.py", {st_mode=S_IFREG|0644, st_size=5994, ...}, 0) = 0

4549  newfstatat(AT_FDCWD, "hid.pyx", 0x7ffef2144cb0, 0) = -1 ENOENT (No such file or directory)

4549  write(3, "22610    WARNING pynitrokey.cli An unhandled exception occurred\nTraceback (most recent call last):\n  File \"/home/farblos/.local/share/pipx/venvs/pynitrokey/lib/python3.12/site-packages/nitrokey/trussed/_bootloader/lpc55_upload/utils/interfaces/device/usb_"..., 4179) = 4179

What am I missing here?  I know little about Python.

Thanks for the detailed report!  I’m not sure if the hid.pyx error is the cause or just a symptom.  I’ll look into it.
Does the following udev rule fix the problem for you?
ATTRS{idVendor}=="20a0", ATTRS{idProduct}=="42dd", MODE="666"

Another idea – the hidapi library recently changed its default backend.  Can you check which version you are using?  The method depends on how you installed pynitrokey – generally, you need to run pip freeze | grep hidapi with the correct pip.

Like this?
[~]$ /home/farblos/.local/share/pipx/venvs/pynitrokey/bin/python3 -m pip freeze | grep hidapi
hidapi==0.14.0.post4

I probably should add here that I'm one of those preferring not to install the Debian Recommends - meaning that my system may be lacking packages which are "usually" installed.  But I'm not sure to what extent that matters when using pipx and venvs...
Will try the 0666 on the hidraw device tomorrow, but my gut feeling rather points to something missing in my Python setup ...

Yes, thank you!  I was able to reproduce the problem on my machine.  It is caused by a breaking change in a dependency, see https://github.com/trezor/cython-hidapi/issues/191.  There are two options to fix the problem:

Rollback to hidapi==0.14.0.post2, for example with pipx:pipx inject pynitrokey hidapi==0.14.0.post2

Add a new udev rule:ATTRS{idVendor}=="20a0", ATTRS{idProduct}=="42dd", MODE="666"

Thanks!  So you were right with your 0666 proposal, after all.
I will go for the pipx inject rollback as a work-around and see how you manage to fix this in the long term.  Of course, using the uaccess tag is way more elegant ...
Thanks again.

Completed the firmware update successfully after doing
pipx inject --force pynitrokey hidapi==0.14.0.post2

I package pynitrokey for gentoo (for my personal overlay), I ran into this issue as gentoo has hidapi 0.14.0_p4 (post4) and no older versions available, a workaround that worked for me personally was to add this local udev rule
ACTION!="add|change", GOTO="nk3_end"
ATTRS{idVendor}=="20a0", ATTRS{idProduct}=="42dd", TAG+="uaccess"
LABEL="nk3_end"

Now I wonder how I can make the package work for others too, is it as simple as modifying the udev rule that libnitrokey provides, removing all hidraw match filters?


How do I output the attention from the model?

Hi,
When running dnabert2, I'm trying to output not only the CLS and hidden states but also the attentions.
I tried:
`db2_model = AutoModel.from_pretrained(dirname, output_attentions=True, trust_remote_code=True)
output = db2_model(input_ids)
`
but the output is only a tuple of length 2 (the hidden states and the CLS tensor).
Any help would be much appreciated!
Thanks!

Hi,
I also have the same question. Could you please show where the finetuned model weight is saved?
Thanks a lot!

I'm here because I'm also looking for how to get the attention :'(
@ZoeyXiang1202 here is a small example to ge the hidden states:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
MODEL_ID = "zhihan1996/DNABERT-2-117M"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID, output_attentions=True, trust_remote_code=True)
model.eval()
dna_sequence = "ACTGACTGACTG"
inputs = tokenizer(dna_sequence, return_tensors="pt")

# Perform a forward pass to get the outputs
with torch.no_grad():  # Disable gradient computation for inference
    outputs = model(**inputs)

print( outputs.keys())

hidden_states = outputs['hidden_states']

# Check the type and shape of hidden_states
print("Hidden States Type:", type(hidden_states))
print("Number of Hidden States:", len(hidden_states))

# Print the shape of each hidden state tensor
for i, state in enumerate(hidden_states):
    print(f"Hidden State {i} Shape:", state.shape)

