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enable WEBGPU tests with buffer limit (#11489)

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TestSample still fails?
This commit is contained in:
chenyu
2025-08-03 13:02:44 -07:00
committed by GitHub
parent 8f374ee1f7
commit dbc7807c61
4 changed files with 4 additions and 16 deletions
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5
test/test_ops.py
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@@ -2,7 +2,7 @@ import time, math, unittest, functools, platform, warnings
import numpy as np
from typing import List, Callable
import torch
from tinygrad.helpers import getenv, IMAGE, DEBUG, CI, Context, TRANSCENDENTAL, OSX, AMD_LLVM
from tinygrad.helpers import getenv, IMAGE, DEBUG, CI, Context, TRANSCENDENTAL, AMD_LLVM
from tinygrad import Tensor, Device, dtypes
from tinygrad.tensor import _to_np_dtype
from tinygrad.device import is_dtype_supported
@@ -2682,7 +2682,6 @@ class TestOps(unittest.TestCase):
i, j, k, o, p = [Tensor(tor.detach().cpu().numpy().astype(np.int32), requires_grad=False) for tor in [a,b,c,d,e]]
return a,b,c,d,e,i,j,k,o,p
@unittest.skipIf(Device.DEFAULT == "WEBGPU", "WEBGPU can only run kernels with up to 10 buffers")
def test_slice_fancy_indexing_no_dim_collapse(self):
a,b,c,d,e,i,j,k,o,p = self._get_index_randoms()
# no dim collapse from int or dim injection from None
@@ -2734,7 +2733,6 @@ class TestOps(unittest.TestCase):
helper_test_op([(2,3)], lambda x: x[torch.tensor([[0,1,-1],[-1,-2,0]]), torch.tensor([2,1,-1])],
lambda x: x[Tensor([[0,1,-1],[-1,-2,0]]), Tensor([2,1,-1])])
@unittest.skipIf(Device.DEFAULT == "WEBGPU", "WEBGPU can only run kernels with up to 10 buffers")
def test_slice_fancy_indexing_list_indices(self):
a,b,c,d,e,i,j,k,o,p = self._get_index_randoms()
helper_test_op([(2,5,6,5,3,4)], lambda x: x[[[0]]], lambda x: x[[[0]]])
@@ -2754,7 +2752,6 @@ class TestOps(unittest.TestCase):
helper_test_op([(2,5,6,5,3,4)], lambda x: x[a,((2,),(1,),(0,)),c,(2,1,0)], lambda x: x[i,((2,),(1,),(0,)),k,(2,1,0)])
helper_test_op([(2,5,6,5,3,4)], lambda x: x[1,(2,1,0),None,c,(2,1,0),e], lambda x: x[1,(2,1,0),None,k,(2,1,0),p])
@unittest.skipIf(Device.DEFAULT == "WEBGPU" and not OSX, "WEBGPU Vulkan can only run kernels with up to 10 buffers")
def test_slice_fancy_indexing_list_with_tensors(self):
a,b,c,d,e,i,j,k,o,p = self._get_index_randoms()
helper_test_op([(2,5,6,5,3,4)], lambda x: x[[a]], lambda x: x[[i]])