(dbt-env) C:\dbt_project>dbt compile
20:21:56 Running with dbt=1.3.1
20:21:56 [WARNING]: Configuration paths exist in your dbt_project.yml file which do not apply to any resources.
There are 1 unused configuration paths:
models.dbt_project.example
20:21:56 Found 0 models, 0 tests, 0 snapshots, 0 analyses, 339 macros, 0 operations, 0 seed files, 0 sources, 0 exposures, 0 metrics
20:21:56
20:21:56 [WARNING]: Nothing to do. Try checking your model configs and model specification args
20:21:56 Done.
and the adapter is dby-synapse
dbt_project.yml
name: 'dbt_project'
version: '1.0.0'
config-version: 2
profile: 'dbt_project'
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]
target-path: "target"
clean-targets:
- "target"
- "dbt_packages"
models:
dbt_project:
example:
+materialized: view
dbt init dbt_projct...
Note: dbt debug.. all is successful
Configuration:
profiles.yml file [OK found and valid]
dbt_project.yml file [OK found and valid]
Required dependencies:
git [OK found]
Connection test: [OK connection ok]
All checks passed!
when compiling or run get the error
My case was folder issue.. i was running the dbt from wrong folder
Related
dbt version: 1.3.1
python version: 3.9.6
adapter = dbt-synapse.yml
# profiles.yml
default: dbt_project
dbt_project:
target: dev
outputs:
dev:
type: synapse
driver: 'ODBC Driver 17 for SQL Server'
server: XXXXXXX
database: ###
port: 1433
schema: #######
user: ######
password: #####
azure_blob:
target: dev
outputs:
dev:
type: azure_blob
account_name: ##
account_key: ##
container: ##
prefix: delta_lake
--- after implied this change here is the error message a get--01/30/2023--- #2:32 pm central time----
i get this error when try to read the file from azure blob storage
-- the is the profiles.yml--------
default: dbt_project
dbt_project:
target: dev
outputs:
dev:
type: synapse #synapse #type: Azuresynapse
driver: 'ODBC Driver 17 for SQL Server' # (The ODBC Driver installed on your system)
server: XXXXXXX
database: XXXXXXX
port: 1433
schema: XXXXXXX
#authentication: sqlpassword
user: XXXXXXX
password: XXXXXXX
azure_blob:
type: azure_blob
account_name: XXXXXXX
account_key: XXXXXXX
container: data-platform-archive #research-container/Bronze/Freedom/ABS_VESSEL/
prefix: abc/FGr1/fox/
--------------- dbt_project.yml-------------------------
name or the intended use of these models
name: 'dbt_project'
version: '1.0.0'
config-version: 2
# This setting configures which "profile" dbt uses for this project.
profile: 'dbt_project'
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]
target-path: "target"
clean-targets:
- "target"
- "dbt_packages"
models:
dbt_project:
staging:
+materialized: table
utilities:
+materialized: view
azure_Blob:
staging:
+materialized: view
--------------------------------
Model name=dbt_stg_DL_abs_acm_users.sql"
and here is the code
{{ config(
materialized='view',
connection='azure_blob'
) }}
select *
from {{ source('data-platform-archive/abc/FGr1/fox/', 'abc.parquet') }}
Compilation Error in model dbt_stg_DL_abs_acm_users
Model 'model.dbt_project.dbt_stg_DL_abs_acm_users' 'abc.parquet' which was not found
Yes, what you've shown here is multiple profiles in a single profiles.yml file. However, there is no default key in the profiles.yml file, since the profile must be specified by the project.
In your dbt_project.yml file, there is a key that names the profile that the project should use. This project config use the dbt_project profile that you have defined:
# dbt_project.yml
name: 'jaffle_shop'
profile: 'dbt_project'
And this one will use the azure_blob profile that you have defined:
# dbt_project.yml
name: 'jaffle_shop'
profile: 'azure_blob'
This is a common pattern if you are developing on multiple projects on a single machine. For a SINGLE project, it is more common to define multiple targets:
# profiles.yml
dbt_project:
target: dev
outputs:
dev:
type: synapse
...
blob:
type: azure_blob
...
You can select which target to use at runtime by passing the -t or --target parameter to the CLI: dbt run -t blob would run the project against the azure_blob connection. The target: dev line in the file above specifies that the dev target (so the Synapse connection) should be the default, if the target is not specified at runtime.
