PyTorch for Numpy users.

PyTorch version of Torch for Numpy users.

Types

Numpy	PyTorch
np.ndarray	torch.Tensor
np.float32	torch.FloatTensor
np.float64	torch.DoubleTensor
np.int8	torch.CharTensor
np.uint8	torch.ByteTensor
np.int16	torch.ShortTensor
np.int32	torch.IntTensor
np.int64	torch.LongTensor

Constructors

Ones and zeros

Numpy	PyTorch
np.empty((2, 3))	torch.Tensor(2, 3)
np.empty_like(x)	x.new(x.size()).type(x.type())
np.eye	torch.eye
np.identity	torch.eye
np.ones	torch.ones
np.ones_like	torch.ones(x.size()).type(x.type())
np.zeros	torch.zeros
np.zeros_like	torch.zeros(x.size()).type(x.type())

From existing data

Numpy	PyTorch
np.array([[1, 2], [3, 4]])	torch.Tensor([[1, 2], [3, 4])
x.copy()	x.clone()
np.fromfile(file)	torch.Tensor(torch.Storage(file))
np.frombuffer
np.fromfunction
np.fromiter
np.fromstring
np.loadtxt
np.concatenate	torch.cat

Numerical ranges

Numpy	PyTorch
np.arange(10)	torch.range(0, 9)
np.arange(2, 3, 0.1)	torch.range(2, 2.9, 10)
np.linspace	torch.linspace
np.logspace	torch.logspace

Building matrices

Numpy	PyTorch
np.diag	torch.diag
np.tril	torch.tril
np.triu	torch.triu

Attributes

Numpy	PyTorch
x.shape	x.size()
x.strides	x.stride()
x.ndim	x.dim()
x.data	x.data()
x.size	x.nelement()
x.dtype	x.type()

Indexing

Numpy	PyTorch
x[0]	x[0]
x[:, 0]	x[:, 0]
x[indices]	x[torch.LongTensor(indices)]
np.take(x, indices)	x[torch.LongTensor(indices)]
x[x != 0]	x[x != 0]

Shape manipulation

Numpy	PyTorch
x.reshape	x.view
x.resize	x.resize_
	x.resize_as_
x.transpose	x.permute
x.flatten()	x.view(-1)
x.squeeze	x.squeeze
x[:, np.newaxis]	x.unsqueeze(1)

Item selection and manipulation

Numpy	PyTorch
np.put
x.repeat
x.tile	x.repeat
np.choose
np.sort	sorted, indices = torch.sort(x, [dim])
np.argsort	sorted, indices = torch.sort(x, [dim])
np.nonzero	torch.nonzero
np.where	torch.nonzero

Calculation

Numpy	PyTorch
x.min	mins, indices = torch.min(x, [dim])
x.argmin	mins, indices = torch.min(x, [dim])
x.max	maxs, indices = torch.max(x, [dim])
x.argmax	maxs, indices = torch.max(x, [dim])
x.clip
x.round	x.round
np.floor(x)	x.floor()
np.ceil(x)	x.ceil()
x.trace	x.trace
x.sum	x.sum
x.cumsum	x.cumsum
x.mean	x.mean
x.std	x.std
x.prod	x.prod
x.cumprod	x.cumprod
x.all	(x == 1).sum() == x.nelement()
x.any	(x == 1).sum() > 0

Arithmetic and comparison operations

Numpy	PyTorch
x.lt	x.lt
x.le	x.le
x.gt	x.gt
x.ge	x.ge
x.eq	x.eq
x.ne	x.ne