[microTVM] Enable micro tvmc tutorial testing in CI

docs/script_convert.py

@@ -0,0 +1,94 @@
+# 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
+# to you under the Apache License, Version 2.0 (the
+# "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
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import argparse
+import pathlib
+
+BASH = "# bash"
+BASH_IGNORE = "# bash-ignore"
+BASH_MULTILINE_COMMENT_START = ": '"
+BASH_MULTILINE_COMMENT_END = "'"
+
+
+def bash_to_python(src_path: pathlib.Path, dest_path: pathlib.Path):
+    """Convert a bash script file to a Python format compatible with Sphinx doc."""
+    with open(src_path, "r") as src_f:
+        with open(dest_path, "w") as dest_f:
+            line = src_f.readline()
+            bash_block = []
+            bash_detected = False
+            bash_ignore_detected = False
+            new_line_required = False
+            while line:
+                line = line.strip("\n").strip("\r")
+                if bash_detected:
+                    if line == BASH:
+                        # write the bash block to destination
+                        if new_line_required:
+                            dest_f.write("\n")
+                        python_code = "# .. code-block:: bash\n#\n"
+                        for bash_line in bash_block:
+                            python_code += f"#\t  {bash_line}\n"
+                        python_code += "#"
+                        dest_f.write(python_code)
+
+                        bash_detected = False
+                        bash_block = []
+                        new_line_required = True
+                    else:
+                        # add new bash command line
+                        bash_block.append(line)
+                elif bash_ignore_detected:
+                    if line == BASH_IGNORE:
+                        bash_ignore_detected = False
+                        new_line_required = True
+                    else:
+                        new_line_required = False
+                        pass
+                else:
+                    if line == BASH:
+                        bash_detected = True
+                    elif line == BASH_IGNORE:
+                        bash_ignore_detected = True
+                    elif line in [BASH_MULTILINE_COMMENT_START, BASH_MULTILINE_COMMENT_END]:
+                        if new_line_required:
+                            dest_f.write("\n")
+                        dest_f.write('"""')
+                        new_line_required = True
+                    else:
+                        if new_line_required:
+                            dest_f.write("\n")
+                        dest_f.write(f"{line}")
+                        new_line_required = True
+
+                line = src_f.readline()
+            if new_line_required:
+                dest_f.write("\n")
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Convert tutorial script to Python.")
+    parser.add_argument("script", type=str, help="Path to script file.")
+    args = parser.parse_args()
+
+    src_path = pathlib.Path(args.script)
+    dest_path = src_path.parent / f"{src_path.stem}.py"
+    bash_to_python(src_path, dest_path)
+
+
+if __name__ == "__main__":
+    main()

gallery/how_to/work_with_microtvm/micro_tvmc.py → gallery/how_to/work_with_microtvm/micro_tvmc.sh

@@ -15,7 +15,7 @@
 # specific language governing permissions and limitations
 # under the License.
 
-"""
+: '
 .. _tutorial-micro-tvmc:
 
 Executing a Tiny Model with TVMC Micro
@@ -25,7 +25,7 @@
 This tutorial explains how to compile a tiny model for a micro device,
 build a program on Zephyr platform to execute this model, flash the program
 and run the model all using `tvmc micro` command.
-"""
+'
 
 ######################################################################
 # .. note::
@@ -42,6 +42,10 @@
 #       ./docker/bash.sh tlcpack/ci-qemu
 #
 
+# bash-ignore
+shopt -s expand_aliases
+alias tvmc="python3 -m tvm.driver.tvmc"
+# bash-ignore
 
 ############################################################
 # Using TVMC Micro
@@ -55,16 +59,15 @@
 #
 # To check if you have TVMC command installed on your machine, you can run:
 #
-# .. code-block:: bash
-#
-#     tvmc --help
-#
+# bash
+tvmc --help
+# bash
 # To compile a model for microtvm we use ``tvmc compile`` subcommand. The output of this command
 # is used in next steps with ``tvmc micro`` subcommands. You can check the availability of TVMC Micro using:
 #
-# .. code-block:: bash
-#
-#     tvmc micro --help
+# bash
+tvmc micro --help
+# bash
 #
 # The main tasks that you can perform using ``tvmc micro`` are ``create``, ``build`` and ``flash``.
 # To read about specific options under a givern subcommand, use
@@ -80,10 +83,9 @@
 #
 # For this tutorial we will be using the model in tflite format.
 #
-# .. code-block:: bash
-#
-#     wget https://github.com/tensorflow/tflite-micro/raw/main/tensorflow/lite/micro/examples/magic_wand/magic_wand.tflite
-#
+# bash
+wget https://github.com/tensorflow/tflite-micro/raw/main/tensorflow/lite/micro/examples/magic_wand/magic_wand.tflite
+# bash
 
