YuchenJin commented on a change in pull request #9315: URL: https://github.com/apache/tvm/pull/9315#discussion_r732416090
########## File path: gallery/tutorial/tensor_ir_blitz_course.py ########## @@ -0,0 +1,135 @@ +# 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. +""" +.. _tir_blitz: + +Blitz Course to TensorIR +======================== +**Author**: `Siyuan Feng <https://github.com/Hzfengsy>`_ + +TensorIR is a domain specific languages for deep learning programs serving two broad purposes: + +- An implement for transforming and optimizing programs on various hardware backends. + +- An abstraction for automatic tensorized program optimization. + +""" + +import tvm +from tvm.script import tir as T +import numpy as np + +################################################################################################ +# IRModule +# -------- +# An IRModule is the central data structure in TensorIR, which contains deep learning programs. +# It is the basic object of interest of IR transformation and model building. +# + + +################################################################################################ +# Create an IRModule +# ------------------ +# IRModule can be created by writing TVMScript, which is a script syntax for TVM IR. (see the ref) Review comment: Did you miss adding the link to the ref? ########## File path: gallery/tutorial/tensor_ir_blitz_course.py ########## @@ -0,0 +1,135 @@ +# 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. +""" +.. _tir_blitz: + +Blitz Course to TensorIR +======================== +**Author**: `Siyuan Feng <https://github.com/Hzfengsy>`_ + +TensorIR is a domain specific languages for deep learning programs serving two broad purposes: + +- An implement for transforming and optimizing programs on various hardware backends. + +- An abstraction for automatic tensorized program optimization. + +""" + +import tvm +from tvm.script import tir as T +import numpy as np + +################################################################################################ +# IRModule +# -------- +# An IRModule is the central data structure in TensorIR, which contains deep learning programs. +# It is the basic object of interest of IR transformation and model building. +# + + +################################################################################################ +# Create an IRModule +# ------------------ +# IRModule can be created by writing TVMScript, which is a script syntax for TVM IR. (see the ref) +# Here is a simple module for vector add. +# + + [email protected]_module +class MyModule: + @T.prim_func + def main(a: T.handle, b: T.handle): + # We exchange data between function by handles, which are similar to pointer. + T.func_attr({"global_symbol": "main", "tir.noalias": True}) + # Create buffer from handles. + A = T.match_buffer(a, (8,), dtype="float32") + B = T.match_buffer(b, (8,), dtype="float32") + for i in range(8): + # A block is an abstraction for computation. + with T.block("B"): + # Define a spatial block iterator and bind it to value i. + vi = T.axis.spatial(8, i) + B[vi] = A[vi] + 1.0 + + +ir_module = MyModule +print(type(ir_module)) +print(ir_module.script()) + +################################################################################################ +# Build and Run an IRModule +# ------------------------- +# We can build the IRModule into a runnable module with specific target backends. +# + +mod = tvm.build(ir_module, target="llvm") # The module for CPU backends. +print(type(mod)) + +################################################################################################ +# Prepare the input array and output array, then run the module. +# + +a = tvm.nd.array(np.arange(8).astype("float32")) +b = tvm.nd.array(np.zeros((8,)).astype("float32")) +mod(a, b) +print(a) +print(b) + + +################################################################################################ +# Transform an IRModule +# --------------------- +# The IRModule is the central data structure for program optimization, which can be transformed +# by :code:`Schedule`. +# Schedule is consist of primitives. Each primitive does a simple job on IR transformation, +# such as loop tiling or make computation parallel. (Please see ref) Review comment: Did you miss the ref? ########## File path: gallery/tutorial/tensor_ir_blitz_course.py ########## @@ -0,0 +1,135 @@ +# 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. +""" +.. _tir_blitz: + +Blitz Course to TensorIR +======================== +**Author**: `Siyuan Feng <https://github.com/Hzfengsy>`_ + +TensorIR is a domain specific languages for deep learning programs serving two broad purposes: + +- An implement for transforming and optimizing programs on various hardware backends. + +- An abstraction for automatic tensorized program optimization. + +""" + +import tvm +from tvm.script import tir as T +import numpy as np + +################################################################################################ +# IRModule +# -------- +# An IRModule is the central data structure in TensorIR, which contains deep learning programs. Review comment: Thanks @Hzfengsy, would it be more precise to say IRModule is the central data structure in TVM (instead of TensorIR)? Might be worth mentioning it can contain a collection of functions including `relay::Function` and `tir::PrimFunc` (since you use `@T.prim_func` in the following code snippets). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