It's somewhat unusual to have multiple targets use different types of databases, and some care must be taken to write compatible syntax. But it is possible -- many packages do this for integration tests, for example.
I followed this tutorial for cross compilation of aarch64
https://www.tensorflow.org/lite/guide/build_arm
1- I cloned tensorflow repo
2- ran bazel build --config=elinux_aarch64 -c opt //tensorflow/lite:libtensorflowlite.so
logs
INFO: Options provided by the client:
Inherited 'common' options: --isatty=1 --terminal_columns=211
INFO: Reading rc options for 'build' from c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc:
Inherited 'common' options: --experimental_repo_remote_exec
INFO: Options provided by the client:
'build' options: --python_path=C:/Users/Mohamed_Gamal/AppData/Local/Microsoft/WindowsApps/python.exe
INFO: Reading rc options for 'build' from c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc:
'build' options: --define framework_shared_object=true --java_toolchain=//tensorflow/tools/toolchains/java:tf_java_toolchain --host_java_toolchain=//tensorflow/tools/toolchains/java:tf_java_toolchain --define=use_fast_cpp_protos=true --define=allow_oversize_protos=true --spawn_strategy=standalone -c opt --announce_rc --define=grpc_no_ares=true --noincompatible_remove_legacy_whole_archive --enable_platform_specific_config --define=with_xla_support=true --config=short_logs --config=v2 --define=no_aws_support=true --define=no_hdfs_support=true --experimental_cc_shared_library --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,tensorflow/compiler/mlir/tfrt/jit/python_binding,tensorflow/compiler/mlir/tfrt/jit/transforms,tensorflow/compiler/mlir/tfrt/python_tests,tensorflow/compiler/mlir/tfrt/tests,tensorflow/compiler/mlir/tfrt/tests/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,tensorflow/compiler/mlir/tfrt/tests/tf_to_corert,tensorflow/compiler/mlir/tfrt/tests/tf_to_tfrt_data,tensorflow/compiler/mlir/tfrt/tests/saved_model,tensorflow/compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/tfrt/common,tensorflow/core/tfrt/eager,tensorflow/core/tfrt/eager/backends/cpu,tensorflow/core/tfrt/eager/backends/gpu,tensorflow/core/tfrt/eager/core_runtime,tensorflow/core/tfrt/eager/cpp_tests/core_runtime,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/core/tfrt/runtime,tensorflow/core/tfrt/saved_model,tensorflow/core/tfrt/graph_executor,tensorflow/core/tfrt/saved_model/tests,tensorflow/core/tfrt/tpu,tensorflow/core/tfrt/utils
INFO: Found applicable config definition build:short_logs in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --output_filter=DONT_MATCH_ANYTHING
INFO: Found applicable config definition build:v2 in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
INFO: Found applicable config definition build:elinux_aarch64 in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --config=elinux --cpu=aarch64 --distinct_host_configuration=true
INFO: Found applicable config definition build:elinux in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --crosstool_top=#local_config_embedded_arm//:toolchain --host_crosstool_top=#bazel_tools//tools/cpp:toolchain
INFO: Found applicable config definition build:windows in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --copt=/W0 --copt=/D_USE_MATH_DEFINES --host_copt=/D_USE_MATH_DEFINES --cxxopt=/std:c++14 --host_cxxopt=/std:c++14 --config=monolithic --copt=-DWIN32_LEAN_AND_MEAN --host_copt=-DWIN32_LEAN_AND_MEAN --copt=-DNOGDI --host_copt=-DNOGDI --copt=/experimental:preprocessor --host_copt=/experimental:preprocessor --linkopt=/DEBUG --host_linkopt=/DEBUG --linkopt=/OPT:REF --host_linkopt=/OPT:REF --linkopt=/OPT:ICF --host_linkopt=/OPT:ICF --verbose_failures --features=compiler_param_file --distinct_host_configuration=false
INFO: Found applicable config definition build:monolithic in file c:\users\mohamed_gamal\downloads\tensorflow_src.bazelrc: --define framework_shared_object=false
WARNING: Download from https://storage.googleapis.com/mirror.tensorflow.org/github.com/tensorflow/runtime/archive/9df1c45bd751eeff53f6811501e015c7eba4b536.tar.gz failed: class com.google.devtools.build.lib.bazel.repository.downloader.UnrecoverableHttpException GET returned 404 Not Found