# Optional: Processing logits
probabilities = torch.softmax(outputs.logits, dim=-1)
print("Probabilities:", probabilities)


kubestone-controller-manager pod start issue

I'm getting this error when I try to deploy the kubestone-controller-manager pod.  Any ideas what might cause this?
Image is:
xridge/kubestone:latest
sha256:1f7cd4f90d5b6ef2db127d1fd4cf733b33aef4e90744325fa1a7557e70eb725d
2020-06-05T13:52:26.706Z        INFO    controller-runtime.metrics      metrics server is starting to listen    {"addr": ":8080"}
2020-06-05T13:52:26.746Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "iperf3", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.746Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "fio", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.746Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "sysbench", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.746Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "drill", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.747Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "pgbench", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.747Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "ioping", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.747Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "qperf", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.747Z        INFO    controller-runtime.controller   Starting EventSource    {"controller": "ycsbbench", "source": "kind source: /, Kind="}
2020-06-05T13:52:26.747Z        ERROR   controller-runtime.source       if kind is a CRD, it should be installed before calling Start   {"kind": "YcsbBench.perf.kubestone.xridge.io", "error": "no matches for kind \"YcsbBench\" in version \"perf.kubestone.xridge.io/v1alpha1\""}
github.com/go-logr/zapr.(*zapLogger).Error
        /go/pkg/mod/github.com/go-logr/zapr@v0.1.0/zapr.go:128
sigs.k8s.io/controller-runtime/pkg/source.(*Kind).Start
        /go/pkg/mod/sigs.k8s.io/controller-runtime@v0.2.0/pkg/source/source.go:88
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).Watch
        /go/pkg/mod/sigs.k8s.io/controller-runtime@v0.2.0/pkg/internal/controller/controller.go:122
sigs.k8s.io/controller-runtime/pkg/builder.(*Builder).doWatch
        /go/pkg/mod/sigs.k8s.io/controller-runtime@v0.2.0/pkg/builder/controller.go:162
sigs.k8s.io/controller-runtime/pkg/builder.(*Builder).Build
        /go/pkg/mod/sigs.k8s.io/controller-runtime@v0.2.0/pkg/builder/controller.go:151
sigs.k8s.io/controller-runtime/pkg/builder.(*Builder).Complete
        /go/pkg/mod/sigs.k8s.io/controller-runtime@v0.2.0/pkg/builder/controller.go:129
github.com/xridge/kubestone/controllers/ycsbbench.(*Reconciler).SetupWithManager
        /workspace/controllers/ycsbbench/controller.go:92
main.main
        /workspace/main.go:145
runtime.main
        /usr/local/go/src/runtime/proc.go:200
2020-06-05T13:52:26.747Z        ERROR   setup   unable to create controller     {"controller": "YcsbBench", "error": "no matches for kind \"YcsbBench\" in version \"perf.kubestone.xridge.io/v1alpha1\""}
github.com/go-logr/zapr.(*zapLogger).Error
        /go/pkg/mod/github.com/go-logr/zapr@v0.1.0/zapr.go:128
main.main
        /workspace/main.go:146
runtime.main
        /usr/local/go/src/runtime/proc.go:200

yes. your CRDs and operator seem to be missmatched.
For version v0.5.0 (which doesnt have ycsb):
kustomize build "github.com/xridge/kubestone.git/config/default?ref=v0.5.0"

or you can use the master branch which has ycsb:
kustomize build "github.com/xridge/kubestone.git/config/default?ref=master"

Ah i see the bug here. The v0.5.0 does not use xridge/kubestone:v0.5.0 image. It uses latest which is the master branch build.
You can update your Deployment to use xridge/kubestone:v0.5.0 or use the master CRDs as i just described.


TypeError: undefined is not a function - imagesLoaded ?

Not sure what the issue is - had some elements overlapping so I tried using imagesLoaded and I'm getting this error in console:
TypeError: undefined is not a function (line:95)
Here is my JS:
$( function() {

  var $container = $('.isotope').isotope({
    itemSelector: '.episode',
    masonry: {
      columnWidth: 250,
      gutter: 20,
      isFitWidth: true
    }
  });

  $container.imagesLoaded( function() {
    $container.isotope('layout');
  });

});

Also, here is our staging site where the error is showing: http://dftg.revelationconcept.com/journey/

Looks like you need to add imagesloaded.pkgd.js to your page.

Oh, wow. So sorry! I thought that was a part of the isotope library...I didn't see it was something separate in the documentation...thanks!


Add analytics events

Move between tabs between 'Docker extension' and 'Docker compose' in the wizard
Opening the observability panel
I'm not getting any events from clicking the 'Docker Extension Install' button - can you recheck?

Items 1 and 3 are resolved in https://github.com/digma-ai/digma-ui/pull/61


introduce hero slider block

Please always provide the GitHub issue(s) your PR is for, as well as test URLs where your change can be observed (before and after):
Fix #108
Test URLs:

Before: https://main--icicidirect--aemsites.hlx.live/research/equity

After: https://cta--icicidirect--aemsites.hlx.live/draft/vivesing/equity

[ ] New Blocks introduced in this PR
If yes, please provide details below

Block Name
Documentation

TBD

Block/Section Structure:

The right card seem to get cut as about 834px

Should the hero-slider be added to lcp candidatrs list?

