ashutosh-arm commented on a change in pull request #8833: URL: https://github.com/apache/tvm/pull/8833#discussion_r695598599
########## File path: python/tvm/relay/backend/contrib/cmsisnn/codegen.py ########## @@ -0,0 +1,140 @@ +# 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. +"""Codegen for CMSIS-NN""" +import tvm +from tvm import relay +from tvm.relay.expr_functor import ExprVisitor + + +def generate_tir(name, func): + """Generates TIR""" + + class GenerateTIR(ExprVisitor): + """Generates TIR module containing TIR primfuncs corresponding to the Relay operators. + Note: Relay operator to primfunc mapping may not be 1:1. + """ + + def __init__(self, name): + super().__init__() + self.name = name + self.tir_mod = None + self.scale = 1.0 / 256 + + def call_contains_op(self, call, op_name): + if not isinstance(call.op, tvm.ir.op.Op): + return False + if call.op.name != op_name: + return False + return True + + def is_quantized_softmax(self, call): + """Checks for the following relay sequence + a = qnn.dequantize(in, scale, zero_point) + b = nn.softmax(a) + c = qnn.quantize(c, scale, zero_point) + """ + if not self.call_contains_op(call, "qnn.quantize"): + return False + softmax_call = call.args[0] + if not self.call_contains_op(softmax_call, "nn.softmax"): + return False + dequantize_call = softmax_call.args[0] + if not self.call_contains_op(dequantize_call, "qnn.dequantize"): + return False + if not call.attrs.out_dtype == "int8": + return False + self.scale = dequantize_call.args[1].data.numpy().item(0) + return True + + def emit_softmax_tir(self, call): + """Generates TIR extern_call for softmax""" + shape = call.checked_type.shape # NHWC + dtype = call.checked_type.dtype + ir_builder = tvm.tir.ir_builder.create() + in_buf = tvm.tir.decl_buffer(shape=shape, dtype=dtype) + out_buf = tvm.tir.decl_buffer(shape=shape, dtype=dtype) + num_rows = shape[0] * shape[1] * shape[2] + row_size = shape[3] + ir_builder.emit( + tvm.tir.call_extern( + dtype, + "arm_softmax_s8", + in_buf.data, + num_rows, + row_size, + self.scale, + out_buf.data, + ) + ) + prim_func = tvm.tir.PrimFunc([in_buf, out_buf], ir_builder.get()) + prim_func = prim_func.with_attr("global_symbol", self.name) + prim_func = prim_func.with_attr("tir.noalias", True) + self.tir_mod = tvm.IRModule({self.name: prim_func}) + + def visit_call(self, call): + """Iterates over the relay operators within relay external function""" + super().visit_call(call) + if self.is_quantized_softmax(call): + self.emit_softmax_tir(call) + + def generate_tir(self, func): + self.visit(func) + return self.tir_mod + + tir_mod = GenerateTIR(name).generate_tir(func) + return tir_mod + + +def relay_to_tir(name, func): + """Lower a Relay function to TIR for the CMSIS-NN target. + + The Relay function should only contain operations supported + by the CMSIS-NN target. This is enforced by the graph partitioner + for CMSIS-NN. + + Parameters + ---------- + name: str + Name of the external relay function + func : tvm.relay.Function + The Relay function to lower. + + Returns + ------- + mod : tvm.IRModule + The lowered TIR module. + + """ + tir_mod = generate_tir(name, func) + return tir_mod + + +@tvm._ffi.register_func("relay.ext.cmsisnn") +def cmsisnn_compiler(relay_func): + """It compiles Relay's external function into equivalent TIR + and subsequently converts that into 'c' code. During the 'c' + code generation, it embeds CMSIS-NN APIs for the corresponding + operators. + """ + assert isinstance(relay_func, tvm.ir.function.BaseFunc) Review comment: Result of copy-n-paste. But my guess is that non AOT flows might be supplying other types too. -- 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]
