hogepodge commented on a change in pull request #7917:
URL: https://github.com/apache/tvm/pull/7917#discussion_r638069401
##########
File path: cmake/libs/Libbacktrace.cmake
##########
@@ -14,14 +14,39 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
+
+# On MacOS, the default C compiler (/usr/bin/cc) is actually a small script
that dispatches to a
+# compiler the default SDK (usually
/Library/Developer/CommandLineTools/usr/bin/ or
Review comment:
On MacOS, the default C compiler (/usr/bin/cc) is script that dispatches
to the compiler
provided by the default SDK (usually
/Library/Developer/CommandLineTools/usr/bin/ or
##########
File path: cmake/libs/Libbacktrace.cmake
##########
@@ -14,14 +14,39 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
+
+# On MacOS, the default C compiler (/usr/bin/cc) is actually a small script
that dispatches to a
+# compiler the default SDK (usually
/Library/Developer/CommandLineTools/usr/bin/ or
+#
/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/).
CMake
+# automatically detects what is being dispatched and uses it instead along
with all the flags it
+# needs. CMake makes this second compiler avaliable through the
CMAKE_C_COMPILER variable, but it
+# does not make the necessary flags available. This leads to configuration
errors in libbacktrace
+# because it can't find system libraries. Our solution is to detect if
CMAKE_C_COMPILER lives in
+# /Library or /Applications and switch to the default compiler instead.
Review comment:
Our solution is to detect if CMAKE_C_COMPILER is installed in
##########
File path: docs/deploy/index.rst
##########
@@ -25,12 +25,20 @@ as well as how to integrate it with your project.
.. image:: https://tvm.apache.org/images/release/tvm_flexible.png
+Build the TVM runtime library
+-----------------------------
+
+.. _build-tvm-runtime-on-target-device:
+
Unlike traditional deep learning frameworks. TVM stack is divided into two
major components:
-- TVM compiler, which does all the compilation and optimizations
+- TVM compiler, which does all the compilation and optimizations of the model
- TVM runtime, which runs on the target devices.
-In order to integrate the compiled module, we **do not** need to build entire
TVM on the target device. You only need to build the TVM compiler stack on your
desktop and use that to cross-compile modules that are deployed on the target
device.
+In order to integrate the compiled module, we **do not** need to build entire
+TVM on the target device. You only need to build the TVM compiler stack on
your
Review comment:
we **do not** need to build the entire TVM project on the target device.
Rather, we only need to build the TVM compiler stack on a host device and use
that to cross-compile modules that can be deployed to a target device.
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