PyTorch often receives requests for NumPy-like functionality. This issue is a "rollup" of these requests. It will be continue to be updated with additional requests and helpful links for implementing them.

Newer contributors, checkout the Wiki and read the Contribution Guide for help getting started.

If one of these issues requires additional discussion then, to avoid cluttering this rollup, please create a new issue titled “Implementing [Request]”, label it with “module: numpy”, and start the more focused discussion there.

Functions (Updated for the PyTorch 1.8 release):

• divmod (reserved for onboarding)
• frexp
• dsplit, hsplit, and vsplit
• block
• diag_indices
• take_along_axis
• histogram
• histogram_bin_edges
• isin(Function request: np.isin #3025) (reserved for bootcamp)
• let clamp accept tensors (Support clamp() with tensor min and max #2793)
• corrcoef, requested in Function request: np.corrcoef #1254

Completed Functions

• diff, implemented by @soulitzer in Implement np.diff for single order differences #50569
• any and all supporting all dtypes, implemented by @kshitij12345 in [numpy] torch.{all, any} : Extend Dtype Support #44790
• broadcast_to, implemented by @RockingJavaBean in Implementing NumPy-like function torch.broadcast_to #48997
• xlogy, see original issue Implement torch.xlogy #22656, implemented by @kshitij12345 in [numpy] Add torch.xlogy #48777
• floatpower, implemented by @Kiyosora in Implement NumPy-like function torch.float_power() #44937
• msort, added by @Kiyosora in Implement NumPy-like function torch.msort() #48440
• ldexp, added by @ranman in Add basic ldexp operator for numpy compatibility #45370
• column_stack and row_stack, implemented by @RockingJavaBean in implement NumPy-like functionality column_stack, row_stack #46313
• kron, implemented by @IvanYashchuk in Added Kronecker product of tensors (torch.kron) #45358
• ravel, implemented by @ejguan in Implement ravel #46098
• swapaxes, implemented by @kshitij12345 in Add torch.swapdims and torch.swapaxes #46041
• tile, implemented by @arbfay in An implementation of torch.tile as requested in pytorch/pytorch#38349 #47974
• copysign, implemented by @ejguan in Implement copysign #46396
• maximum, minimum implemented by @RockingJavaBean in implement NumPy-like functionality maximum, minimum #42579
• dstack, hstack, vstack, implemented by @muthuArivoli in Implement hstack, vstack, dstack #42799
• arcosh, arcsinh, arctanh, implemented by @krshrimali in Add arcosh, arcsinh and arctanh to unary ops #38388
• atleast_1d, atleast_2d, atleast_3d, implemented by @kshitij12345 in Add torch.atleast_{1d/2d/3d} #41317
• deg2rad, rad2deg, implemented by @aayn in Implement rad2deg, deg2rad #38852
• fliplr, flipud, implemented by @kshitij12345 in Add torch.flip{lr, ud} #38599
• isneginf, isposinf, implemented by @RockingJavaBean in implement numpy-like functionality isposinf, isneginf #41588
• isreal, implemented by @Justin-Huber in torch.isreal #41298
• logaddexp, logaddexp2, implemented by @cloudhan in Implement logaddexp #38384
• signbit, implemented by @Kiyosora in Implementing NumPy-like function torch.signbit() #41589
• count_nonzero, implemented by @kshitij12345 in Add torch.count_nonzero #39992
• gcd, lcm, implemented by @aayn in Implement gcd, lcm #40651
• moveaxis (Add moveaxis function #36048), implemented by @kshitij12345 in Add torch.movedim #41480 (as movedim)
• quantile, implemented by @heitorschueroff in Initial implementation of quantile operator #39417
• nansum, implemented by @kshitij12345 in Add torch.nansum #38628
• hypot ([feature request] torch.hypot #22764), implemented by @muthuArivoli in Implement hypot #42291
• nextafter, implemented by @muthuArivoli in Implement torch.nextafter #42580

cc @ezyang @gchanan @zou3519 @bdhirsh @jbschlosser @anjali411 @mruberry @rgommers @heitorschueroff
cc @aayn @n-gao