Align with PyTorch test_ops case suites (#50)

Signed-off-by: Feng Yuan <[email protected]> Co-authored-by: Yutao Xu <[email protected]> Co-authored-by: chuanqiw <[email protected]>
intel · Mar 25, 2024 · e755b1e · e755b1e
1 parent 9ce96cf
commit e755b1e
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Showing 12 changed files with 424 additions and 33 deletions.
diff --git a/.github/ci_commit_pins/pytorch.txt b/.github/ci_commit_pins/pytorch.txt
diff --git a/.github/workflows/pull.yml b/.github/workflows/pull.yml
@@ -26,8 +26,8 @@ jobs:
         run: |
           pwd
           cd ../ && rm -rf pytorch
-          git clone https://github.com/pytorch/pytorch
-          cd pytorch && git checkout `cat ../torch-xpu-ops/.github/ci_commit_pins/pytorch.txt` && git submodule sync && git submodule update --init --recursive
+          git clone -b nightly https://github.com/pytorch/pytorch
+          cd pytorch && git log -n 1 && git submodule sync && git submodule update --init --recursive
           rm -rf third_party/torch-xpu-ops && cp -r ../torch-xpu-ops third_party/
           # Workaround for torch-xpu-ops ci test
           sed -i "s/checkout --quiet \${TORCH_XPU_OPS_COMMIT}/log -n 1/g" caffe2/CMakeLists.txt
@@ -52,11 +52,12 @@ jobs:
           cd examples
           timeout 8000 pytest -v 2>&1 | tee torch_xpu_ops_example.log
       - name: Run XPU OP UT
-        if: ${{ hashFiles('test/python/') != '' }}
+        if: ${{ hashFiles('test/xpu/') != '' }}
         run: |
           source /opt/intel/oneapi/compiler/latest/env/vars.sh
           source activate xpu_op_${ZE_AFFINITY_MASK}
-          cd test/python
+          export PYTORCH_ENABLE_XPU_FALLBACK=1
+          cd test/xpu
           timeout 8000 pytest -v 2>&1 | tee torch_xpu_ops_ut.log
       - name: Run Torch XPU UT
         run: |

diff --git a/test/python/examples/test_binary.py → examples/test_binary.py b/test/python/examples/test_binary.py → examples/test_binary.py
@@ -59,7 +59,7 @@ def test_div_int(self, dtype=torch.float):
         c_cpu = a_cpu / b_cpu
         self.assertEqual(c_cpu.dtype, c_xpu.dtype) # assume float
         self.assertEqual(c_cpu, c_xpu.to(cpu_device))
-    
+
     def test_binary_div_channels_last(self, dtype=torch.float):
         shapes = [
             (1, 2, 3, 4),
@@ -222,7 +222,7 @@ def test_binary_div_channels_last(self, dtype=torch.float):
                 self.assertEqual(
                     a_xpu.is_contiguous(memory_format=torch.channels_last), False
                 )
-    
+
     def test_pow(self, dtype=torch.float):
         x_cpu = torch.tensor(([2.5, 3.1, 1.3]), dtype=torch.float, device=cpu_device)
         x_xpu = torch.tensor(
@@ -235,7 +235,7 @@ def test_pow(self, dtype=torch.float):
         self.assertEqual(torch.pow(x_cpu, y_cpu), torch.pow(x_xpu, y_xpu).cpu())
         self.assertEqual(x_cpu.pow(y_cpu), x_xpu.pow(y_xpu).cpu())
         self.assertEqual(x_cpu.pow_(y_cpu), x_xpu.pow_(y_xpu).cpu())
-    
+
     def test_binary_op(self, dtype=torch.float):
         x_cpu = torch.randn(5)
 

diff --git a/test/python/examples/test_compare.py → examples/test_compare.py b/test/python/examples/test_compare.py → examples/test_compare.py
@@ -26,21 +26,21 @@ def _test_compare_fn(self, fn, dtype):
         y_xpu.zero_()
         fn(x1_xpu, x2_xpu, out=y_xpu)
         self.assertEqual(y_xpu.cpu(), y)
-    
+
     def test_eq(self, dtype=torch.float):
         self._test_compare_fn(torch.eq, dtype)
-    
+
     def test_ne(self, dtype=torch.float):
         self._test_compare_fn(torch.ne, dtype)
-    
+
     def test_lt(self, dtype=torch.float):
         self._test_compare_fn(torch.lt, dtype)
-    
+
     def test_le(self, dtype=torch.float):
         self._test_compare_fn(torch.le, dtype)
-    
+
     def test_gt(self, dtype=torch.float):
         self._test_compare_fn(torch.gt, dtype)
-    
+
     def test_ge(self, dtype=torch.float):
         self._test_compare_fn(torch.ge, dtype)
diff --git a/test/python/examples/test_copy.py → examples/test_copy.py b/test/python/examples/test_copy.py → examples/test_copy.py
diff --git a/test/python/examples/test_loops.py → examples/test_loops.py b/test/python/examples/test_loops.py → examples/test_loops.py
@@ -34,13 +34,13 @@ def _test_loops(self, dtype=torch.float):
             c = a + b + 1
             c_xpu = a_xpu + b_xpu + 1
             self.assertEqual(c, c_xpu.cpu())
-    
+
     def test_loops_float(self):
         self._test_loops(torch.float)
-    
+
     def test_loops_half(self):
         self._test_loops(torch.half)
-    
+
     def test_loops_bfloat16(self):
         self._test_loops(torch.bfloat16)
 