In the current aem.js implementation, waitForLCP only checks for the first block in the document and in our case it is the breadcrumb block. We will have to change the default impl to wait for any block in the document to be the candidate of LCP. Since LHS is 100 without adding hero-slider block to the LCP list, would it make sense to skip it for now?
cc @sdmcraft

The right card seem to get cut as about 834px

Fixed it

The right card seem to get cut as about 834px

Fixed it !

Still see some truncation but we can take it up later.


Fixed #28913 -- Fixed error handling when MIGRATIONS_MODULES has a missing top-level package

When specifying a custom migration module package for an app in
the MIGRATIONS_MODULES setting, if the top-level package does not
exist, added relevant error handling so an informative
error message is displayed to the user while trying to make
migrations.
Signed-off-by: Sanket Saurav<EMAIL_ADDRESS>

A test is required.

@timgraham Added a test. Kindly let me know if this is adequate.


[Question] Validate end date must greater than the start time

Hi,
I have two parameters to query data in this time range. I'd like to validate the end time must greater than the start time. I'm not sure the approach is good or not. RuleFor for the object itself is accord with FluentValidation design?
RuleFor(x => x.StartTime).NotEmpty();
RuleFor(x => x.EndTime).NotEmpty();
RuleFor(x => x).Must(x => x.EndTime == default(DateTime) || x.StartTime == default(DateTime) || x.EndTime > x.StartTime)
        .WithMessage("EndTime must greater than StartTime");

Thanks :)

Sure, that's a perfectly supported scenario.

Thanks a lot.


offset strings

Strings that are at offsets of existing strings are not displayed inlined when they could be:

Fixed in the build #2229

2249


Add availability checks for debug report extension usage

Description
Adding the missing condition checks before using the structures and functions from the VK_EXT_debug_report extension in the samples.
Normal functionality should not change when the extension is supported, tested on a device where the extension is missing.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Thank you very much for your contribution. Note that CI fails at the clang format step, which means you need to properly format your changes with clang-format, see https://github.com/KhronosGroup/Vulkan-Samples/actions/runs/9530177624/job/26297193969?pr=1072

Thanks, I've updated the file now.


Unable to set placeholder with AlamofireSource

I am using Using ImageSlideshow (1.7.0) with AlamofireSource. Although placeholder is set but only a white screen is shown when the url is not found (Error 404), the placeholder is not shown. AlamofireSource is created by following code:
let source = AlamofireSource(urlString: pic_url, placeholder: UIImage(named: image_default_photo))
Found similar issue on https://github.com/zvonicek/ImageSlideshow/issues/309 , but adding imageView.image = self.placeholder to AlamofireSource "load" function in the first line does not help.
Thanks in advance.

Please reopen if you still see this happening!


train_annot_folder

hello. I am new to this whole AI thing. I am currently working on a project similar to this. I Would really like your help. I am not getting this " contains annotations in PASCAL VOC format (one xml file for each image)". I have my own dataset of images. What is this PASCAL VOC format? should I need to create one xml file of my very own image?  If yes, what should I put in it? I'm really clueless. Please help.

Hi, yes, you must create an xml file for each image. This xml file contains the characteristics of each object present in the image: bounding box coordinates, class of the object. You can see some examples in the data/train/annotation folder of this repository.

Hi, yes, you must create an xml file for each image. This xml file contains the characteristics of each object present in the image: bounding box coordinates, class of the object. You can see some examples in the data/train/annotation folder of this repository.

thank you so much!


Update final-form-builder.tsx styled component

Removing white-space: nowrap from FieldsGroup div styling
Saw #476 and figured I could tackle that issue.
Seemed to just involve removing the white-space directive to go back to a normal default.
My guess is that this was added in order to have titles themselves not wrap? If so, that functionality is probably gone as well, but I don't know if it's a breaking change to go from no-wrap to wrap.
Here's a screenshot of the change on the gatsby demo:

Awesome work @Spraynard, thanks! I'll take a look at this tomorrow morning :smile:

Thank you :)

We had a discussion at one point around text wrapping. For labels it was intentional that they don't wrap; we have text-overflow: ellipsis; on the label element. I think if we want to support text wrapping specifically for the description, we could put white-space: normal; on the FieldDescription component in packages/tinacms/src/plugins/fields/wrapFieldWithMeta.tsx and leave the final-form-builder.tsx white-space definition as-is.

Alright I think that we're all good now. I've updated wrapFieldWithMeta.tsx FieldDescription component styling to have white-space: normal defined.
From the looks of it, the layout that I'm getting is the same as what you were requesting. Example below.

Thank you very much for the guidance.

Thanks @Spraynard !

