TypeError: can't assign a numpy.int64 to a torch.FloatTensor #452

goodproj13 · 2019-02-28T17:34:42Z

Guys,
Did anyone know what caused this issue below? Many thanks in advance.
Torch: 0.40
Python: 3.6

We use voc format of KITTI dataset. The only thing I changed for the original code from this repo is to change the picture format from "jpg" to "png" which is the format for KITTI dataset. When I run ''python trainvel_net.py", I got error below:

Traceback (most recent call last):
File "trainval_net.py", line 209, in
imdb.num_classes, training=True)
File "/home/NewPartion/pycharm/faster-rcnn.pytorch/lib/roi_data_layer/roibatchLoader.py", line 54, in init
self.ratio_list_batch[left_idx:(right_idx+1)] = target_ratio
TypeError: can't assign a numpy.int64 to a torch.FloatTensor

EMCP · 2019-03-14T19:34:51Z

please paste all the output from your training run.. so we can see if you enabled CUDA, etc...

ma-xu · 2019-04-12T15:26:28Z

Did you solve this problem? I have the same issue ...

goodproj13 · 2019-04-12T15:28:50Z

I didn't solve the problem and I ended up using other's. Sorry!

…

________________________________ From: Xu Ma <notifications@github.com> Sent: Friday, April 12, 2019 11:26:30 AM To: jwyang/faster-rcnn.pytorch Cc: Dongfang Liu; Author Subject: Re: [jwyang/faster-rcnn.pytorch] TypeError: can't assign a numpy.int64 to a torch.FloatTensor (#452) Did you solve this problem? I have the same issue ... — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub<#452 (comment)>, or mute the thread<https://github.com/notifications/unsubscribe-auth/ALO7KPSBVIN5LS4PTJWHQJDPQCS2NANCNFSM4G25NUQQ>.

ma-xu · 2019-04-12T15:47:30Z

Maybe I should try mmdetection or Detectron ...

Weizhongjin · 2019-04-16T07:07:51Z

Change original code to
temp = torch.ones(batch_size)*target_ratio
self.ratio_list_batch[left_idx:(right_idx+1)] = temp

benedictflorance · 2019-06-04T16:05:09Z

@Weizhongjin

Change original code to
temp = torch.ones(batch_size)*target_ratio
self.ratio_list_batch[left_idx:(right_idx+1)] = temp

Doing the above fix throws this error:

**TypeError: mul() received an invalid combination of arguments - got (numpy.int64), but expected one of:
 * (Tensor other)
      didn't match because some of the arguments have invalid types: (numpy.int64)
 * (float other)
      didn't match because some of the arguments have invalid types: (numpy.int64)

**

Has anyone found a fix for this?