diff --git a/test/python/examples/test_rand.py → examples/test_rand.py b/test/python/examples/test_rand.py → examples/test_rand.py
@@ -19,7 +19,7 @@ def test_distribution_normal(self, dtype=torch.float):
         torch.normal(mean=-3.0, std=1.2, size=(10000,), device=xpu_device, dtype=dtype, out=x_xpu)
         self.assertEqual(x_xpu.cpu().mean(), -3.0, rtol=tol, atol=tol)
         self.assertEqual(x_xpu.cpu().std(), 1.2, rtol=tol, atol=tol)
-    
+
     def test_distribution_uniform(self, dtype=torch.float):
         tol = 1e-2
         x_xpu = torch.tensor(list(range(10000)), device=xpu_device, dtype=dtype)

diff --git a/test/python/examples/test_resize.py → examples/test_resize.py b/test/python/examples/test_resize.py → examples/test_resize.py
@@ -28,14 +28,14 @@ def test_view(self, dtype=torch.float):
         assert b_xpu.shape[2] == 2
 
         self.assertEqual(c_cpu, b_xpu.to(cpu_device))
-    
+
     def test_view_as_real(self, dtype=torch.cfloat):
         a_cpu = torch.randn(2, 3, 4, dtype=dtype)
         a_xpu = a_cpu.to(xpu_device)
         b_cpu = torch.view_as_real(a_cpu)
         b_xpu = torch.view_as_real(a_xpu)
         self.assertEqual(b_cpu, b_xpu.to(cpu_device))
-    
+
     def test_view_as_complex(self, dtype=torch.float):
         a_cpu = torch.randn(109, 2, dtype=dtype)
         a_xpu = a_cpu.to(xpu_device)

diff --git a/test/python/examples/test_tensor_factory.py → examples/test_tensor_factory.py b/test/python/examples/test_tensor_factory.py → examples/test_tensor_factory.py
diff --git a/test/python/examples/test_unary.py → examples/test_unary.py b/test/python/examples/test_unary.py → examples/test_unary.py
@@ -14,7 +14,7 @@ class Dtypes(object):
     def __init__(self, include_dtypes, exclude_dtypes=[]):
         self.include_dtypes = include_dtypes
         self.exclude_dtypes = exclude_dtypes
-    
+
     def __call__(self, fn):
         def fn_out(*args, **kwargs):
             for dtype in self.include_dtypes:
@@ -38,39 +38,39 @@ def _test_unary_out_ops(self, fn_str, dtype):
         d_cpu = eval(f"torch.{fn_str}(a_cpu, out=c_cpu)")
         d_xpu = eval(f"torch.{fn_str}(a_xpu, out=c_xpu)")
         self.assertEqual(c_cpu, c_xpu.cpu(), atol=1e-4, rtol=1e-4)
-    
+
     @Dtypes(floating_types)
     def test_abs_out(self, dtype):
         self._test_unary_out_ops('abs', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_sin_out(self, dtype):
         self._test_unary_out_ops('sin', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_cos_out(self, dtype):
         self._test_unary_out_ops('cos', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_log_out(self, dtype):
         self._test_unary_out_ops('log', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_sqrt_out(self, dtype):
         self._test_unary_out_ops('sqrt', dtype)
 
     @Dtypes(floating_and_complex_types)
     def test_rsqrt_out(self, dtype):
         self._test_unary_out_ops('rsqrt', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_tanh_out(self, dtype):
         self._test_unary_out_ops('tanh', dtype)
-    
+
     @Dtypes(all_basic_and_complex_types, [torch.bool])
     def test_neg_out(self, dtype):
         self._test_unary_out_ops('neg', dtype)
-    
+
     @Dtypes(floating_and_complex_types)
     def test_reciprocal_out(self, dtype):
         self._test_unary_out_ops('reciprocal', dtype)
diff --git a/src/aten/BinaryOps.cpp b/src/aten/BinaryOps.cpp
@@ -210,23 +210,23 @@ Tensor XPUNativeFunctions::rsub(
     const Tensor& self,
     const Tensor& other,
     const Scalar& alpha) {
-  return XPUNativeFunctions::sub(self, other, alpha);
+  return XPUNativeFunctions::sub(other, self, alpha);
 }
 
 Tensor& XPUNativeFunctions::rsub_out(
     const Tensor& self,
     const Tensor& other,
     const Scalar& alpha,
     Tensor& out) {
-  return XPUNativeFunctions::sub_out(self, other, alpha, out);
+  return XPUNativeFunctions::sub_out(other, self, alpha, out);
 }
 
 Tensor XPUNativeFunctions::rsub(
     const Tensor& self,
     const Scalar& other,
     const Scalar& alpha) {
   return XPUNativeFunctions::sub(
-      self, native::wrapped_scalar_tensor(other), alpha);
+      native::wrapped_scalar_tensor(other), self, alpha);
 }
 
 Tensor& XPUNativeFunctions::rsub_out(
@@ -235,7 +235,7 @@ Tensor& XPUNativeFunctions::rsub_out(
     const Scalar& alpha,
     Tensor& out) {
   return XPUNativeFunctions::sub_out(
-      self, native::wrapped_scalar_tensor(other), alpha, out);
+      native::wrapped_scalar_tensor(other), self, alpha, out);
 }
 
 Tensor XPUNativeFunctions::remainder(const Tensor& self, const Tensor& other) {