@all-contributors please add @Spraynard for code


Support build args in composefiles

You can now pass arguments to a build if you're using the new file format:
build:
  context: .
  args:
    buildno: 1

libcompose can read this fine. What is left to do is taking care of those args :angel:


Connect to Azure Data Lake using Polybase

Is it possible to connect to Azure Data Lake Gen2 ( or Gen1)  using Polybase in SQL Server ? Thanks !

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

ID: 94ab99ca-282b-6ace-6354-09a0d3ad97ad
Version Independent ID: 7448fdc3-2a74-1811-38c5-aafcef2630e7
Content: Configure PolyBase to access external data in Azure Blob Storage - SQL Server
Content Source: docs/relational-databases/polybase/polybase-configure-azure-blob-storage.md
Product: sql
Technology: polybase
GitHub Login: @MikeRayMSFT
Microsoft Alias: mikeray

@SuperSing Thank you for the question, assigning this to the author now.

@uc-msft - do you have any comment on this?

Hi @SuperSing - apologies for the delay. Currently here is the answer:

Connection to ADLS Gen 1 is not supported.
Connection to ADLS Gen 2 may be supported if the ADLS does not use a hierarchical namespace. To connect, create an external data source that connects to Azure Blob Storage with a wasb location prefix. See CREATE EXTERNAL DATA SOURCE (Transact-SQL).
Additional connection scenarios are supported with Multi-protocol access for Azure Data Lake Storage, which is currently available in public preview.


Fixed setfenv vulnerability

Disallowed use of setfenv on SF's own methods.
Credit to KubeRoot (@kubinator4321) for finding this exploit

No I don't, everything is included in the SF.Types table.


TINKERPOP-1041

Same as https://github.com/apache/incubator-tinkerpop/pull/207
But target on tp31

@velo do you have thoughts on how to proceed with windows CI now that we know apache infra doesn't currently support that?

I guess we would maintain the status quo.
May be a committer can enable an appveyor free account

Apache administers the github mirror so they would have to enable the commit hook to appveyor unless i'm missing something in how appveyor works.  I assume you can only enabled appveyor on a github repo you administer (like travis).  is that right?

You probably right
On Sat, 6 Feb 2016 12:30 stephen mallette<EMAIL_ADDRESS>wrote:

Apache administers the github mirror so they would have to enable the
commit hook to appveyor unless i'm missing something in how appveyor works.
I assume you can only enabled appveyor on a github repo you administer
(like travis). is that right?
—
Reply to this email directly or view it on GitHub
https://github.com/apache/incubator-tinkerpop/pull/209#issuecomment-180620586
.

I guess you should update the PR to remove the appveyor stuff then.
@pluradj have you had a look at this PR yet?  would be nice to get your review/vote as you have a windows environment that you could test it out on...

I'm running into some test failures when I do mvn clean install on Windows. I built on Linux and Mac without running into this.
Tests run: 9, Failures: 2, Errors: 2, Skipped: 0, Time elapsed: 37.053 sec <<< FAILURE! - in org.apache.tinkerpop.gremli
n.spark.SparkHadoopGremlinTest
shouldSupportRemoveAndListMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed
: 1.498 sec  <<< FAILURE!
java.lang.AssertionError: expected:<2> but was:<3>
        at org.junit.Assert.fail(Assert.java:88)
        at org.junit.Assert.failNotEquals(Assert.java:834)
        at org.junit.Assert.assertEquals(Assert.java:645)
        at org.junit.Assert.assertEquals(Assert.java:631)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkRemoveAndListMethods(AbstractStora
geCheck.java:84)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportRemoveAndListMethods(Fil
eSystemStorageCheck.java:58)

shouldNotHaveResidualDataInStorage(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapse
d: 1.372 sec  <<< FAILURE!
java.lang.AssertionError: null
        at org.junit.Assert.fail(Assert.java:86)
        at org.junit.Assert.assertTrue(Assert.java:41)
        at org.junit.Assert.assertFalse(Assert.java:64)
        at org.junit.Assert.assertFalse(Assert.java:74)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkResidualDataInStorage(AbstractStor
ageCheck.java:133)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldNotHaveResidualDataInStorage(Fi
leSystemStorageCheck.java:78)

shouldSupportCopyMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed: 0.702 s
ec  <<< ERROR!
java.util.concurrent.ExecutionException: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/p
luradj/src/github/apache/incubator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/SparkHadoopGraphProvider
/graph-provider-data/clusterCount already exists
        at java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
        at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1895)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkCopyMethods(AbstractStorageCheck.j
ava:109)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportCopyMethods(FileSystemSt
orageCheck.java:69)
Caused by: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/src/github/apache/incub
ator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/SparkHadoopGraphProvider/graph-provider-data/clusterCo
unt already exists
        at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:146)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scal
a:1011)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
        at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:9
38)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
        at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:930)
        at org.apache.spark.api.java.JavaPairRDD.saveAsNewAPIHadoopFile(JavaPairRDD.scala:809)
        at org.apache.tinkerpop.gremlin.spark.structure.io.OutputFormatRDD.writeMemoryRDD(OutputFormatRDD.java:65)
        at org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer.lambda$submitWithExecutor$1(SparkGraph
Computer.java:271)
        at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1590)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

shouldSupportHeadMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed: 0.032 s
ec  <<< ERROR!
java.io.IOException: Unable to delete file: C:\home\pluradj\src\github\apache\incubator-tinkerpop\TINKERPOP-1041\spark-g
remlin\target\test-case-data\SparkHadoopGraphProvider\graph-provider-data\~reducing\part-r-00001
        at org.apache.commons.io.FileUtils.forceDelete(FileUtils.java:2279)
        at org.apache.commons.io.FileUtils.cleanDirectory(FileUtils.java:1653)
        at org.apache.commons.io.FileUtils.deleteDirectory(FileUtils.java:1535)
        at org.apache.commons.io.FileUtils.forceDelete(FileUtils.java:2270)
        at org.apache.commons.io.FileUtils.cleanDirectory(FileUtils.java:1653)
        at org.apache.commons.io.FileUtils.deleteDirectory(FileUtils.java:1535)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.deleteDirectory(FileSystemStorageChec
k.java:101)
        at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportHeadMethods(FileSystemSt
orageCheck.java:49)

Running org.apache.tinkerpop.gremlin.spark.structure.io.InputOutputRDDTest
[WARN] org.apache.tinkerpop.gremlin.hadoop.process.computer.AbstractHadoopGraphComputer$Features - Unknown OutputFormat
class and thus, persistence options are unknown -- assuming all options are possible
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 1.346 sec - in org.apache.tinkerpop.gremlin.spark.struct
ure.io.InputOutputRDDTest
Running org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest
Tests run: 2, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 4.933 sec <<< FAILURE! - in org.apache.tinkerpop.gremlin
.spark.structure.io.InputRDDTest
shouldReadFromArbitraryRDD(org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest)  Time elapsed: 3.224 sec  <<< E
RROR!
java.lang.IllegalStateException: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/s
rc/github/apache/incubator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/InputRDDTest/shouldReadFromArbit
raryRDD/~reducing already exists
        at java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
        at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1895)
        at org.apache.tinkerpop.gremlin.process.computer.traversal.step.map.ComputerResultStep.processNextStart(Computer
ResultStep.java:80)
        at org.apache.tinkerpop.gremlin.process.traversal.step.util.AbstractStep.next(AbstractStep.java:126)
        at org.apache.tinkerpop.gremlin.process.traversal.step.util.AbstractStep.next(AbstractStep.java:37)
        at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next(DefaultTraversal.java:157)
        at org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest.shouldReadFromArbitraryRDD(InputRDDTest.java:56)

Caused by: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/src/github/apache/incub
ator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/InputRDDTest/shouldReadFromArbitraryRDD/~reducing alre
ady exists
        at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:146)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scal
a:1011)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
        at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:998)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:9
38)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
        at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:930)
        at org.apache.spark.api.java.JavaPairRDD.saveAsNewAPIHadoopFile(JavaPairRDD.scala:809)
        at org.apache.tinkerpop.gremlin.spark.structure.io.OutputFormatRDD.writeMemoryRDD(OutputFormatRDD.java:65)
        at org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer.lambda$submitWithExecutor$1(SparkGraph
Computer.java:271)
        at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1590)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

Travis seems happy, so it's something in my environment?
Apache Maven 3.3.3<PHONE_NUMBER>791599e205a5524ec3e0dfe41d4a06; 2015-04-22T07:57:37-04:00)
Maven home: C:\home\pluradj\usr\lib\apache-maven-3.3.3\bin\..
Java version: 1.8.0_66, vendor: Oracle Corporation
Java home: C:\home\pluradj\usr\lib\jdk1.8.0_66\jre
Default locale: en_US, platform encoding: Cp1252
OS name: "windows 7", version: "6.1", arch: "amd64", family: "dos"

Yes, I was not able to fix this errors.
But if you run either master or tp311, more will fail
On Thu, 11 Feb 2016 04:01 Jason Plurad<EMAIL_ADDRESS>wrote:

I'm running into some test failures when I do mvn clean install on
Windows. I built on Linux and Mac without running into this.
Tests run: 9, Failures: 2, Errors: 2, Skipped: 0, Time elapsed: 37.053 sec <<< FAILURE! - in org.apache.tinkerpop.gremli
n.spark.SparkHadoopGremlinTest
shouldSupportRemoveAndListMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed
: 1.498 sec  <<< FAILURE!
java.lang.AssertionError: expected:<2> but was:<3>
at org.junit.Assert.fail(Assert.java:88)
at org.junit.Assert.failNotEquals(Assert.java:834)
at org.junit.Assert.assertEquals(Assert.java:645)
at org.junit.Assert.assertEquals(Assert.java:631)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkRemoveAndListMethods(AbstractStora
geCheck.java:84)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportRemoveAndListMethods(Fil
eSystemStorageCheck.java:58)
shouldNotHaveResidualDataInStorage(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapse
d: 1.372 sec  <<< FAILURE!
java.lang.AssertionError: null
at org.junit.Assert.fail(Assert.java:86)
at org.junit.Assert.assertTrue(Assert.java:41)
at org.junit.Assert.assertFalse(Assert.java:64)
at org.junit.Assert.assertFalse(Assert.java:74)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkResidualDataInStorage(AbstractStor
ageCheck.java:133)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldNotHaveResidualDataInStorage(Fi
leSystemStorageCheck.java:78)
shouldSupportCopyMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed: 0.702 s
ec  <<< ERROR!
java.util.concurrent.ExecutionException: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/p
luradj/src/github/apache/incubator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/SparkHadoopGraphProvider
/graph-provider-data/clusterCount already exists
at java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1895)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.AbstractStorageCheck.checkCopyMethods(AbstractStorageCheck.j
ava:109)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportCopyMethods(FileSystemSt
orageCheck.java:69)
Caused by: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/src/github/apache/incub
ator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/SparkHadoopGraphProvider/graph-provider-data/clusterCo
unt already exists
at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:146)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scal
a:1011)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:9
38)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:930)
at org.apache.spark.api.java.JavaPairRDD.saveAsNewAPIHadoopFile(JavaPairRDD.scala:809)
at org.apache.tinkerpop.gremlin.spark.structure.io.OutputFormatRDD.writeMemoryRDD(OutputFormatRDD.java:65)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer.lambda$submitWithExecutor$1(SparkGraph
Computer.java:271)
at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1590)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
shouldSupportHeadMethods(org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck)  Time elapsed: 0.032 s
ec  <<< ERROR!
java.io.IOException: Unable to delete file: C:\home\pluradj\src\github\apache\incubator-tinkerpop\TINKERPOP-1041\spark-g
remlin\target\test-case-data\SparkHadoopGraphProvider\graph-provider-data~reducing\part-r-00001
at org.apache.commons.io.FileUtils.forceDelete(FileUtils.java:2279)
at org.apache.commons.io.FileUtils.cleanDirectory(FileUtils.java:1653)
at org.apache.commons.io.FileUtils.deleteDirectory(FileUtils.java:1535)
at org.apache.commons.io.FileUtils.forceDelete(FileUtils.java:2270)
at org.apache.commons.io.FileUtils.cleanDirectory(FileUtils.java:1653)
at org.apache.commons.io.FileUtils.deleteDirectory(FileUtils.java:1535)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.deleteDirectory(FileSystemStorageChec
k.java:101)
at org.apache.tinkerpop.gremlin.hadoop.structure.io.FileSystemStorageCheck.shouldSupportHeadMethods(FileSystemSt
orageCheck.java:49)
Running org.apache.tinkerpop.gremlin.spark.structure.io.InputOutputRDDTest
[WARN] org.apache.tinkerpop.gremlin.hadoop.process.computer.AbstractHadoopGraphComputer$Features - Unknown OutputFormat
class and thus, persistence options are unknown -- assuming all options are possible
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 1.346 sec - in org.apache.tinkerpop.gremlin.spark.struct
ure.io.InputOutputRDDTest
Running org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest
Tests run: 2, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 4.933 sec <<< FAILURE! - in org.apache.tinkerpop.gremlin
.spark.structure.io.InputRDDTest
shouldReadFromArbitraryRDD(org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest)  Time elapsed: 3.224 sec  <<< E
RROR!
java.lang.IllegalStateException: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/s
rc/github/apache/incubator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/InputRDDTest/shouldReadFromArbit
raryRDD/~reducing already exists
at java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1895)
at org.apache.tinkerpop.gremlin.process.computer.traversal.step.map.ComputerResultStep.processNextStart(Computer
ResultStep.java:80)
at org.apache.tinkerpop.gremlin.process.traversal.step.util.AbstractStep.next(AbstractStep.java:126)
at org.apache.tinkerpop.gremlin.process.traversal.step.util.AbstractStep.next(AbstractStep.java:37)
at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next(DefaultTraversal.java:157)
at org.apache.tinkerpop.gremlin.spark.structure.io.InputRDDTest.shouldReadFromArbitraryRDD(InputRDDTest.java:56)
Caused by: org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory C:/home/pluradj/src/github/apache/incub
ator-tinkerpop/TINKERPOP-1041/spark-gremlin/target/test-case-data/InputRDDTest/shouldReadFromArbitraryRDD/~reducing alre
ady exists
at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:146)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scal
a:1011)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:998)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:9
38)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:930)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:930)
at org.apache.spark.api.java.JavaPairRDD.saveAsNewAPIHadoopFile(JavaPairRDD.scala:809)
at org.apache.tinkerpop.gremlin.spark.structure.io.OutputFormatRDD.writeMemoryRDD(OutputFormatRDD.java:65)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer.lambda$submitWithExecutor$1(SparkGraph
Computer.java:271)
at java.util.concurrent.CompletableFuture$AsyncSupply.run(CompletableFuture.java:1590)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Travis seems happy, so it's something in my environment?
Apache Maven 3.3.3<PHONE_NUMBER>791599e205a5524ec3e0dfe41d4a06; 2015-04-22T07:57:37-04:00)
Maven home: C:\home\pluradj\usr\lib\apache-maven-3.3.3\bin..
Java version: 1.8.0_66, vendor: Oracle Corporation
Java home: C:\home\pluradj\usr\lib\jdk1.8.0_66\jre
Default locale: en_US, platform encoding: Cp1252
OS name: "windows 7", version: "6.1", arch: "amd64", family: "dos"
—
Reply to this email directly or view it on GitHub
https://github.com/apache/incubator-tinkerpop/pull/209#issuecomment-182410088
.

You're right, fair enough.
Did you pull the TP3 codebase into Eclipse and run the tests within it?
The code changes look good to me.

Yes, they also fail on eclipse
On Thu, 11 Feb 2016 07:18 Jason Plurad<EMAIL_ADDRESS>wrote:

You're right, fair enough.
Did you pull the TP3 codebase into Eclipse and run the tests within it?
The code changes look good to me.
—
Reply to this email directly or view it on GitHub
https://github.com/apache/incubator-tinkerpop/pull/209#issuecomment-182512844
.

I was referring to the testcases from the JIRA... do those now work in Eclipse?

Ow, i never tried to run all tests in eclipse...
On Thu, 11 Feb 2016 07:25 Jason Plurad<EMAIL_ADDRESS>wrote:

I was referring to the testcases from the JIRA... do those now work in
Eclipse?
—
Reply to this email directly or view it on GitHub
https://github.com/apache/incubator-tinkerpop/pull/209#issuecomment-182516098
.

@spmallette I just asked apache infra for it.
https://issues.apache.org/jira/browse/INFRA-11249
Hopefully we will get that working.

BTW, @pluradj  any idea on what to do on the broken tests?

@velo thanks for getting appveyor enabled - the process described to me for doing that didn't seem as if it would be that simple - cool

@velo I've been digging around on it. Haven't figured anything out yet.

+1 on appveyor enablement

Perhaps we should re-calibrate a bit here. The original ticket was about getting the StructureStandardTestSuite working on windows (which can be a blocker for graph providers doing dev on windows).  As far as i can gather, that much is fixed.  As a bonus, @velo got us a build on windows through appveyor and even got apache infra to enable it for us.
There are some good fixes in this PR as-is and it would be nice to see appveyors yaml in the main dev branches.  Since the original issue is resolved, let's get this PR up for VOTE.  To do that, we need appveyor yaml to change slightly so that it doesn't fail the build.  Since the tests don't all pass, @velo can you please change the build to -Dspark-gremlin.skip.tests=true or maybe even skip just the failing tests -Dspark-gremlin.test.excludes="**/*ExcludeTest.java - we do that temporarily until a separate pull request can address those failures (we'll need a new ticket obviously).
Does that sound reasonable?

@spmallette sounds ok to me. I have a couple small fixes figured out, but I'm suspecting that the local Spark job is holding on to file handles, which prevents it from deleting files.
Vote: +1. Nice work @velo!

@spmallette @pluradj done, I create a appveyor profile which skips the broken tests

Looks like appveyor still isn't happy for some reason.....build failed on spark apparently.  @velo as soon as you can get that build to go green we can dig deeper on review/VOTE. thanks.

Done

Any news on this?

ah - sorry - just got a little busy on other things. we should get this over to tp31.  @pluradj can you please vote on this from the windows perspective?
I'll vote before end of week - then we just need one more....hopefully we close out by end of week.

