Webother (Tensor or Scalar) – value (if other is a scalar) or values selected at indices where condition is False. Keyword Arguments: out (Tensor, optional) – the output tensor. Returns: A tensor of shape equal to the broadcasted shape of condition, input, other. Return type: Tensor. Example: WebDec 3, 2024 · The tensor () method. This method returns a tensor when data is passed to it. data can be a scalar, tuple, a list or a NumPy array. In the above example, a NumPy array that was created using np.arange () was passed to the tensor () method, resulting in a 1-D tensor. We can create a multi-dimensional tensor by passing a tuple of tuples, a list ...
Check if at least one element in tensor is nonzero
WebJan 24, 2024 · Default: torch_strided. ( torch.device, optional) the desired device of returned tensor. Default: if NULL, uses the current device for the default tensor type (see torch_set_default_tensor_type ). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. (bool, optional) If autograd should record … WebDec 15, 2024 · TensorFlow code, and tf.keras models will transparently run on a single GPU with no code changes required.. Note: Use tf.config.list_physical_devices('GPU') to confirm that TensorFlow is using the GPU. The simplest way to run on multiple GPUs, on one or many machines, is using Distribution Strategies.. This guide is for users who have … it\u0027s the way you love me it\u0027s perpetual bliss
How to check if a tensor is empty in TensorFlow #38976
WebThe atomic strain increment tensor _ is then found from the deformation gradient D by subtracting out the rigid-body rotations in the usual way. Of this strain tensor, two scalar invariants are of special interest, the local dilatation e, and the local deviatoric normal distortion 6, which are defined as: = Tr _. WebApr 8, 2024 · As you can see, the view() method has changed the size of the tensor to torch.Size([4, 1]), with 4 rows and 1 column.. While the number of elements in a tensor object should remain constant after view() method is applied, you can use -1 (such as reshaped_tensor.view(-1, 1)) to reshape a dynamic-sized tensor.. Converting Numpy … Webtorch.all(input, dim, keepdim=False, *, out=None) → Tensor. For each row of input in the given dimension dim , returns True if all elements in the row evaluate to True and False otherwise. If keepdim is True, the output tensor is of the same size as input except in the dimension dim where it is of size 1. it\u0027s the way to go