WARNING: Download from https://mirror.bazel.build/github.com/bazelbuild/rules_cc/archive/081771d4a0e9d7d3aa0eed2ef389fa4700dfb23e.tar.gz failed: class com.google.devtools.build.lib.bazel.repository.downloader.UnrecoverableHttpException GET returned 404 Not Found
INFO: Repository local_config_embedded_arm instantiated at:
C:/users/mohamed_gamal/downloads/tensorflow_src/WORKSPACE:15:14: in
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/workspace2.bzl:868:19: in workspace
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/workspace2.bzl:118:34: in _tf_toolchains
Repository rule arm_linux_toolchain_configure defined at:
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/tools/toolchains/embedded/arm-linux/arm_linux_toolchain_configure.bzl:34:48: in
ERROR: An error occurred during the fetch of repository 'local_config_embedded_arm':
Traceback (most recent call last):
File "C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/tools/toolchains/embedded/arm-linux/arm_linux_toolchain_configure.bzl", line 23, column 9, in _arm_linux_toolchain_configure_impl
_tpl(repository_ctx, "cc_config.bzl", {
File "C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/tools/toolchains/embedded/arm-linux/arm_linux_toolchain_configure.bzl", line 6, column 28, in _tpl
repository_ctx.template(
Error in template: Unable to load package for //tensorflow/tools/toolchains/embedded/arm-linux:cc_config.bzl.tpl: BUILD file not found in any of the following directories. Add a BUILD file to a directory to mark it as a package.
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/tools/toolchains/embedded/arm-linux
DEBUG: Rule 'io_bazel_rules_docker' indicated that a canonical reproducible form can be obtained by modifying arguments shallow_since = "1596824487 -0400"
DEBUG: Repository io_bazel_rules_docker instantiated at:
C:/users/mohamed_gamal/downloads/tensorflow_src/WORKSPACE:23:14: in
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/workspace0.bzl:110:34: in workspace
C:/users/mohamed_gamal/_bazel_mohamed_gamal/wmmhak3q/external/bazel_toolchains/repositories/repositories.bzl:35:23: in repositories
Repository rule git_repository defined at:
C:/users/mohamed_gamal/_bazel_mohamed_gamal/wmmhak3q/external/bazel_tools/tools/build_defs/repo/git.bzl:199:33: in
ERROR: C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/lite/BUILD:1158:24: //tensorflow/lite:libtensorflowlite.so depends on #local_config_embedded_arm//:toolchain in repository #local_config_embedded_arm which failed to fetch. no such package '#local_config_embedded_arm//': Unable to load package for //tensorflow/tools/toolchains/embedded/arm-linux:cc_config.bzl.tpl: BUILD file not found in any of the following directories. Add a BUILD file to a directory to mark it as a package.
C:/users/mohamed_gamal/downloads/tensorflow_src/tensorflow/tools/toolchains/embedded/arm-linux
ERROR: Analysis of target '//tensorflow/lite:libtensorflowlite.so' failed; build aborted: Analysis failed
INFO: Elapsed time: 0.724s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (0 packages loaded, 0 targets configured)
I want to use tensorflow's c++ api to inference in my project, when I build it for cpu, it's ok. But when I build it for support gpu (bazel build --config=cuda ...), it has some error.
My WORKSPACE:
http_archive(
name = "org_tensorflow",
strip_prefix = "tensorflow-1.15.0",
sha256 = "a5d49c00a175a61da7431a9b289747d62339be9cf37600330ad63b611f7f5dc9",
urls = ["https://github.com/tensorflow/tensorflow/archive/v1.15.0.tar.gz"]
)
load("#org_tensorflow//tensorflow:workspace.bzl", "tf_workspace")
tf_workspace(tf_repo_name = "org_tensorflow")
# Uncomment the following two lines has the same error.
# load("#org_tensorflow//third_party/gpus:cuda_configure.bzl", "cuda_configure")
# cuda_configure(name="local_config_cuda")
My .bazelrc:
...
# config for using cuda
build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true
build:cuda --action_env TF_NEED_CUDA=1
build:cuda --crosstool_top=#local_config_cuda//crosstool:toolchain
...