benedictflorance · 2019-06-04T16:09:59Z

@EMCP

Called with args:
Namespace(batch_size=1, checkepoch=1, checkpoint=0, checkpoint_interval=10000, checksession=1, class_agnostic=False, cuda=True, dataset='hollywoodheads_scuta', disp_interval=100, lamda=0.1, large_scale=False, lr=0.002, lr_decay_gamma=0.1, lr_decay_step=6, mGPUs=True, max_epochs=5, net='vgg16', num_workers=0, optimizer='sgd', resume=False, save_dir='data/adaptation/experiments', session=1, start_epoch=1, use_tfboard=False)
loading our dataset...........
/export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch/lib/model/utils/config.py:376: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
  yaml_cfg = edict(yaml.load(f))
Using config:
{'ANCHOR_RATIOS': [0.5, 1, 2],
 'ANCHOR_SCALES': [4, 8, 16, 32],
 'CROP_RESIZE_WITH_MAX_POOL': False,
 'CUDA': False,
 'DATA_DIR': '/export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch/data',
 'DEDUP_BOXES': 0.0625,
 'DSN_DIFF_WEIGHT': 100000,
 'EPS': 1e-14,
 'EXP_DIR': 'vgg16',
 'FEAT_STRIDE': [16],
 'GPU_ID': 0,
 'MATLAB': 'matlab',
 'MAX_NUM_GT_BOXES': 50,
 'MOBILENET': {'DEPTH_MULTIPLIER': 1.0,
               'FIXED_LAYERS': 5,
               'REGU_DEPTH': False,
               'WEIGHT_DECAY': 4e-05},
 'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
 'POOLING_MODE': 'align',
 'POOLING_SIZE': 7,
 'RESNET': {'FIXED_BLOCKS': 1, 'MAX_POOL': False},
 'RNG_SEED': 3,
 'ROOT_DIR': '/export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch',
 'TEST': {'BBOX_REG': True,
          'HAS_RPN': True,
          'MAX_SIZE': 1000,
          'MODE': 'nms',
          'NMS': 0.3,
          'PROPOSAL_METHOD': 'gt',
          'RPN_MIN_SIZE': 16,
          'RPN_NMS_THRESH': 0.7,
          'RPN_POST_NMS_TOP_N': 300,
          'RPN_PRE_NMS_TOP_N': 6000,
          'RPN_TOP_N': 5000,
          'SCALES': [600],
          'SVM': False},
 'TRAIN': {'ASPECT_GROUPING': False,
           'BATCH_SIZE': 256,
           'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
           'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0],
           'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2],
           'BBOX_NORMALIZE_TARGETS': True,
           'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
           'BBOX_REG': True,
           'BBOX_THRESH': 0.5,
           'BG_THRESH_HI': 0.5,
           'BG_THRESH_LO': 0.0,
           'BIAS_DECAY': False,
           'BN_TRAIN': False,
           'DISPLAY': 10,
           'DOUBLE_BIAS': True,
           'FG_FRACTION': 0.25,
           'FG_THRESH': 0.5,
           'GAMMA': 0.1,
           'HAS_RPN': True,
           'IMS_PER_BATCH': 1,
           'LEARNING_RATE': 0.01,
           'MAX_SIZE': 1000,
           'MOMENTUM': 0.9,
           'PROPOSAL_METHOD': 'gt',
           'RPN_BATCHSIZE': 256,
           'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
           'RPN_CLOBBER_POSITIVES': False,
           'RPN_FG_FRACTION': 0.5,
           'RPN_MIN_SIZE': 8,
           'RPN_NEGATIVE_OVERLAP': 0.3,
           'RPN_NMS_THRESH': 0.7,
           'RPN_POSITIVE_OVERLAP': 0.7,
           'RPN_POSITIVE_WEIGHT': -1.0,
           'RPN_POST_NMS_TOP_N': 2000,
           'RPN_PRE_NMS_TOP_N': 12000,
           'SCALES': [600],
           'SNAPSHOT_ITERS': 5000,
           'SNAPSHOT_KEPT': 3,
           'SNAPSHOT_PREFIX': 'res101_faster_rcnn',
           'STEPSIZE': [30000],
           'SUMMARY_INTERVAL': 180,
           'TRIM_HEIGHT': 600,
           'TRIM_WIDTH': 600,
           'TRUNCATED': False,
           'USE_ALL_GT': True,
           'USE_FLIPPED': True,
           'USE_GT': False,
           'WEIGHT_DECAY': 0.0005},
 'USE_GPU_NMS': True}
Loaded dataset `hollywoodheads_scuta_2007_train_s` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
hollywoodheads_scuta_2007_train_s gt roidb loaded from /export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch/data/cache/hollywoodheads_scuta_2007_train_s_gt_roidb.pkl
done
Preparing training data...
done
before filtering, there are 200 images...
after filtering, there are 200 images...
Source Train Size =  200
Loaded dataset `hollywoodheads_scuta_2007_train_t` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
hollywoodheads_scuta_2007_train_t gt roidb loaded from /export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch/data/cache/hollywoodheads_scuta_2007_train_t_gt_roidb.pkl
done
Preparing training data...
done
before filtering, there are 200 images...
after filtering, there are 200 images...
Target Train Size =  200
source 200 target 200 roidb entries
Traceback (most recent call last):
  File "da_trainval_net.py", line 257, in <module>
    s_imdb.num_classes, training=True)
  File "/export/livia/home/vision/bflorance/da-faster-rcnn-PyTorch/lib/roi_da_data_layer/roibatchLoader.py", line 55, in __init__
    self.ratio_list_batch[left_idx:(right_idx+1)] = target_ratio    # trainset ratio list ,each batch is same number
TypeError: can't assign a numpy.int64 to a torch.FloatTensor

EMCP · 2019-06-04T16:35:33Z

Can you possibly upgrade to PyTorch 1.0 ? I've used exclusively 1.x and had zero issues for months now

benedictflorance · 2019-06-04T16:37:54Z

@EMCP I'm working on domain adaptation (https://github.com/tiancity-NJU/da-faster-rcnn-PyTorch) and it uses the PyTorch 0.4 version of this repo. :(

EMCP · 2019-06-04T16:40:49Z

okay i am abroad from my deep learning rig, so I cannot test PyTorch .4 until mid June... but I would diff the two versions and ensure you've got any/all bug fixes pushed to the 1.x version... I never ran the Master branch so I cannot get a sense if it's been properly patched or not..

