16.09.2018 · tensor = tf.multiply (ndarray, 42) tensor.numpy () # throw AttributeError: 'Tensor' object has no attribute 'numpy'. I use anaconda 3 with tensorflow 1.14.0. I upgraded tensorflow with the command below. conda update tensorflow. now tensorflow is 2.0.0, issue fixed. Try this to see if it resolves your issue.
31.01.2018 · Howdy folks relatively new to Python, numpy, PyTorch (come from C++ and Matlab). I am using CUDA 9.1, Python 3.6, Torch 0.3.0.post4, running on Ubuntu 16.04 LTS and I am starting off as follows: python train.py --arch segnet --dataset pa...
Jun 01, 2021 · The elements in img_tensor can either have values in [0, 1] (float32) or [0, 255] (uint8). Convert Tensor to a NumPy array using numpy (). AttributeError: 'Tensor' object has no attribute 'ndim' You can get around this easily by letting all PyTorch tensors know how to respond to ndim like this: torch .
Oct 07, 2019 · AttributeError: 'list' object has no attribute 'dim' when predicting in pytorch ... AttributeError: 'list' object has no attribute 'dim' ... while a PyTorch tensor is ...
Feb 22, 2020 · AttributeError: 'Tensor' object has no attribute 'numpy' Describe the expected behavior I'd like to be able to access the numpy() property of arguments passed to a mapping function passed to tf.data.Dataset.map
22.02.2020 · @nscotto, You can convert tensor into numpy array using tensor.numpy(), But you can't do the same in case of MapDataset.In the example code you have given, the x in the transformer function is MapDataset and not Tensor. I have seen similar issue #30035 and also you can refer to this function which I think will solve your problem. Also, if you have any doubts …
Jul 05, 2021 · I am trying to perform random cropping on an image. Here is my code. I tried following the examples given over here but got stuck. import numpy as np from sklearn.datasets import load_sample_images import matplotlib.pyplot as plt import torch import torch.nn as nn def random_crop(imgs, out=84): imgs = torch.tensor(84) transforms = torch.nn.Sequential( imgs.RandomCrop(84), ) imgs = transforms ...
05.05.2020 · There is add_scalar (singular, so no s at the end) that would seem to work roughly like you want (except for the .eval() in there). You are calling add_scalars (plural) which takes name/value pairs in form of a dict if you want to add several.. Best regards. Thomas
13.09.2020 · Problem Description I am trying to write a custom loss function in TensorFlow 2.3.0. To calculate the loss, I need the y_pred parameter to be converted to a numpy array. However, I can't find a way...
May 05, 2020 · There is add_scalar (singular, so no s at the end) that would seem to work roughly like you want (except for the .eval() in there). You are calling add_scalars (plural) which takes name/value pairs in form of a dict if you want to add several.
This answer has been awarded bounties worth 25 reputation by Community. Show activity on this post. The Python binary that you are running does not have torch installed. It does have a directory named torch on the module search path, and it is treated as a namespace package: $ pwd /some/path $ python3 -c 'import torch; print (torch); print ...
22.07.2021 · Is it possible that perhaps, that someone has proposed nn.Identity? Does it not work with Identity, but with your implementation? Because it’s actually the same thing.
It seems you are trying to pass a numpy array to F.nll_loss , while a PyTorch tensor is expected. I'm not sure how y_pred is calculated, but note that using ...
08.05.2020 · The cuda() method is defined for tensors, while it seems you are calling it on a numpy array. Try to transform the numpy array to a tensor before calling tensor.cuda() via: tensor = torch.from_numpy(array).
Sep 17, 2018 · tensor = tf.multiply (ndarray, 42) tensor.numpy () # throw AttributeError: 'Tensor' object has no attribute 'numpy'. I use anaconda 3 with tensorflow 1.14.0. I upgraded tensorflow with the command below. conda update tensorflow. now tensorflow is 2.0.0, issue fixed. Try this to see if it resolves your issue.
05.07.2021 · I am trying to perform random cropping on an image. Here is my code. I tried following the examples given over here but got stuck. import numpy as np from sklearn.datasets import load_sample_images import matplotlib.pyplot as plt import torch import torch.nn as nn def random_crop(imgs, out=84): imgs = torch.tensor(84) transforms = torch.nn.Sequential( …