maybe_convert_to_dtype(a, dtype, *[, ...])
|
If a has the same dtype as the given dtype, returns a unmodified. |
device_put(a, device)
|
|
arange(*, start, step, stop, device[, dtype])
|
|
convolution(a, weight, bias, stride, ...)
|
- rtype:
TensorProxy
|
full(shape, fill_value, *, device[, dtype])
|
- rtype:
TensorProxy
|
full_like(a, fill_value, *[, device, dtype])
|
- rtype:
TensorProxy
|
uniform(shape[, minval, maxval])
|
- rtype:
TensorProxy
|
uniform_like(a[, minval, maxval, device, dtype])
|
|
diagonal(a[, offset, dim1, dim2])
|
- rtype:
TensorProxy
|
expand(a, *shape)
|
- rtype:
TensorProxy
|
flatten(a[, start_dim, end_dim])
|
- rtype:
TensorProxy
|
movedim(a, /, source, destination)
|
- rtype:
TensorProxy
|
reshape(a, shape)
|
- rtype:
TensorProxy
|
slice_in_dim(a, start_index, limit_index[, ...])
|
|
squeeze(a, dims)
|
|
transpose(a, permutation)
|
|
stride_order(a[, order])
|
Creates a dense, non-overlapping and strided tensor with the same data and metadata as a. |
take(a, indices, dim)
|
- rtype:
TensorProxy
|
index_add(a, indices, value, dim)
|
- rtype:
TensorProxy
|
take_along_axis(a, /, indices, dim)
|
- rtype:
TensorProxy
|
scatter_add(a, /, indices, value, dim)
|
- rtype:
TensorProxy
|
unsqueeze(a, /, dims)
|
- rtype:
TensorProxy
|
cat(tensors, dim)
|
Concatenates the given sequence of tensors in the given dimension. |
stack(tensors, dim)
|
Concatenates the given sequence of tensors in a new (the given) dimension. |
compute_broadcast_shape(*_shapes)
|
Computes the common shape with the fewest dimensions that all input shapes can be broadcast to. |
matrix_transpose(a)
|
Transposes the last two dimensions of a tensor. |
maybe_broadcast(*args[, ...])
|
Returns tensors with the same shape, possibly broadcasting inputs to the result shape. |
