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Bookmark or Share- PyTorch: How to get the shape of a Tensor as a list of intP.S.: Note that tensor.shape is an alias to tensor.size(), though tensor.shape is an attribute of the tensor in question whereas tensor.size() is a function. Share Improve this answer
- Difference between numpy.array shape (R, 1) and (R,)Shape n, expresses the shape of a 1D array with n items, and n, 1 the shape of a n-row x 1-column array. (R,) and (R,1) just add (useless) parentheses but still express respectively 1D and 2D array shapes, Parentheses around a tuple force the evaluation order and prevent it to be read as a list of values (e.g. in function calls). This tuple ...
- python - What does .shape [] do in "for i in range (Y.shape [0 ...shape is a tuple that gives you an indication of the number of dimensions in the array. So in your case, since the index value of Y.shape[0] is 0, your are working along the first dimension of your array.
- python - x.shape [0] vs x [0].shape in NumPy - Stack Overflowx is a 2D array, which can also be looked upon as an array of 1D arrays, having 10 rows and 1024 columns.x[0] is the first 1D sub-array which has 1024 elements (there are 10 such 1D sub-arrays in x), and x[0].shape gives the shape of that sub-array, which happens to be a 1-tuple - (1024, ).
- arrays - what does numpy ndarray shape do? - Stack Overflowyourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; And you can get the (number of) dimensions of your array using yourarray.ndim or np.ndim(). (i.e. it gives the n of the ndarray since all arrays in NumPy are just n-dimensional arrays (shortly called as ndarrays))
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