I voted +1 a few days ago.
The changes for appveyor since then look fine too. I added a windows profile in the spark-gremlin/pom.xml to exclude the same tests as appveyor, mvn clean install on a local Windows build. I tested with Windows 7.
mvn clean install
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary:
[INFO]
[INFO] Apache TinkerPop ................................... SUCCESS [ 12.979 s]
[INFO] Apache TinkerPop :: Gremlin Shaded ................. SUCCESS [  5.288 s]
[INFO] Apache TinkerPop :: Gremlin Core ................... SUCCESS [ 45.655 s]
[INFO] Apache TinkerPop :: Gremlin Test ................... SUCCESS [ 20.554 s]
[INFO] Apache TinkerPop :: Gremlin Groovy ................. SUCCESS [01:10 min]
[INFO] Apache TinkerPop :: Gremlin Groovy Test ............ SUCCESS [ 11.831 s]
[INFO] Apache TinkerPop :: TinkerGraph Gremlin ............ SUCCESS [01:58 min]
[INFO] Apache TinkerPop :: Hadoop Gremlin ................. SUCCESS [07:21 min]
[INFO] Apache TinkerPop :: Spark Gremlin .................. SUCCESS [01:12 min]
[INFO] Apache TinkerPop :: Giraph Gremlin ................. SUCCESS [ 16.402 s]
[INFO] Apache TinkerPop :: Neo4j Gremlin .................. SUCCESS [  8.352 s]
[INFO] Apache TinkerPop :: Gremlin Driver ................. SUCCESS [ 13.021 s]
[INFO] Apache TinkerPop :: Gremlin Server ................. SUCCESS [ 12.301 s]
[INFO] Apache TinkerPop :: Gremlin Console ................ SUCCESS [ 22.349 s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 14:31 min
[INFO] Finished at: 2016-02-18T14:46:07-05:00
[INFO] Final Memory: 148M/2211M
[INFO] ------------------------------------------------------------------------

oh - thanks @pluradj - i must have missed your vote.
I'm going to run the full integration tests on ubuntu just to be sure nothing is busted there.  I assume that since we still don't have a complete build for windows with mvn clean install there would be problems with integration tests in that environment.  If the tests all pass on my end I think this should be good to go.

FWIW, I would skip broken tests on Windows... is more likely to someone fix
them if they were broken :)

You can't be serious velo, right? I originally reported that bug. The test suite is effectively the specification for TinkerPop vendors. That's a good thing in and on itself, but it also means that it must be as clean and polished as it can possibly be. Believe me, the VERY LAST thing you want to do as a TinkerPop vendor is to go in and fix a broken test. It would be analoguous to changing the system specification while implementing the system. The suite needs to be reliable, without any other formal specification, there's no way around it.

sorry, misspelled... I mean to say "I wouldn't skip broken tests on windows"

Oh ok, alright then :)

i was working on the assumption that the tests skipped would get a fresh JIRA ticket to track the change.  In my mind, having the core of tinkerpop building on windows with most tests working was better than not having anything at all - which is where we are now on tp31 and master.

agreed, that is why I created an appveyor profile... which skips this tests...
But I wouldn't create a windows profile.... the idea being this broken tests should be a pain for windows devs (like me)

I've grown suspicious of this line:
https://github.com/apache/incubator-tinkerpop/pull/209/files#diff-8ae08149638a77bbb943e6bb8438cfb6R631
because you awaitTermination without calling shutdown first. Calling shutdownNow after it doesn't indicate an orderly shutdown either and nothing is done with the list of returned un-executed tasks....
that said, I don't think it really matters though because we actually got that test much more stable on the tp31 line since you originally branched this.  I just wanted to bring those points to your attention in case you had comments.  When I merge your branch to tp31 locally, those lines you added go away.
I had some failures with integration tests last night, but solved the problem this morning (bug in the latest tp31 branch).  I'll need to re-run the tests gain in full tonight after that fix. If all works, I can vote positively tomorrow.

The way it was before, I would see intermittent errors on windows.
AwaitTermination will "Blocks until all tasks have completed execution after a shutdown request, or the timeout occurs, or the current thread is interrupted, whichever happens first."
So, it will either return after timeout or well all finish.
Them it runs a forcefully shutdown.
That way this tests become stable either here or in the appveyor.

You quoted the javadoc there and that's precisely my point about something looking wrong.  If my interpretation of that javadoc and the java source code is correct, awaitTermination is returning false after blocking (due to timeout), and you are just sleeping the thread for 30 seconds. which is plenty of time for that work to finish. then you call a hard shutdownNow which has no effect really because there are no more tasks executed. awaitTermintation requires a call to shutdown somewhere for it to ever return true (success).
if this was a problem for appveyor I suggest you update your branch with the latest changes which should have fixed the problems we were seeing with this test:
https://github.com/apache/incubator-tinkerpop/blob/tp31/gremlin-groovy/src/test/java/org/apache/tinkerpop/gremlin/groovy/engine/GremlinExecutorTest.java#L634-L638
Let's see if appveyor is happy with that change before we go to merge this.

@spmallette rebased my pull request with tp31, all green!

VOTE +1

I cant test in a windows environment, but given the comments in this discussion and a manual review of changes, it all seems to be good.
VOTE: +1

merged - @velo thanks for working through this with us. it would be great if you could add a JIRA ticket for any remaining issues we have with this (e.g. tests we ignored for purpose of getting this merged back to master early). Thanks!