My BUILD:
cc_library(
name = "tf_utils",
srcs = ["tf_utils.cpp"],
hdrs = ["tf_utils.h"],
deps = ["#org_tensorflow//tensorflow/cc/saved_model:loader"
"#org_tensorflow//tensorflow/core:tensorflow"]
)
cc_binarary(
name = "test",
srcs = ["test.cpp"],
deps = ["tf_utils"]
)
When I run bazel build --config=cuda //:test
The error message is：
ERROR: external/com_google_protobuf/BUILD:405:1: C++ compilation of rule '#com_google_protobuf//:protoc' failed (Exit 1) crosstool_wrapper_driver_is_not_gcc failed: error executing command external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -MD -MF bazel-out/host/bin/external/com_google_protobuf/_objs/protoc/main.d ... (remaining 46 argument(s) skipped)
Use --sandbox_debug to see verbose messages from the sandbox
src/main/tools/linux-sandbox-pid1.cc:413: "execvp(external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc, 0x6dfe10)": No such file or directory
Target //:test failed to build
Use --verbose_failures to see the command lines of failed build steps.
The error message shows no such file or directory, but it does exist.
# ls -la external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
-rwxrwxr-x 1 root root 9129 Dec 1 14:14 external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc*
The tensorflow version is 1.15, bazel version is 3.1.0.
Does anyone know how to configure bazel correctly so that tensorflow can support gpu as an external dependency? Thanks very much.
The branch was previously functional, then merged to master and the builds on master failed. Master was reverted, then master was merged into this branch and some fixes were made. When attempting to merge back to master, the build failed again with the following error. The push passed, the pr failed.
* What went wrong:
Could not resolve all files for configuration ':app:debugCompileClasspath'.
> Could not find com.squareup.leakcanary:leakcanary-android:1.5.4.
The travis.yml file:
sudo: false
language: android
android:
components:
- build-tools-27.0.2
- android-27
- sys-img-armeabi-v7a-android-27
jdk:
- oraclejdk8
before_install:
- yes | sdkmanager "platforms;android-27"
- chmod +x gradlew
#First app is built then unit tests are run
jobs:
include:
- stage: build
async: true
script: ./gradlew assemble
- stage: test
async: true
script: ./gradlew -w runUnitTests
notifications:
email:
recipients:
- email#me.com
on_success: always # default: change
on_failure: always # default: always
I felt maven repo outage today and faced the same issue. Hours later, I found that the failed Travis Job is working fine now. Do check it at your side.
Also, For any given scenario when classpath dependencies are missing one should check the build.gradle file rather than the .travis.yml file.
The failure message says that the app:debugCompileClasspath task is failing when looking for the com.squareup.leakcanary:leakcanary-android:1.5.4 (jar or AAR). Gradle allows you to define the repositories at the the root level
allProjects{
repositories {
maven() //Gradle has definition the points to https://jcenter.bintray.com/
}
}
So it will look into the following places for the class files or jar file.
Name: $ANDROID_HOME/extras/m2repository; url: file:/$ANDROID_HOME/extras/m2repository/
Name: $ANDROID_HOME/extras/google/m2repository; url: $ANDROID_HOME/extras/google/m2repository/
Name: $ANDROID_HOME/extras/android/m2repository; url: file:$ANDROID_HOME/extras/android/m2repository/
Name: BintrayJCenter; url: https://jcenter.bintray.com/
If not found the dependency resolution will fail giving the error mentioned above.
I'm completely new to bazel and tensorflow so the solution to this may be obvious to someone with some experience. My bazel build of tensorflow fails with a "missing dependency" error message. Here is the relevant sequence of build commands and output:
(tf-gpu)kss#linux-9c32:~/projects> git clone --recurse-submodules https://github.com/tensorflow/tensorflow tensorflow-nogpu
Cloning into 'tensorflow-nogpu'...
remote: Counting objects: 16735, done.
remote: Compressing objects: 100% (152/152), done.
remote: Total 16735 (delta 73), reused 0 (delta 0), pack-reused 16583
Receiving objects: 100% (16735/16735), 25.25 MiB | 911.00 KiB/s, done.
Resolving deltas: 100% (10889/10889), done.
Checking connectivity... done.
Submodule 'google/protobuf' (https://github.com/google/protobuf.git) registered for path 'google/protobuf'
Cloning into 'google/protobuf'...
remote: Counting objects: 30266, done.
remote: Compressing objects: 100% (113/113), done.
remote: Total 30266 (delta 57), reused 0 (delta 0), pack-reused 30151
Receiving objects: 100% (30266/30266), 28.90 MiB | 1.98 MiB/s, done.
Resolving deltas: 100% (20225/20225), done.
Checking connectivity... done.
