Fix tutorial 18584

LICENSE

@@ -1,6 +1,6 @@
                                  Apache License
                            Version 2.0, January 2004
-                        http://www.apache.org/licenses/
+                        https://www.apache.org/licenses/
 
    TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
 
@@ -192,7 +192,7 @@
    you may not use this file except in compliance with the License.
    You may obtain a copy of the License at
 
-       http://www.apache.org/licenses/LICENSE-2.0
+       https://www.apache.org/licenses/LICENSE-2.0
 
    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,

README.md

@@ -6,7 +6,7 @@
 <!--- "License"); you may not use this file except in compliance -->
 <!--- with the License.  You may obtain a copy of the License at -->
 
-<!---   http://www.apache.org/licenses/LICENSE-2.0 -->
+<!---   https://www.apache.org/licenses/LICENSE-2.0 -->
 
 <!--- Unless required by applicable law or agreed to in writing, -->
 <!--- software distributed under the License is distributed on an -->

docs/how_to/tutorials/customize_opt.py

@@ -1,4 +1,4 @@
-# Licensed to the Apache Software Foundation (ASF) under one
+# Licensed to the Apache Software Foundation (ASF) under one
 # or more contributor license agreements.  See the NOTICE file
 # distributed with this work for additional information
 # regarding copyright ownership.  The ASF licenses this file
@@ -55,6 +55,12 @@
 from tvm import IRModule, relax
 from tvm.relax.frontend import nn
 
+# Note: This tutorial requires TVM to be built with CUDA support.
+# If you encounter 'No module named ''tvm_ffi''' error,
+# you need to build TVM from source with CUDA enabled.
+# Build instructions: https://tvm.apache.org/docs/install/from_source.html
+
+
 ######################################################################
 # Composable IRModule Optimization
 # --------------------------------
@@ -103,9 +109,17 @@ def forward(self, x):
 
 
 # Import cublas pattern
-import tvm.relax.backend.cuda.cublas as _cublas
-
-
+try:
+    import tvm.relax.backend.cuda.cublas as _cublas
+except ImportError as e:
+    if "tvm_ffi" in str(e):
+        import sys
+        print("Error: TVM needs to be built with CUDA support.", file=sys.stderr)
+        print("Please build TVM from source with CUDA enabled.", file=sys.stderr)
+        print("See: https://tvm.apache.org/docs/install/from_source.html", file=sys.stderr)
+        sys.exit(1)
+    else:
+        raise
 # Define a new pass for CUBLAS dispatch
 @tvm.transform.module_pass(opt_level=0, name="CublasDispatch")
 class CublasDispatch:
@@ -223,3 +237,6 @@ def transform_module(self, mod: IRModule, _ctx: tvm.transform.PassContext) -> IR
 # of the computation graph. The flexibility of the optimization pipeline enables us to quickly
 # iterate the optimization and improve the performance of the model.
 #
+
+
+