 ############################################################
 # Compiling a TFLite model to a Model Library Format
@@ -95,19 +97,18 @@
 #
 # Here, we generate a MLF file for ``qemu_x86`` Zephyr board. To generate MLF output for the ``magic_wand`` tflite model:
 #
-# .. code-block:: bash
-#
-#     tvmc compile magic_wand.tflite \
-#       --target='c -keys=cpu -link-params=0 -model=host' \
-#       --runtime=crt \
-#       --runtime-crt-system-lib 1 \
-#       --executor='graph' \
-#       --executor-graph-link-params 0 \
-#       --output model.tar \
-#       --output-format mlf \
-#       --pass-config tir.disable_vectorize=1 \
-#       --disabled-pass=AlterOpLayout
-#
+# bash
+tvmc compile magic_wand.tflite \
+    --target='c -keys=cpu -link-params=0 -model=host' \
+    --runtime=crt \
+    --runtime-crt-system-lib 1 \
+    --executor='graph' \
+    --executor-graph-link-params 0 \
+    --output model.tar \
+    --output-format mlf \
+    --pass-config tir.disable_vectorize=1 \
+    --disabled-pass=AlterOpLayout
+# bash
 # This will generate a ``model.tar`` file which contains TVM compiler output files. To run this command for
 # a different Zephyr device, you need to update ``target``. For instance, for ``nrf5340dk_nrf5340_cpuapp`` board
 # the target is ``--target='c -keys=cpu -link-params=0 -model=nrf5340dk'``.
@@ -122,14 +123,13 @@
 # for the project to ``create`` subcommand along with project options. Project options for each
 # platform (Zephyr/Arduino) are defined in their Project API server file. To generate Zephyr project, run:
 #
-# .. code-block:: bash
-#
-#     tvmc micro create \
-#       project \
-#       model.tar \
-#       zephyr \
-#       --project-option project_type=host_driven zephyr_board=qemu_x86
-#
+# bash
+tvmc micro create \
+    project \
+    model.tar \
+    zephyr \
+    --project-option project_type=host_driven zephyr_board=qemu_x86
+# bash
 # This will generate a ``Host-Driven`` Zephyr project for ``qemu_x86`` Zephyr board. In Host-Driven template project,
 # the Graph Executor will run on host and perform the model execution on Zephyr device by issuing commands to the
 # device using an RPC mechanism. Read more about `Host-Driven Execution <https://tvm.apache.org/docs/arch/microtvm_design.html#host-driven-execution>`_.
@@ -148,26 +148,24 @@
 # Next step is to build the Zephyr project which includes TVM generated code for running the tiny model, Zephyr
 # template code to run a model in Host-Driven mode and TVM runtime source/header files. To build the project:
 #
-# .. code-block:: bash
-#
-#     tvmc micro build \
-#       project \
-#       zephyr \
-#       --project-option zephyr_board=qemu_x86
-#
+# bash
+tvmc micro build \
+    project \
+    zephyr \
+    --project-option zephyr_board=qemu_x86
+# bash
 # This will build the project in ``project`` directory and generates binary files under ``project/build``. To build
 # Zephyr project for a different Zephyr board, change ``zephyr_board`` project option.
 #
 # Next, we flash the Zephyr binary file to Zephyr device. For ``qemu_x86`` Zephyr board this step does not
 # actually perform any action since QEMU will be used, however you need this step for physical hardware.
 #
-# .. code-block:: bash
-#
-#     tvmc micro flash \
-#       project \
-#       zephyr \
-#       --project-option zephyr_board=qemu_x86
-#
+# bash
+tvmc micro flash \
+    project \
+    zephyr \
+    --project-option zephyr_board=qemu_x86
+# bash
 
 ############################################################
 # Run Tiny Model on Micro Target
@@ -179,14 +177,14 @@
 # and pass ``--device micro`` to specify the device type. This command will open a communication channel, set input
 # values using ``Graph Executor`` on host and run full model on the device. Then it gets output from the device.
 #
-# .. code-block:: bash
-#
-#     tvmc run \
-#       --device micro \
-#       project \
-#       --project-option zephyr_board=qemu_x86 \
-#       --fill-mode ones
-#       --print-top 4
+# bash
+tvmc run \
+    --device micro \
+    project \
+    --project-option zephyr_board=qemu_x86 \
+    --fill-mode ones \
+    --print-top 4
+# bash
 #     # Output:
 #     #
 #     # INFO:__main__:b'[100%] [QEMU] CPU: qemu32,+nx,+pae\n'

tests/python/unittest/test_ci.py → tests/python/ci/test_ci.py

@@ -15,16 +15,13 @@
 # specific language governing permissions and limitations
 # under the License.
 
-import pathlib
 import subprocess
 import sys
 import json
 import textwrap
-import tempfile
-
 import pytest
 
-REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent.parent.parent
+from test_utils import REPO_ROOT
 
 
 class TempGit: