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Revert "[CUDNN] Remove defunct cuDNN V8 API build flag (#120006)"

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This reverts commit ee4cafa098ede2d9546016223cbc1a522ea3630a.

Reverted https://github.com/pytorch/pytorch/pull/120006 on behalf of https://github.com/huydhn due to Sorry for reverting your change but it is failing ROCm jobs in trunk ee4cafa098 ([comment](https://github.com/pytorch/pytorch/pull/120006#issuecomment-2098849813))
This commit is contained in:
PyTorch MergeBot
2024-05-07 16:28:04 +00:00
parent 848fce35b5
commit 1b396d69cb
3 changed files with 28 additions and 11 deletions
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37
test/quantization/core/test_quantized_op.py
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@ -21,7 +21,6 @@ from hypothesis import strategies as st
import torch.testing._internal.hypothesis_utils as hu
hu.assert_deadline_disabled()
from torch.testing._internal.common_cuda import SM80OrLater
from torch.testing._internal.common_utils import TestCase
from torch.testing._internal.common_utils import IS_PPC, TEST_WITH_UBSAN, IS_MACOS, BUILD_WITH_CAFFE2, IS_SANDCASTLE
from torch.testing._internal.common_quantization import skipIfNoFBGEMM, skipIfNoQNNPACK, skipIfNoONEDNN
@ -32,7 +31,7 @@ from torch.testing._internal.common_quantized import (
qengine_is_onednn,
)
from torch.ao.quantization import PerChannelMinMaxObserver
from torch.testing._internal.common_cuda import TEST_CUDNN, TEST_CUDNN_VERSION, TEST_CUDA
from torch.testing._internal.common_cuda import TEST_CUDNN, TEST_CUDA
from torch.testing._internal.optests import opcheck
import torch.backends.xnnpack
@ -906,7 +905,9 @@ class TestQuantizedOps(TestCase):
"""Tests the correctness of the cudnn add and add_relu op
(Similar to test_qadd_relu_different_qparams, will probably merge in the future)"""
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the test_qadd_relu_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qadd_relu_cudnn(self):
dtype = torch.qint8
add_relu = torch.ops.quantized.add_relu
@ -939,7 +940,9 @@ class TestQuantizedOps(TestCase):
"""Tests the correctness of the cudnn add and add_relu op for nhwc format"""
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the test_qadd_relu_cudnn_nhwc op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qadd_relu_cudnn_nhwc(self):
dtype = torch.qint8
add_relu = torch.ops.quantized.add_relu
@ -1376,7 +1379,7 @@ class TestQuantizedOps(TestCase):
self.assertEqual(a_ref, a_hat.dequantize(),
msg="ops.quantized.max_pool1d results are off")
# TODO: merge this test with test_max_pool2d
# TODO: merge this test with test_max_pool2d when USE_EXPERIMENTAL_CUDNN_V8_API flag is enabled in CI
"""Tests 2D cudnn max pool operation on quantized tensors."""
@given(X=hu.tensor(shapes=hu.array_shapes(min_dims=3, max_dims=4,
min_side=1, max_side=10),
@ -1391,7 +1394,9 @@ class TestQuantizedOps(TestCase):
padding=st.integers(0, 2),
ceil_mode=st.booleans())
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(TEST_CUDNN_VERSION <= 90100, "cuDNN maxpool2d mishandles -128 before v90100")
@unittest.skip("Local only - currently the qconv2d_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_max_pool2d_cudnn(self, X, kernel, stride, dilation, padding, ceil_mode):
X, (scale, zero_point, torch_type) = X
assume(kernel // 2 >= padding) # Kernel cannot be overhanging!
@ -4045,7 +4050,9 @@ class TestQuantizedLinear(TestCase):
use_channelwise=st.sampled_from([False])) # channelwise currently not supported for qlinear cudnn
@skipIfNoFBGEMM
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the qlinear_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
# TODO: check with yang regarding CUDNN flags
def test_qlinear_cudnn(self, batch_size, input_channels, output_channels, use_bias,
use_relu, use_multi_dim_input, use_channelwise):
@ -5420,7 +5427,9 @@ class TestQuantizedConv(TestCase):
use_channelwise=st.sampled_from([False]))
@skipIfNoFBGEMM
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the qconv2d_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qconv2d_cudnn(
self,
batch_size,
@ -5501,7 +5510,9 @@ class TestQuantizedConv(TestCase):
use_channelwise=st.sampled_from([False]))
@skipIfNoFBGEMM
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the qconv2d_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qconv2d_relu_cudnn(
self,
batch_size,
@ -6234,7 +6245,9 @@ class TestQuantizedConv(TestCase):
use_channelwise=st.sampled_from([False]))
@skipIfNoFBGEMM
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the qconv1d_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qconv1d_cudnn(
self,
batch_size,
@ -6306,7 +6319,9 @@ class TestQuantizedConv(TestCase):
use_channelwise=st.sampled_from([False]))
@skipIfNoFBGEMM
@unittest.skipIf(not TEST_CUDNN, "cudnn is not enabled.")
@unittest.skipIf(not SM80OrLater, "requires sm80 or later.")
@unittest.skip("Local only - currently the qconv1d_cudnn op is bulid "
"with USE_EXPERIMENTAL_CUDNN_V8_API, we can enable the test "
"after it is built by default")
def test_qconv1d_relu_cudnn(
self,
batch_size,