Restore "pytest.mark.gpu" for RELAX tests

tests/python/relax/test_codegen_cublas.py

@@ -36,14 +36,7 @@ def reset_seed():
     np.random.seed(0)
 
 
-has_cublas = tvm.get_global_func("relax.ext.cublas", True)
-
-cublas_enabled = pytest.mark.skipif(
-    not has_cublas,
-    reason="CUBLAS not enabled.",
-)
-
-pytestmark = [cublas_enabled]
+pytestmark = tvm.testing.requires_cublas.marks()
 
 
 def build_and_run(mod, inputs_np, target, legalize=False, cuda_graph=False):
@@ -231,6 +224,7 @@ def test_matmul_igemm_offload(
     tvm.testing.assert_allclose(out, ref, rtol=1e-2, atol=1e-2)
 
 
+@tvm.testing.requires_cuda_compute_version(9)
 @pytest.mark.skipif(ml_dtypes is None, reason="requires ml_dtypes to be installed")
 @pytest.mark.parametrize(
     "x_shape, y_shape, transpose_y, out_dtype",

tests/python/relax/test_codegen_cudnn.py

@@ -34,14 +34,7 @@ def reset_seed():
     np.random.seed(0)
 
 
-has_cudnn = tvm.get_global_func("relax.ext.cudnn", True)
-
-cudnn_enabled = pytest.mark.skipif(
-    not has_cudnn,
-    reason="cuDNN not enabled.",
-)
-
-pytestmark = [cudnn_enabled]
+pytestmark = tvm.testing.requires_cudnn.marks()
 
 
 _activation_table = {

tests/python/relax/test_codegen_cutlass.py

@@ -75,14 +75,7 @@ def main(
         return conv2
 
 
-has_cutlass = tvm.get_global_func("relax.ext.cutlass", True)
-
-cutlass_enabled = pytest.mark.skipif(
-    not has_cutlass,
-    reason="CUTLASS not enabled.",
-)
-
-pytestmark = [cutlass_enabled]
+pytestmark = tvm.testing.requires_cutlass.marks()
 
 
 def build_and_run(mod, inputs_np, target, legalize=True, cuda_graph=False):

tests/python/relax/test_codegen_tensorrt.py

@@ -43,13 +43,22 @@ def main(
 
 
 has_tensorrt = tvm.get_global_func("relax.ext.tensorrt", True)
+env_checker_runtime = tvm.get_global_func("relax.is_tensorrt_runtime_enabled", True)
 
-tensorrt_enabled = pytest.mark.skipif(
+requires_tensorrt_codegen = pytest.mark.skipif(
     not has_tensorrt,
     reason="TENSORRT not enabled.",
 )
 
-pytestmark = [tensorrt_enabled]
+requires_tensorrt_runtime = pytest.mark.skipif(
+    not env_checker_runtime or not env_checker_runtime(),
+    reason="TensorRT runtime not available",
+)
+
+pytestmark = [
+    requires_tensorrt_codegen,
+    requires_tensorrt_runtime,
+] + tvm.testing.requires_cuda.marks()
 
 
 def build_and_run(mod, inputs_np, target, legalize=False):

tests/python/relax/test_contrib_vllm.py

@@ -32,7 +32,7 @@
     reason="VLLM not enabled.",
 )
 
-pytestmark = [vllm_enabled]
+pytestmark = [vllm_enabled] + tvm.testing.requires_cuda.marks()
 
 
 def build_and_run(mod, inputs_np, target, legalize=True):

tests/python/relax/test_transform_codegen_pass.py

@@ -30,17 +30,17 @@
 env_checker_codegen = tvm.get_global_func("relax.ext.tensorrt", True)
 env_checker_runtime = tvm.get_global_func("relax.is_tensorrt_runtime_enabled", True)
 
-has_tensorrt_codegen = pytest.mark.skipif(
+requires_tensorrt_codegen = pytest.mark.skipif(
     not env_checker_codegen,
     reason="TensorRT codegen not available",
 )
-has_tensorrt_runtime = pytest.mark.skipif(
+requires_tensorrt_runtime = pytest.mark.skipif(
     not env_checker_runtime or not env_checker_runtime(),
     reason="TensorRT runtime not available",
 )
 
 # Global variable in pytest that applies markers to all tests.
-pytestmark = [has_tensorrt_codegen, has_tensorrt_runtime]
+pytestmark = [requires_tensorrt_codegen] + tvm.testing.requires_cuda.marks()
 
 # Target gpu
 target_str = "nvidia/nvidia-t4"
@@ -117,6 +117,7 @@ def setup_test():
 
 
 @tvm.testing.requires_gpu
+@requires_tensorrt_runtime
 def test_tensorrt_only(entry_func_name):
     mod, inputs, expected = setup_test()
 
@@ -146,6 +147,7 @@ def test_tensorrt_only(entry_func_name):
 
 
 @tvm.testing.requires_gpu
+@requires_tensorrt_runtime
 def test_mix_use_tensorrt_and_tvm():
     mod, inputs, expected = setup_test()
 
@@ -367,7 +369,7 @@ def test_no_op_for_call_to_tir():
     @tvm.script.ir_module
     class Before:
         @R.function
-        def main(x: R.Tensor):
+        def main(x: R.Tensor([4], "int64")):
             R.func_attr({"relax.force_pure": True})
             _ = Before.shape_func(x)
             return x