HELP！many issuea，but i flow your tips

[Aurora-Rong]

$ bash scripts/run_detnas_coco_fpn_300M_search.sh

---

Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.

---

Traceback (most recent call last): File "tools/train_net.py", line 19, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script _compile_and_register_class(obj, _rcb, qualified_name) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

Traceback (most recent call last): File "tools/train_net.py", line 19, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script _compile_and_register_class(obj, _rcb, qualified_name) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

Traceback (most recent call last): File "tools/train_net.py", line 19, in

from maskrcnn_benchmark.data import make_data_loader

File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script Traceback (most recent call last): File "tools/train_net.py", line 19, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in _compile_and_register_class(obj, _rcb, qualified_name) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in return torch.jit.script(fn, _rcb=rcb) from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

_compile_and_register_class(obj, _rcb, qualified_name)

File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

Traceback (most recent call last): File "tools/train_net.py", line 19, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script Traceback (most recent call last): Traceback (most recent call last): File "tools/train_net.py", line 19, in _compile_and_register_class(obj, _rcb, qualified_name) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class Traceback (most recent call last): File "tools/train_net.py", line 19, in File "tools/train_net.py", line 19, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from maskrcnn_benchmark.data import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/init.py", line 2, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from .build import make_data_loader File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in _jit_script_class_compile(qualified_name, ast, rcb) from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn from .coco import COCODataset File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in from .build import make_data_loader import torchvision File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/build.py", line 11, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in import torchvision File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from torchvision import models File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in from . import datasets as D File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/init.py", line 3, in from torchvision import models from . import detection File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in from .coco import COCODataset from .faster_rcnn import *from . import detection

File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in File "/home/mist/DetNAS-master/maskrcnn_benchmark/data/datasets/coco.py", line 3, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in

import torchvision  File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in <module>

File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/init.py", line 3, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetworkfrom torchvision import models

File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/init.py", line 12, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in class BalancedPositiveNegativeSampler(object): File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script from . import detectionfrom . import _utils as det_utils

File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/init.py", line 1, in File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in class BalancedPositiveNegativeSampler(object): from .faster_rcnn import * File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script

File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/faster_rcnn.py", line 13, in from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/rpn.py", line 11, in from . import _utils as det_utils File "/mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py", line 19, in fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError_compile_and_register_class(obj, _rcb, qualified_name):

builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class

class BalancedPositiveNegativeSampler(object):

File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1219, in script _compile_and_register_class(obj, _rcb, qualified_name) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn _compile_and_register_class(obj, _rcb, qualified_name)return torch.jit.script(fn, _rcb=rcb) _jit_script_class_compile(qualified_name, ast, rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn

File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1076, in _compile_and_register_class return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: _jit_script_class_compile(qualified_name, ast, rcb) builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/_recursive.py", line 222, in try_compile_fn return torch.jit.script(fn, _rcb=rcb) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/jit/init.py", line 1226, in script fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj)) RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj))

RuntimeError: builtin cannot be used as a value: at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype=dtype, layout=tensor.layout, ~~~~~~~~~~~~~ <--- HERE device=tensor.device, pin_memory=tensor.is_pinned()) 'zeros_like' is being compiled since it was called from 'torch.torchvision.models.detection._utils.BalancedPositiveNegativeSampler.call' at /mistgpu/miniconda/lib/python3.7/site-packages/torchvision/models/detection/_utils.py:72:12

        # randomly select positive and negative examples
        perm1 = torch.randperm(positive.numel(), device=positive.device)[:num_pos]
        perm2 = torch.randperm(negative.numel(), device=negative.device)[:num_neg]

        pos_idx_per_image = positive[perm1]
        neg_idx_per_image = negative[perm2]

        # create binary mask from indices
        pos_idx_per_image_mask = zeros_like(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...  <--- HERE
            matched_idxs_per_image, dtype=torch.uint8
        )
        neg_idx_per_image_mask = zeros_like(
            matched_idxs_per_image, dtype=torch.uint8
        )

        pos_idx_per_image_mask[pos_idx_per_image] = torch.tensor(1, dtype=torch.uint8)
        neg_idx_per_image_mask[neg_idx_per_image] = torch.tensor(1, dtype=torch.uint8)

Traceback (most recent call last): File "/mistgpu/miniconda/lib/python3.7/runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "/mistgpu/miniconda/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in main() File "/mistgpu/miniconda/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main cmd=cmd) subprocess.CalledProcessError: Command '['/mistgpu/miniconda/bin/python3', '-u', 'tools/train_net.py', '--local_rank=7', '--config-file', 'configs/e2e_faster_rcnn_DETNAS_COCO_FPN_300M_search.yaml', 'OUTPUT_DIR', 'models/DETNAS_COCO_FPN_300M_1x_search']' returned non-zero exit status 1.

[yukang2017]

Sorry for the late reply. I thinks this issue might comes from the installation. Would you please show your torch and torchvision version?