[GitHub] [tvm] mehrdadh commented on a diff in pull request #12182: [microTVM][tutorial] AOT host-driven tutorial with TFLite model

[GitBox <gi...@apache.org>]

mehrdadh commented on code in PR #12182:
URL: https://github.com/apache/tvm/pull/12182#discussion_r930240740


##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,162 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with
+a TFLite model. This tutorial can be executed on a X86 CPU using C runtime (CRT)
+or on Zephyr plarform on a microcontroller that supports Zephyr platform.

Review Comment:
   done



##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,162 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with
+a TFLite model. This tutorial can be executed on a X86 CPU using C runtime (CRT)
+or on Zephyr plarform on a microcontroller that supports Zephyr platform.
+"""
+
+import numpy as np
+import pathlib
+import json
+import os
+
+import tvm
+from tvm import relay
+from tvm.relay.backend import Executor, Runtime
+from tvm.contrib.download import download_testdata
+
+######################################################################
+# Import a TFLite model
+# ---------------------
+#
+# To begin with, download and import a TFLite model from TinyMLPerf models.

Review Comment:
   I added comment about the origin of the model and fixed MLPerf Tiny name.



##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,162 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with

Review Comment:
   added few comments, please take another look.



##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,168 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with
+a TFLite model. This tutorial can be executed on a X86 CPU using C runtime (CRT)

Review Comment:
   done.



##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,168 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with
+a TFLite model. This tutorial can be executed on a X86 CPU using C runtime (CRT)
+or on Zephyr plarform on a microcontroller that supports Zephyr platform.
+"""
+
+# sphinx_gallery_start_ignore
+from tvm import testing
+
+testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
+import numpy as np
+import pathlib
+import json
+import os
+
+import tvm
+from tvm import relay
+from tvm.relay.backend import Executor, Runtime
+from tvm.contrib.download import download_testdata
+
+######################################################################
+# Import a TFLite model
+# ---------------------
+#
+# To begin with, download and import a TFLite model from TinyMLPerf models.
+#
+# **Note:** By default this tutorial runs on X86 CPU using CRT, if you would like to run on Zephyr platform
+# you need to export `TVM_MICRO_USE_HW` environment variable.
+#
+use_physical_hw = bool(os.getenv("TVM_MICRO_USE_HW"))
+MODEL_URL = "https://github.com/tlc-pack/web-data/raw/main/testdata/microTVM/model/keyword_spotting_quant.tflite"
+MODEL_PATH = download_testdata(MODEL_URL, "keyword_spotting_quant.tflite", module="model")
+SAMPLE_URL = "https://github.com/tlc-pack/web-data/raw/main/testdata/microTVM/data/keyword_spotting_int8_6.pyc.npy"
+SAMPLE_PATH = download_testdata(SAMPLE_URL, "keyword_spotting_int8_6.pyc.npy", module="data")
+
+tflite_model_buf = open(MODEL_PATH, "rb").read()
+try:
+    import tflite
+
+    tflite_model = tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+except AttributeError:
+    import tflite.Model
+
+    tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+input_shape = (1, 49, 10, 1)
+INPUT_NAME = "input_1"
+relay_mod, params = relay.frontend.from_tflite(
+    tflite_model, shape_dict={INPUT_NAME: input_shape}, dtype_dict={INPUT_NAME: "int8"}
+)
+
+######################################################################
+# Defining the target
+# -------------------
+#
+# Now we need to define the target, runtime and executor. In this tutorial, we focused on
+# using AOT host driven executor. We use the host micro target which is for running a model

Review Comment:
   added



##########
gallery/how_to/work_with_microtvm/micro_aot.py:
##########
@@ -0,0 +1,168 @@
+# 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.
+"""
+.. _tutorial-micro-AoT:
+
+microTVM Host-Driven AoT
+===========================
+**Authors**:
+`Mehrdad Hessar <https://github.com/mehrdadh>`_,
+`Alan MacDonald <https://github.com/alanmacd>`_
+
+This tutorial is showcasing microTVM host-driven AoT compilation with
+a TFLite model. This tutorial can be executed on a X86 CPU using C runtime (CRT)
+or on Zephyr plarform on a microcontroller that supports Zephyr platform.
+"""
+
+# sphinx_gallery_start_ignore
+from tvm import testing
+
+testing.utils.install_request_hook(depth=3)
+# sphinx_gallery_end_ignore
+
+import numpy as np
+import pathlib
+import json
+import os
+
+import tvm
+from tvm import relay
+from tvm.relay.backend import Executor, Runtime
+from tvm.contrib.download import download_testdata
+
+######################################################################
+# Import a TFLite model
+# ---------------------
+#
+# To begin with, download and import a TFLite model from TinyMLPerf models.
+#
+# **Note:** By default this tutorial runs on X86 CPU using CRT, if you would like to run on Zephyr platform
+# you need to export `TVM_MICRO_USE_HW` environment variable.
+#
+use_physical_hw = bool(os.getenv("TVM_MICRO_USE_HW"))

Review Comment:
   added that.



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