IMO , the repo owner should just do a release branch for older PyTorch versions and stick to the bleeding edge in Master root, instead of this 1.x off on the side strategy.

benedictflorance · 2019-06-06T17:07:32Z

self.ratio_list_batch[left_idx:(right_idx+1)] = torch.tensor(target_ratio.astype(np.float64)) # trainset ratio list ,each batch is same number
This fixed the issue for 0.4.0

EMCP · 2019-06-08T17:17:18Z

feel free to submit a PR and close @benedictflorance

benedictflorance · 2019-06-09T03:19:44Z

Yeah, I've submitted one.
#573

Fix issue #452 for PyTorch 0.4.0

ljk1072911239 · 2019-06-20T08:27:44Z

/lib/roi_data_layer/roibatchLoader.py
line 52, target_ratio = 1 change to:
target_ratio = np.array(1)

* commit '624608fd2f1fb332ef585062cfe51fabf718430d': Update bbox_transform.py Fix typo in faster_rcnn.py Fix typo in faster_rcnn.py Remove "for training" in get_roidb Fix issue jwyang#452 for PyTorch 0.4.0 two pdb imports is redundant

viniciusarruda · 2020-02-13T13:05:40Z

Solving this definitely, in this line, change:

ratio_large = 2 # largest ratio to preserve.

to:

ratio_large = 2.0 # largest ratio to preserve.

PyTorch is creating a tensor with these values and its type is inferred from the data. A value of 2 will be inferred as int, thus, changing to a floating point value will fix it.
Note that this error only occurs when it falls in this if statement. The below if statement uses ratio = ratio_small where ratio_small = 0.5 is already a floating point value as defined in the beginning of the function.

benedictflorance mentioned this issue Jun 4, 2019

“ Bug fix” #514

Open

benedictflorance added a commit to benedictflorance/faster-rcnn.pytorch that referenced this issue Jun 6, 2019

Fix issue jwyang#452 for PyTorch 0.4.0

03f5f8c

jwyang added a commit that referenced this issue Jun 10, 2019

Merge pull request #573 from benedictflorance/master

56aff1c

Fix issue #452 for PyTorch 0.4.0

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TypeError: can't assign a numpy.int64 to a torch.FloatTensor #452

TypeError: can't assign a numpy.int64 to a torch.FloatTensor #452

goodproj13 commented Feb 28, 2019

EMCP commented Mar 14, 2019

ma-xu commented Apr 12, 2019

goodproj13 commented Apr 12, 2019 via email

ma-xu commented Apr 12, 2019 •

edited

Weizhongjin commented Apr 16, 2019

benedictflorance commented Jun 4, 2019 •

edited

benedictflorance commented Jun 4, 2019 •

edited

EMCP commented Jun 4, 2019

benedictflorance commented Jun 4, 2019

EMCP commented Jun 4, 2019

benedictflorance commented Jun 6, 2019

EMCP commented Jun 8, 2019

benedictflorance commented Jun 9, 2019

ljk1072911239 commented Jun 20, 2019

viniciusarruda commented Feb 13, 2020

TypeError: can't assign a numpy.int64 to a torch.FloatTensor #452

TypeError: can't assign a numpy.int64 to a torch.FloatTensor #452

Comments

goodproj13 commented Feb 28, 2019

EMCP commented Mar 14, 2019

ma-xu commented Apr 12, 2019

goodproj13 commented Apr 12, 2019 via email

ma-xu commented Apr 12, 2019 • edited

Weizhongjin commented Apr 16, 2019

benedictflorance commented Jun 4, 2019 • edited

benedictflorance commented Jun 4, 2019 • edited

EMCP commented Jun 4, 2019

benedictflorance commented Jun 4, 2019

EMCP commented Jun 4, 2019

benedictflorance commented Jun 6, 2019

EMCP commented Jun 8, 2019

benedictflorance commented Jun 9, 2019

ljk1072911239 commented Jun 20, 2019

viniciusarruda commented Feb 13, 2020

ma-xu commented Apr 12, 2019 •

edited

benedictflorance commented Jun 4, 2019 •

edited

benedictflorance commented Jun 4, 2019 •

edited