Submodule path 'google/protobuf': checked out '0906f5d18a2548024b511eadcbb4cfc0ca56cd67'
(tf-gpu)kss#linux-9c32:~/projects> cd tensorflow-nogpu/
(tf-gpu)kss#linux-9c32:~/projects/tensorflow-nogpu> ./configure
Please specify the location of python. [Default is /home/kss/.venv/tf-gpu/bin/python]:
Do you wish to build TensorFlow with GPU support? [y/N]
No GPU support will be enabled for TensorFlow
Configuration finished
(tf-gpu)kss#linux-9c32:~/projects/tensorflow-nogpu> bazel build -c opt //tensorflow/tools/pip_package:build_pip_package
Sending SIGTERM to previous Bazel server (pid=8491)... done.
....
INFO: Found 1 target...
ERROR: /home/kss/.cache/bazel/_bazel_kss/b97e0e942a10977a6b42467ea6712cbf/external/re2/BUILD:9:1: undeclared inclusion(s) in rule '#re2//:re2':
this rule is missing dependency declarations for the following files included by 'external/re2/re2/perl_groups.cc':
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/stddef.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/stdarg.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/stdint.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/x86intrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/ia32intrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/mmintrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/xmmintrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/mm_malloc.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/emmintrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/immintrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/fxsrintrin.h'
'/usr/lib64/gcc/x86_64-suse-linux/4.8/include/adxintrin.h'.
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 144.661s, Critical Path: 1.18s
(tf-gpu)kss#linux-9c32:~/projects/tensorflow-nogpu>
The version of bazel I'm using is release 0.1.4, I'm running on openSUSE 13.2. I confirmed that the header files do exist which is probably expected:
(tf-gpu)kss#linux-9c32:~/projects/tensorflow-nogpu> ll /usr/lib64/gcc/x86_64-suse-linux/4.8/include/stddef.h
-rw-r--r-- 1 root root 13619 Oct 6 2014 /usr/lib64/gcc/x86_64-suse-linux/4.8/include/stddef.h
Note for anyone who finds this question:
Use Damien's answer below except that you have to use --crosstool_top rather than --crosstool. Also if you are building for GPU acceleration you will also need to modify the CROSSTOOL file in the tensorflow repo like:
(tf-gpu)kss#linux-9c32:~/projects/tensorflow-gpu> git diff third_party/gpus/crosstool/CROSSTOOL | cat
diff --git a/third_party/gpus/crosstool/CROSSTOOL b/third_party/gpus/crosstool/CROSSTOOL
index dfde7cd..b63f950 100644
--- a/third_party/gpus/crosstool/CROSSTOOL
+++ b/third_party/gpus/crosstool/CROSSTOOL
## -56,6 +56,7 ## toolchain {
cxx_builtin_include_directory: "/usr/lib/gcc/"
cxx_builtin_include_directory: "/usr/local/include"
cxx_builtin_include_directory: "/usr/include"
+ cxx_builtin_include_directory: "/usr/lib64/gcc"
tool_path { name: "gcov" path: "/usr/bin/gcov" }
# C(++) compiles invoke the compiler (as that is the one knowing where
You should tweak the C++ compiler.
To do so, here's the best way to proceed:
edit the file tools/cpp/CROSSTOOL (https://github.com/bazelbuild/bazel/blob/master/tools/cpp/CROSSTOOL) from your package path directory (should be in ~/.bazel/base_workspace, can be found with bazel info package_path) to add a line cxx_builtin_include_directory: /usr/lib64/gcc around line 100 (see https://github.com/bazelbuild/bazel/blob/master/tools/cpp/CROSSTOOL#L101).
Then echo "build --crosstool=//tools/cpp:toolchain" >>~/.bazelrc and then retries to build.
Sorry for the mess, we are working on making C++ toolchain work better out of the box.
Bazel complaints of system header files because compiler uses -MD (as opposed to -MMD) flag when generating dependences. While using -MD is reasonable for an environment that changes often, listing dependency on system header files causes the 'missing dependency declarations' errors.
What helped me was converting the '-MD' flag into '-MMD' flag in the compiler wrapper files third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc.tpl just before 'subprocess.call([CPU_COMPILER]...)':
cpu_compiler_flags = ['-MMD' if flag == '-MD' else flag for flag in cpu_compiler_flags]
and third_party/sycl/crosstool/computecpp.tpl, similar place:
computecpp_device_compiler_flags = ['-MMD' if flag == '-MD' else flag for flag in computecpp_device_compiler_flags]